However, it can be normal for us deep-value investors to feel a slight sense of fatigue when comparing our portfolio performance to those who have more recently outperformed in semiconductors and AI (just ask Terry Smith of Fundsmith). The question then begs, without such headline outperformance, how do we remain competitive in an overvalued world? How do we justify our existence to fiduciaries and stakeholders? Is there still a place for deep-value investing to matter when everyone is losing their heads over AI?

Of course, we won’t venture into justifying our existence simply by claiming that markets are overheated, and therefore one should wait for the house of cards to collapse in a coming recession and therefore be vindicated. While valuations and concentration of the broader index certainly sports irrational exuberance, it comes as little comfort consoling ourselves as such when comparing our portfolio performance to those who are making money in markets hand over fist in today’s markets.

So how would I justify my own existence as a deep-value investor? If I would venture one word, it would be Yield. As fundamental investors who care about investing in businesses, we care first and foremost about the Net Profits and FCF generated by our investee companies over paper profits from capital appreciation of our equity investments in the stock market. This subsequently implies that we care about the earnings or FCF yield generated from our investments, and that we seek for a reasonable investment where we don’t pay too high of a price in exchange for the profits generated.

This means that valuations matter. While our peers might be getting giddy over the rapid capital appreciation of their overvalued shares in what Buffett describes as “casino-like markets”, we remain disciplined in seeking an adequate return from our investments. Not extraordinary returns, simply adequate ones. It can be a hard concept for our heads to screw onto amidst frothy markets, but that’s how we find discipline in time-tested intelligent investing.

Think about it this way. At a 40x PE, you’d have a starting yield of just 2.5%. Even if you assumed 20% persistent earnings growth (a hard assumption), it would still take 12 years before you broke even on a cumulative yield basis. Now imagine you started with 10x PE, or a starting yield of 10% instead. Even with just 10% earnings growth, it’d only take you 8 years before you’d breakeven cumulatively. By year 12, the 10x PE investment would have doubled; in contrast to taking 16 years for the 40x PE investment.

This shows how investing in situations with low valuations can actually pay off more handsomely than investing in situations with high valuations. Furthermore, there tends to be significantly higher uncertainty and volatility when investing in stocks with higher valuations — you’d need every quarter to go right just to see the same level of volatility in the latter as the former. There also tends to be less uncertainty of obtaining the lower growth rate in low valuation situations than expecting the higher growth rates required from high valuation situations to persist over long periods of time.

The second instrumental word I would venture is Risk, or as Graham puts it “safety of principal”. When investing in deep-value situations, it’s just harder to lose your capital. Think about something like PYPL. With built-in expectations already so low, and EPS expected to increase given the huge share buyback authorization, how much more can the share price permanently fall by? Contrast that to something like MU, which sees 10% intra-day swings just from rumors that Meta is about to sell its excess compute dampening memory demand.

This extends to broader macro trends as well. With something already beaten-down like PYPL, it’s likely that there’s a soft floor beneath its valuations should the broader market fall significantly, such as in a recession or a geopolitical war. With something sporting hyperextended valuations like MU, you can expect significant downward volatility or straight-up permanent losses from the evaporation of high expectations should there be an extended recession.

Thus we can conclude that investing in deep-value investments can actually offer higher risk:reward than investing in overvalued investments. And therefore deep-value investors can still justify their existence, whatever the markets might say. Just ask Buffett, who famously invests in situations with an 7x EV/EBIT or less, and who is holding record levels of cash in today’s markets. Given that we are long-term investors, we have the privilege of waiting 10 years to breakeven, so why not benefit from that structural advantage?

Imagine that your portfolio is actually a business, and the funds you put into it represents equity capital. That means your portfolio has its own balance sheet. When you invest in a stock, you acquire its proportionate Net Assets and consolidate them onto your own conglomerate’s balance sheet, and register Goodwill for any amounts you pay in excess of book value. This means you now have an ROA, just like any other business; and assuming you don’t use leverage, your ROA equals your ROE and ROIC.

Now if you were to think of it this way, what would it take to invest in a business with a PE in excess of 40x? There would need to be tremendous growth, because you’d have a starting earnings yield of just 2.5%. For you to earn a 15% ROA, that 2.5% earnings yield would have to grow to 15% over a period of say 10 years to make it worthwhile. That means you’d need to grow earnings by 6x (15/2.5) over 10 years, or 20% per year, without any risk materializing (i.e. with no margin of safety). How many businesses can you think of that can pull off that kind of growth for that long defensively?

Alternatively, let’s say you invest in a business at 20x PE. That’d mean your starting ROA would be 5%, and to grow it to 15% over 10 years, you’d need to grow earnings by just 11% per year. Now, how many businesses can you think of that are offering that kind of growth and are selling for that price today? I can certainly think of a few, and there’d actually still be a margin of safety in the formula.

Thinking of your portfolio as a business really makes you think hard about the sectors that you want to be in, and the stocks that you “invest” in. It also makes you think about the “quality” of your returns, i.e. the defensibility of long-term returns, returns in terms of the market cycle, etc. Importantly, you’re now thinking of your returns as the variable, as opposed to capital gains, and are willing to take different risks when it comes to obtaining an adequate ROA vs. how much your stock price goes up.

It’s also worth mentioning here how quickly narratives can change, and their impact on capital prices. After spending most of early-2026 in the dumps, the Software index IGV just rebounded strongly after Jensen Huang said that the application layer will not be exterminated completely by AI. Likewise, it’s also possible for the narrative for AI/Semi stocks to change to one of pessimism overnight. If you treat your portfolio as a business conglomerate, you’ll be much more sensitive to potentially having to make permanent impairment charges to your equity investments, on top of the mediocre yields from buying in at extended prices.

Buffett once said “I am a better investor because I am a businessman and a better businessman because I am an investor”. Thinking of your portfolio returns as conglomerate ROIC marries the two concepts and makes you think of investing in stocks in a beautifully different way. It also makes you chase different goals in investing and gives you a framework that gets you looking in different parts of the market, thus being differentiated from a competitive perspective.

In the same vein, I also want to touch a bit on Meta. Specifically, how its capital model is changing and how that affects ROIC.

Unlike Alphabet and OpenAI, Meta doesn’t sell its AI services to outside customers. Its AI efforts are of an existential nature, in that it needs to own its own internal foundational model in order to stay competitive without having to rent AI services from outsiders and have its internal data be exposed.

The upshot to this is that Meta should be able to continue its current mouth-watering trend of 20% revenue growth with AI as a new growth vector. The offset to this is that AI-related CAPEX spend is growing even faster. Meta spent about $70B in CAPEX in 2025, nearly double the $40B it spent in 2024, and will spend nearly double that at $130B in 2026.

Let’s put some skin on those bones for a second. Meta’s Property, Plant and Equipment grew to just over $220B in the latest quarter, up from $110B in FY23. Over the same period, its Total Assets nearly doubled as well from $220B to nearly $400B. This means revenues will have to work twice as hard just to maintain their Asset Turnover. If revenue growth doesn’t change while Asset growth doubles, that’s a new structurally worse business model as the ROA halves over time. This is on top of Borrowings increasing from negligible levels to nearly $60B over that same period.

So what’s it worth? Well, the business of running foundational models is a commmoditized business, so let’s say they get a 5% ROA on that CAPEX spend. That means they see roughly $6B in earnings growth on that $130B in FY26 CAPEX. Relative to FY25 earnings of $60B, that represents “just” 10% incremental earnings growth. And it doesn’t get better from there. For every unit of earnings growth, they’d still be getting a 5% ROA on incremental CAPEX. This means that Meta’s business goes from one with a positive ROIIC to potentially one with a negative ROIIC.

If so, is that 20% revenue growth still worth anything, since it comes with the baggage of like Asset growth? Even if they get 10% ROA out of their AI segment, that represents a substantial change in the business model and still “just” 20% earnings growth from monumental CAPEX spend. If the ROE dilutes to 15% as a result, it may no longer command premium equity multiples. This is no longer the legacy capital-light Facebook and Instagram business which grows by 20% organically without incremental CAPEX. It’s a completely new Datacenter business, and I think investors are waking up to that fact.

It also explains why Alphabet recently announced that $80B equity issuance to fund their Datacenter ambitions. These are no longer capital-light businesses growing independently from invested capital, and therefore it makes sense to fund returns from cost of equity. It also explains why Berkshire has invested in Alphabet after spending decades avoiding Tech — this is just another capital-heavy business which requires lots of investment and generates a 5% ROA, which is the staple of Berkshire’s investments. I suppose this is the cost of entry of being in the AI business, and therefore it makes sense that Apple hasn’t dipped its toe into the water yet.

If there’s a moral to the story, it’s that the denominator is just as important as the numerator when it comes to generating a return on capital, which should be the ultimate goal of investing and the driver behind investment decisions. We’re seeing lots of interesting changes to the Tech sector with an evolving AI landscape, and it’ll be interesting to see who the new winners of ROIC will eventually be, just as Google and Facebook were over the past decade.

I think that narrative needs a bit of revisioning. On one hand, yes the moats of these companies are well and truly disrupted. On the other hand, there’s a lot of evidence out there of commoditized businesses in other industries thriving despite the lack of moats. So seeing these Software stocks thrashing and flailing, despite having some of the biggest brands in their space, just elicits a bit of head-scratching from yours truly.

I think what’s really happening is that Software investors who had invested at sky-high valuations and delusional narratives like “Rule of 40” are starting to find that the valuations which depended on such moats existing are evaporating. So the problem isn’t that the underlying businesses are going extinct per se, but rather that investors had paid too high a price on transitional narratives to begin with. It’s a valuation problem, not a business problem.

The businesses themselves are doing fine, and the good news for those who had been on the sidelines watching is that valuations are starting to get into “feels fair” territory. Of course, there are still businesses trading at 50x trailing PE after accounting for share-based compensation, but there are also some great businesses in the 15-20x PE zone whose share prices have been flailing like a fish out of water. It’s honestly reached “time to buy” time, as the feeling goes.

Value investors who are comfortable with waiting and doing nothing for extended periods of time are feeling kinda non-plussed about all this supposed disruption risk. From my perspective, I’m not seeing the possible disruption except in some very obvious instances where the risk is very high-visibility (e.g. Chegg, Duolingo). There are some genuinely great businesses going on sale for no other reason than “everyone is heading for the exits” — fundamentals are actually performing sterlingly. And they seem to be crashing with no end in sight, which I guess is a fear in and of itself.

And therein lies the issue with “growth” or “momentum” investing. Sure it feels great to get that euphoric high from participating with the crowd on a rocketship, but as Buffett puts it you usually pay a high price for a cheery consensus. And there usually isn’t much margin of safety in doing so, as evidenced by how viciously the share price crashes can be when they turn the other way.

Coming back to the Buffett quote, I’m really starting to get into head-scratching zone when it comes to seeing these share prices crashing. The businesses are performing, growth is good, balance sheets are Net Cash… and acquisition prices are falling into bargain levels. I’m starting to nibble, and if prices fall into further head-scratching territory on no apparent news, I’m comfortable buying more and in size. Again, we’re talking about some of the biggest, baddest businesses in the Software sector, which don’t have to worry about companies from the Airline or Energy sector. They just have to worry about each other. And I don’t see where the worry is coming from, even from AI.

How does the value investor find balance when it comes to catching falling knives? Once again, it boils down to valuation. You gotta be comfortable buying at prices where if it falls by -50% from here, your reaction is to get more excited instead of wondering what’s going on. That means you’ve done your research (obviously), and that you’ve reached zen with the valuation such that even if it falls further, you’re okay. It means you hold a bit of cash, and you’re prepared to keep nibbling downwards as the share price continues to decline.

It also means that you waited until now before doing anything. If I’m being honest, there had been times in the recent past when I felt valuations were still stretched on some of these great businesses, but was tempted to make a move despite their valuations still making me uncomfortable. But now that their share prices have fallen to genuinely “valuable” levels, my gut feel is finally feeling right about making these buys and I’m good with splashing some cash in their direction.

A bit of a shameless plug for my recent writeup on GoDaddy. I think it’s a genuinely misunderstood business, and that once again the disruption risk is low. I’ve received feedback from some that Cloudflare is going to disrupt it; but that’s just another major competitor coming into the space of what is already a commoditized sector. It’s tough to disrupt a business which is already commoditized, and what matters in a commoditized industry is economies of scale, which GDDY has.

I’ve already identified a bunch of businesses in the space which are experiencing this “Disruption-but-not-really” phenomenon. And boy are they on sale, and I’m starting to feel comfortable buying from here. Even if their share prices continue to fall, I’m still comfortable buying unless somehow something changes, which we’ll see.

Secondly, just because you aim for 10% CAGR as a growth target doesn’t mean you’ll never achieve 15% CAGR. Think about it, a stock that has already climbed by 10% could easily climb by another 5%. The point is to actually be right rather than focusing on maximum upside, thus giving sizing and exposure a chance to work by not losing money.

Now I want to talk about why having a growth target of just 10% CAGR may be healthier than one with 15% CAGR. Firstly, I think it’s quite obvious that even a 10% CAGR target is better than having negative growth (i.e. losing money). Most investors in the stock market, if they are honest with themselves, tend to have a significantly higher growth target than the oft-stated gold standard of 15% CAGR. This leads them to take significantly more risk than is prudent, or that they are equipped to handle, given their circumstances. Having a 10% CAGR target is like putting on training wheels, or learning to walk before you run — it introduces risk discipline into the investment process until your process has matured to a level where you know how to keep your capital safe.

For instance, let’s say you’re just starting out as an investor in the stock market. With a 10% CAGR target, you’re less likely to invest in naked options or Bitcoin than if you were reaching for an overnight 2x or 3x return. Instead, you might invest in say PYPL, which has a 9x trailing PE; or LULU, which has a 10x trailing PE. While you’d be giving up attaining 2-3x gains in a short space of time, you’re also less likely to lose money by investing in these beaten-down stocks. This keeps your capital safe until your investment process matures to the point where you’re looking for risk:reward asymmetry over maximum upside.

It bears repeating that just because you’re aiming for 10% CAGR, doesn’t mean you can’t achieve 15% CAGR. As long as your call is right, there’s nothing stopping a stock which has gone up by 10% from going up by another 5%. The point is to avoid being wrong, which ends up in losing money.

Next, let’s talk about why reaching for risk:reward asymmetry should be the end-goal, rather than reaching for a fixed return in markets. When you buy a stock, you’re not investing directly in the company; you’re simply buying the stock from someone else. This person, who we shall call Mr. Market, is selling the stock to you at the market price, which is often at a probabilistic fair value. This means that the risk:reward implied in the market price tends to be fair given the future uncertainties of the business. Thus, rather than looking for a return by investing in the business per se, you should be looking for unfair mispricings in the market price where Mr. Market is selling the stock for a wrong price. This usually doesn’t happen by virtue of Mr. Market being completely wrong and having made an unforced error; but rather because the probabilities implied in the market price are factoring in completely different outcomes than what your (presumably correct) analysis has revealed. Combine this with a situation that offers downside protection (e.g. irrational depression), and you’ll come out ahead over successive transactions over the long-term.

What does this have to do with favoring a 10% CAGR target over say a 15% CAGR target? Firstly, it is simply a lot easier to find positive risk:reward opportunities yielding 10% over 15%. Even eschewing straightforward opportunities with a trailing 10% yield like PYPL, you train different mental muscles when you’re looking for 10% yield over 15% yield. As a natural matter, you simply end up taking substantially less risk when you’re only reaching for 10%, which allows you to focus on the goal of achieving an asymmetric risk:reward ratio rather than being obsessed with attaining maximum upside.

Secondly, having a 10% CAGR target helps to shift the investment focus to risk management. Think about it this way, what do you do with all that excess energy if you’re only looking to achieve 10% upside? You can now focus on reducing downside, right? This once again contributes to optimizing risk:reward asymmetry, where you achieve that not by increasing return but by reducing risk.

Thirdly, it helps to remember that investing in stock markets is a marathon, not a sprint. Sure, you get a dopamine high if you make a lot of money on a risky call, but can you repeat that success for the next stock? And the next? Over the long-term, every dollar you lose takes away from every dollar you make; and if you’re constantly reaching for maximum yield, you might just end up making less money over the long-term than if you had just lost less money.

Finally, it’s worth repeating that just because you aim to achieve 10% CAGR doesn’t mean you can’t achieve 15% CAGR. The way stock markets work, they tend to be irrationally exuberant when your call is right — so if the stock goes up by 10%, there’s nothing stopping it from going up by another 5%. This means that you might even end up achieving 15% CAGR without ever intending to! The point is to have a risk-focused mindset which puts a floor on the downside, which having a 10% CAGR mentality helps with, and which quite frankly also makes it easier to achieve a higher growth target like 15% CAGR in the real world.

I would be remiss if I didn’t echo all the quotes about adequate risk management which all the legendary value investors who have come before me have already said. So here they are in all their resplendent glory:

Not Investment Advice. Read Disclaimers.

In his recent posts, Michael Burry revealed that he was buying “value” factor stocks such as ADBE, PYPL & LULU. The big question is, why? While Burry is well-known for his deep-value plays, it’s not immediately obvious what he sees behind these names that others might be missing.

One conclusion that could be made is that he’s buying them simply for their low multiples, and hoping that the market re-rates them in the future. However, that’s something anyone could figure out, and doesn’t explain his conviction behind them. So what is the value investing framework that informs his boldness behind such stocks, beyond simply their low multiples?

Firstly, Burry operates on the principle popularized by Monish Pabrai, “Heads I win, tails I don’t lose much”. When a stock has already compressed to single or low double-digit multiples, there isn’t a lot of room for further multiple compression. In this case, he is operating from a “risk-first” framework, where he acknowledges the possibility of being wrong — or as Soros would say, “how much can I lose if I’m wrong?”

Unlike many investors, Burry doesn’t operate from a position of being correct — he actively acknowledges the possibility that he could be wrong. And if he does end up being wrong, the low multiples of his stock positions puts a floor on how much further they could nosedive downwards.

This framework is echoed by another famous value investor, Peter Lynch. Lynch is famous for holding a diversified basket of stocks, and publicly acknowledges that he is right only 6 out of 10 times on a stock pick.

If so, then the obvious corollary is to ask “how much am I risking if I’m wrong”? Rather than throw themselves headfirst into a position with the full conviction of being correct, intelligent investors like Lynch ask themselves how much they could lose if they were wrong on a position. It is this kind of caution that informs Burry’s picks on ADBE, PYPL and LULU — where he won’t lose much if he’s wrong, and where he could make multiples of his investment if he ends up being right.

This subsequently introduces a probability framework into the investment decision. When you’re also accounting for the possibility of being wrong, your investment process inevitably ends up being about determining probabilities rather than outcomes. Burry isn’t saying ADBE will definitely go up — far from it, he thinks that there’s a chance that it goes down.

The general idea is that the world is unpredictable, and that anything could happen in the macroeconomic environment to influence the stock price trajectory. When you’re agnostic to the outcome of a stock position, what ends up mattering isn’t being correct, but rather the odds of it going up or down. Subsequently, it is in a low valuation relative to intrinsic value that you can gain some control over the odds of the stock price trajectory.

To illustrate, say there’s a 6 out of 10 chance that you end up being right on the stock. Well, obviously you’d want to ensure an acceptable outcome even if the odds land on the remaining 4 out of 10 chance that you end up being wrong about the stock. This is what Soros means by “it’s not about whether you’re right or wrong that’s important; but rather how much you make when you’re right and how much you lose when you’re wrong”.

This is why valuation matters so much in Burry’s investment framework — it’s the one thing within his control as far as the odds of the stock price trajectory is concerned. By buying into low multiples, he puts a floor on how much the stock could fall further while leaving ample upside potential. Suppose he ends up being wrong on all his positions. Well, with PYPL trading at 9x PE, there’s not a lot of room for it to fall further. Contrast that to if he ends up being right on all his positions — there’s a chance that PYPL re-rates to 20x PE should the business see improvement. This puts the risk:reward ratio at a significant 1:3 or 1:4, where for every $1 he loses on a wrong position, he makes $3 or $4 on his right positions.

Thus, the investment objective isn’t to be right and bet on investment outcomes materializing with certainty, such as ADBE outperforming. Rather, it is to ensure there is a healthy risk:reward ratio on all positions — such that the aggregate portfolio adds value and is greater than the sum of its parts. The end-goal is to have a portfolio with an aggregate risk:reward exposure that is as high as possible, such that it outperforms in nearly all situations, whether to the upside or downside.

This explains why Burry has invested in ADBE, PYPL and LULU. It’s not that he thinks that he will necessarily be correct on each of his individual positions, but rather that he hopes that he won’t lose much even if he’s wrong, by virtue of their already depressed valuations. Conversely, those same depressed valuations could help provide significant uplift to the stock should they end up being correct. There’s a lot of “maybe’s” in his investment framework, rather than “surely’s”, but they combine to offer superior risk:reward asymmetry in his aggregate portfolio.

Not Investment Advice. Read Disclaimers.

To summarize, risk management in investing involves:

• Identifying all open-ended threats which cannot be eliminated;

• Approaching risk management in a probabilistic manner, not a targeted manner;

• Quantifying the possible losses in all risk scenarios materializing;

• Comparing the possible downside to the possible upside, and ensuring a sufficiently positive upside asymmetry exists.

You’ve probably heard that you need to have good risk management in investing. Amidst these trying markets, nowhere is such advice more relevant. Yet it can be confusing to identify what exactly it is you need to do to manage risk. So what actually is risk in investing?

We all know that risk isn’t volatility. This has already been explained to death, so I won’t repeat it here. Some of you may have heard that risk is the permanent loss of capital — which is true, but remains confusing. Still others might have heard that risk refers to the distribution of possibilities that your investment is exposed to.

In this article, I’ll explain what risk means in investing in layman’s terms. Hopefully, by the end of this article you’ll be able to expertly manage your investment risk exposure.

Firstly, risk refers to all open-ended threats which cannot be eliminated that your capital is exposed to. Yup, all of them. If that sounds like a gazillion things to keep track of, that’s exactly what it is. There’s no neat and tidy way to manage risk, no simple formula to boil risk down to. Buffett said that, “Risk comes from not knowing what you’re doing”, and so you need to be aware of all the macro and business risks that your shares are exposed to. Otherwise, it could lead to the permanent loss of capital.

In this article, I’m going to use FND (check out my previous article about them) to illustrate the concepts I’m describing. What are the material risks which FND faces? There’s the risk of higher interest rates from inflation. That could lead to lower Existing Home Sales, which FND’s business is sensitive to. FND also has seen lower comps from poorer turnover as sales growth declines. These are just examples of some of the risks that FND is facing which you need to be aware of as an investor.

Notice how you can’t just boil all of them down to a simple formula. The intelligent investor is privy to all the individual risks which occur, and has a mental model that keeps track of all of them in his head. That’s what risk management in investing requires.

The second dimension of risk involves the distribution of possibilities that an investment is exposed to. Think about it this way — when you’re looking back on an investment outcome that has already materialized with the benefit of hindsight, there’s no risk because the outcome has already materialized. But when you’re looking forward towards the future before an investment outcome has materialized (e.g. when making an investment decision), there is a lot of possible risk which could yet materialize. You shouldn’t be trying to pinpoint exactly what is going to happen (e.g. setting target prices) because you just don’t know. Rather, you have to consider all the possible outcomes that could happen to your investment.

Let’s illustrate this using FND again. Most sellside analysts would seek to identify exactly what would happen to FND in 12 months time, so that they can figure out its exact future share price trajectory (i.e. target price). But good risk management involves doing more than that — it involves asking yourself what are all the possible outcomes which could happen?

Could FND face greater pressure from higher inflation and therefore higher interest rates? Could FND see depressed sales from declining Existing Home Sales? Could comps take a turn for the worse due to lower housing turnover? Good risk management involves keeping track of all the possibilities in your head, and doesn’t limit itself to just trying to identify one future outcome.

Then, we come to the third dimension of risk: quantifying risk. Now that you have identified all the possible risks which could happen, you need to put a number to them. How much could FND’s share price fall by if higher interest rates materialize in the worst-case scenario?

In my view, FND’s sales and earnings have already hit rock bottom and shouldn’t worsen significantly even if interest rates should rise and Existing Home Sales fall further. What could happen is that FND faces further multiple compression, from 27x PE today to perhaps 20x PE, to reflect declining growth. They’re still going to be growing revenues by about 10%-20% (see my FND article for their fundamentals), so 20x PE sounds like a decent floor for their valuation. That puts the possible downside at about 25% (1-20/27).

See how I quantified the risk? Now you need to do that for all possible downside outcomes for all your positions in your portfolio. This is what risk management involves.

Finally, we come to the fourth dimension of risk management: comparing risk to potential returns. In other words, we need to figure out the risk:reward and see if there is enough asymmetrical upside in the position.

So what’s the upside for FND? In my view, I think it’s quite possible that FND reverts back to its historical highs of $100/share if the macro picture improves and its fundamentals return to health. That represents a nearly 100% upside relative to FND’s current share price of $51.

Thus, the risk reward ratio is 25:100, or 1:4. You can’t eliminate all risk, but you can ensure that you only touch an investment if the potential return far exceeds the potential risk. I typically aim for a 1:3 ratio in all my investments, which should result in an aggregate portfolio risk:reward asymmetry of 1:3 as well. In the best-case scenario, this means your winners triple while your losers only fall by a factor of 1x.

To summarize, risk management in investing involves:

• Identifying all open-ended threats which cannot be eliminated;

• Approaching risk management in a probabilistic manner, not a targeted manner;

• Quantifying the possible losses in all risk scenarios materializing;

• Comparing the possible downside to the possible upside, and ensuring a sufficiently positive upside asymmetry exists.

Congratulations, you’ve just understood risk management in investing! It’s not something you can boil down to a formula, but rather just a very common sense matter to manage. Happy investing!

Not Investment Advice. Read Disclaimers.

Around this time last year, a bunch of expert semiconductor analysts predicted the death of INTC, with its stock trading at <10x PE. Since then, the stock has actually gained about +70%. This shows how even a bad business can be a good stock; whereas a good business can still be a bad stock.

In value investing, we look first and foremost for stocks with low valuations relative to intrinsic value (“low”). This can be a cigar butt or a wonderful business — the point is that valuations must be “low”. Doing so allows us to have exposure to not only high returns but also low risk from already depressed valuations.

Unfortunately, efficient markets tend to be quite selfish about leaving money on the table — which is precisely why stocks with “low” valuations tend to be found in the garbage bin rather than on a silver platter. This explains why value investors tend to be contrarian and found rooting around in the garbage bin over going with the crowd — because that’s exactly where you are more likely to find gems with beaten-down valuations.

This article aims to explain my investment framework as a value investor — how I seek for opportunities that don’t just offer high returns, but that actively put a floor on risk as well. This is how value investing ultimately adds value to society — not just by offering high rewards, but low risk at the same time.

What Is Reward/Returns?

The longer I stay in markets, the more I realize that value investing is simply about being an investor. That’s it, there’s nothing special about it.

Let me explain. There’s no magic trick to being a “value investor”. It is very simply about being an investor, i.e. getting good at investing capital into businesses in public markets. When you buy a stock, you’re replacing the existing investor’s capital plus paying him a market premium. This means that you’ve effectively contributed past invested capital into the business, but at a market premium which serves as your personal entry cost. Thus your ROI is based on the earnings yield (inverse PE) that you entered the investment at.

Beyond that, you have the same business exposure as if the company was privately owned. Importantly, value investors treat returns the same way that businessmen do — we look for an appropriate yield (e.g. 15%), rather than capital market returns per se. This explains why value investors can hold stocks for the long-term and through volatility — we’re fine with short-term capital underperformance as long as the yields that we acquire the stock at is sufficient.

However, focusing on returns alone misses an entire other dimension of investing — managing risk. While many investors seek maximum returns in isolation, value investors look for not just high return opportunities but also those which offer low risk — the Holy Grail of value investing. This is where having a mature understanding of risk management comes in.

What is Risk?

There is a lot of debate about what risk actually means in investing. Some people refer to it as the “permanent loss of capital” — which is true, but also confusing. Others refer to it as “volatility” — which is partially true. Still others refer to it as the distribution of possibilities that a business is exposed to. So what is “risk”?

In my opinion, risk refers to open-ended threats to your capital which cannot be eliminated. Firstly, there’s business risk. In any business, there are bound to be open-ended risks which simply cannot be eliminated and that you are simply forced to be exposed to as a shareholder. This presents a risk of permanent loss to your invested capital, whether due to collapsing fundamentals or compressing valuations — or worse, both simultaneously.

Since these open-ended risks cannot be eliminated, they have to be managed. The investor should be aware of every one of these open-ended risks and be mindful about them (i.e. managing them). The goal is to have as low of a cumulative risk exposure as possible, be it through having a margin of safety or offsetting exposure from other positions.

Secondly, there’s capital risk or market risk. This is the open-ended risk that your capital is exposed to in public markets, which we usually refer to as macro risk. The investor also should be mindful about these open-ended risks and how it impacts the portfolio.

Another way to think about risk is change. Businesses experience change all the time, as they are not static entities — the same goes for their stocks. Investors should be aware of how change in the environment affects their businesses and their stock price trajectory, rather than assuming that the status quo will persist.

Value investors tend to be more risk-averse than return-seeking, so focusing on the downside of their stocks should take priority over seeking returns. The key is to avoid permanent capital loss no matter what.

But What About Volatility?

Let’s be clear about one thing: volatility isn’t risk, which is why I discuss risk & volatility separately. However, I think there is value-add in managing a portfolio for low volatility. What do I mean by this?

As investors in public markets, there is a widespread expectation that capital should be able to be redeemed at par, despite that not being how capital invested in businesses work. Whether you’re managing a fund or just your own capital, stock markets have developed a perverse expectation that you’re managing cash rather than equity. This explains why people lose their nerve when drawdowns occur — their “cash” has seemingly impaired, despite it simply being volatility.

This is why I describe the value-add of fund managers as having the ability to transform temporary capital into permanent capital. By managing portfolio volatility, one is able to manage the expectations of investors who expect their investments to behave like cash, and subsequently who are deathly afraid of downside volatility. (i.e. expect high Sortino ratio)

How do we manage volatility? This is where having a zero-correlation portfolio comes in. By having positions which in aggregate experience random beta exposure (e.g. open-ended macro risk), we as fund managers are free to focus on delivering alpha via undervalued fundamentals without worrying about redemptions (or just avoiding plain nerves). For reference, my portfolio had about 3/4 of positions experiencing upside and just 1/4 of positions experiencing downside at any given time, leading to limited maximum drawdowns. This allows me to sleep comfortably at night despite holding open-ended business risk.

Portfolio diversification also presents another benefit — the tolerance to hold truly beaten-down stocks through thick and thin. Where most analysts had written $INTC off last year due to the open-ended business risk that it was facing, I was able to hold it through its peaks and valleys because it was only one of 20 positions. In this way, I neutralized beta risk (semiconductor exposure) while exposing myself to fundamental upside should the business recover; all while seeing minimal downward swings in my aggregate portfolio. Do this for all your stocks and you have a value investing portfolio.

Finally, managing volatility presents the Holy Grail of portfolio management — the ability to treat your stock portfolio like cash. While excessive diversification does hurt returns, limited diversification doesn’t while still enabling cash-like portfolio liquidity. This means being able to sell a stock whenever you need the cash flow, or meeting client redemptions in an institutional setting without being forced to sell prized stocks just as they’re bottoming.

Low Risk:High Reward, Low Volatility

This is how value investors add value to society — by delivering both low risk and high reward simultaneously, or having a high risk-adjusted return. To value investors, it’s not sufficient to simply be exposed to high returns at the expense of high risk. By adding a low-risk management dimension to the portfolio decision, value investors actively seek to reduce permanent downside while simultaneously experiencing high returns (e.g. 15% CAGR) through acceptable volatility — with the bonus of enabling the stock portfolio to be treated like a cash account.

This combination of low risk, high reward and low volatility is actually not impossible to achieve — one just needs to be comfortable rooting around in the garbage bin for undervalued gems, and simply waiting for the right pitch before swinging, as Buffett puts it. In this way, value investors can expose themselves to not just high upside from stocks rerating to fair value (or the underlying business improving), but also low downside from already depressed valuations putting a floor on further drawdowns. Add a zero correlation dimension to the portfolio to manage volatility, and voila you have a cash-like stock portfolio which is scalable and can deliver regular cash flow for your personal (e.g. retirement) or business (e.g. pension fund management) needs.

This is how value investors add value. High reward + low risk + low volatility = cash-like risk-adjusted returns!

Not Investment Advice. Read Disclaimers.

Imagine having a regular income and dollar cost averaging (DCA) into the S&P500 by investing a certain amount in it every month. Now compare that to investing in the stocks researched on this newsletter in the same manner. Doing both yields identical returns, but with lower correlation and concentration risk using the latter — compared to the former, where the Mag 7 represents 33% of the S&P500.

This article is an update post of sorts which assesses how a value investing portfolio performs amidst a truly hands-off, buy & forget, long-term hold approach. We will also be providing an update on all of the stocks mentioned in the section below.

Since I started writing about US stocks, this newsletter covered the 22 stocks shown in the chart above. They form the basis of the Value Investing Substack (VIS) portfolio — by assuming that each stock was invested in on the day of publication in an equally-weighted manner (i.e. each stock represents 4.5% of the portfolio, cash held until purchase initiated, never sell).

Each stock’s individual contribution to the portfolio is thus aggregated to derive the average performance of the wider VIS portfolio. To illustrate, take INTC for example. It gained 69% since I wrote about it, hence its assumed contribution to the VIS portfolio is 3.1% (i.e. 69% x 4.5%). Adding up the 4.5% weighted gains/losses of all 22 stocks results in an average VIS portfolio performance of 38% over 3 years — or roughly 11% CAGR.

This contrasts with DCA-ing into the S&P500 over the same period, which coincidentally also yields an identical return of 38% or 11% CAGR. As aforementioned, this assumes making an investment in the S&P500 on the same dates as the stocks in the VIS portfolio (i.e. respective date of publication).

The VIS portfolio is a value investing portfolio, hence it tends to outperform during bad times and underperform during good times. Given that 2023, 2024 and 2025 were all banner years for the S&P500, I was quite pleasantly surprised that the portfolio managed to generate identical returns as DCA-ing into the S&P would have. As we shall see below, it managed to do so despite having close to zero correlation risk between stock positions and none of the concentration risk of the Mag 7.

As we can see above, 6 out of 22 stocks posted losses while most of the remaining 16 stocks are in significantly positive territory. This implies a limited maximum drawdown of the VIS portfolio throughout the period concerned, which should result in a greater Sharpe ratio.

The limited drawdowns can be largely attributable to care taken in only selecting stocks with low valuations at the outset, putting a floor below share prices collapsing. It has also resulted in acceptable drawdowns in individual positions, even with complete fundamental duds like PYPL (-22%). The one “growth” stock in the portfolio, FND, posted the greatest drawdown (-46%).

Amidst peak valuations in a more uncertain 2026 and beyond, this proactive downside protection provided by the decision to invest only in low valuations should result in greater ex-ante performance, even if negative market environments should materialize — thus demonstrating superior portfolio risk:reward.

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Individual Stock Performance Review

This section will go through each of the 22 stocks’ performance since the time of their investment — to provide more color on the risk:reward underlying each position, which should inform the risk:reward of the aggregate VIS portfolio. It also reveals the sectors involved, which demonstrates how the portfolio has nearly zero correlation between positions.

OXY (O&G, -15%): The CrownRock acquisition and the sale of OxyChem do not significantly change the big picture. OXY remains the same reliable cash flow producing asset with roughly 10% yields at current prices that it was when Buffett first started acquiring its ordinary shares.

CDPR (Gaming, +148%): The stock was pummeled at the time of writing by the bad news surrounding Cyberpunk 2077, but has re-rated due to the disappearance of said bad news and expectations normalizing over the company’s robust IP library. Valuations have gone from worried to slightly excessive as they now fully price in the expected sales of future titles. (e.g. Witcher 4 in 2027)

EWBC (Banking, +100%): Li Lu had just invested in the stock at the time of writing, and once the CRE-banking scare passed investors realized that EWBC’s portfolio had little office exposure. The China tariff scare also passed, putting EWBC in a strong position as its customers moved manufacturing to Southeast Asia and Mexico. EWBC’s fortress balance sheet benefitted as customers switched to their deposits from weaker banks after the Silicon Valley Bank debacle.

COF (Banking, +61%): Buffett had invested in the stock at the time of writing, and the bank has benefitted from the Discover acquisition by not paying interchange fees to Visa/Mastercard anymore. A stronger credit card consumer and lower interest rates also contributed to both NII expanding and deposit costs reducing.

PYPL (Financial, -22%): Operationally speaking, Paypal has pretty much failed to meet all turnaround expectations set by the new CEO at the time of writing. The latter has since resigned, and the incoming new CEO is exploring breaking up the company and selling its still-valuable assets.

GRAB (Tech, +21%): Grab continues to face fierce competition in its Southeast Asian markets, with Tiktok’s acquisition of GoTo in 2024 putting a dent in Grab’s GMV. Grab announced its first full year Adjusted EBITDA profit amidst lower incentives and promotions, and their $500m share buyback program seems to be putting a floor beneath the stock price.

UBER (Tech, +66%): Uber benefitted from being included in the S&P in early 2024 and saw growth in its mature markets of the US and the UK. The high-margin Advertising and Uber One segments continued to demonstrate growth, and Uber solved its AV problem by becoming the distribution layer for everyone else (Waymo, Aurora).

INTC (Semiconductors, +69%): Intel saw increased optimism from the entrance of a new CEO who prioritized “immediate profitability”, and from Nvidia’s investment to produce x86 chiplets for its AI and PC-grade RTX products. IFS also saw support with new investments from Softbank and rumors that Apple might use IFS for some of its high-volume chip fabrication.

DIS (Media, +6%): Disney’s Parks & Experience saw flat attendance amidst strong pricing power as DIS hiked unit prices but without seeing increased guest volume. The incoming CEO, Josh D’Amaro, is said to be a P&E guy. Disney+ reported its first profit in 2025, but Streaming profits were more than offset by continued cord cutting at Linear TV.

DG (Retail, +8%): DG’s new CEO’s successful implementation of its “Back-to-Basics” turnaround program saw an increased labor pool and SKU rationalization, which improved in-stock levels at stores. Shrink mitigation and inventory control also contributed to working capital improvements, while stores saw trade-in from a higher income consumer segment amidst high inflation and the validation of its fresh produce sales.

Hibbett (Retail, + 28%): This small-cap was first brought to my attention by John Hempton of Bronte Capital for its unique customer base, which you can read more about in my original article. The company has since been acquired by JD Sports and is no longer publicly traded.

FND (Retail, -46%): The flooring specialty retailer saw decreasing ticket and negative comps owing to persistent pressure on declining Existing Home Sales (EHS). Consensus also built-in lower growth expectations after management reduced new store openings from 30 to 20 stores in 2026. Valuations are a double-edged sword depending on which way you swing on EHS.

SE (E-commerce, +65%): SE’s valuation pulled back recently after missing guidance on Adjusted EBITDA, but has gained significantly since the time of writing on improved fundamentals at Shopee. E-commerce in Southeast Asia is maturing and take rates are improving as competitors slow on price & promotion wars. Free Fire saw a huge resurgence in Latin America and India, hitting its highest user count in 3 years.

TSLA (Auto, +171%): At the time of writing, TSLA was facing headwinds in the form of potential auto tariffs by the US & EU on cars manufactured in China. The stock continued to outperform as the Trump election win created expectations on federal AV standards, while its Energy segment surprised in 2025 by contributing to 10% of group revenues. The Auto segment saw slightly depressed performance amidst its first YoY sales decline in early 2025, as Europe and China sales face pressure from increasing EV competition.

SIRI (Media, -21%): SiriusXM reported its first negative growth of self-pay subscribers in 2025, as Gen Z and millennials increasingly turn to Spotify and other streaming platforms. Pandora also continues to bleed with plummeting ad revenue and user count. Berkshire continues to acquire its shares.

VLRS (Airline, +11%): Volaris saw increased CASM in 2025 from their partially grounded fleet due to the ongoing GTF engine inspection program. A strong dollar put pressure on operational costs while base fairs saw pressure amidst rising competition. Markets still have not priced in the Volaris-Viva merger announced in late-2025 as regulatory scrutiny increases over the creation of a near-monopoly.

SHOP (E-commerce, +111%): Shopify continued to post strong GMV growth amidst AI-directed sales funnels, improved B2B listings and sales acceleration in Europe. ShopPay also reported stronger penetration on the platform, while Shopify Capital continued to post gains.

BABA (E-commerce, +29%): Alibaba saw improved consensus expectations on its AI-first strategy, which saw the cloud revenue segment grow its margins. Taobao/Tmall also stabilized in 2025 after years of losing share to PDD.

CELH (Retail, +42%): The Alani Nu and Rockstar acquisitions supercharged revenue growth, turning CELH into an energy drink pure-play arm of Pepsi with 20% market share of the energy drink market. The introduction of Alani Nu into PepsiCo’s DSD network also improved margins at the brand, as Celsius continued to push into international markets.

DBX (Cloud, -9%): Dropbox fell recently amidst the SaaSpocalypse, but actually had a strong showing in 2025 amidst the launch of a new AI assistant (Dash) that increased ARPU and reduced user churn. The share price also benefitted from an aggressive $1.5B share buyback program.

CNH (Ag Equipment, -10%): Agriculture commodity prices continued to face pressure through 2025, resulting in CNH having to cut prices to clear an inventory glut at dealer lots. Early 2026 saw a recovery in the inventory overhang, with management also reporting that the earlier cost-cutting program initiated in 2024 was beginning to bear fruit.

AGCO (Ag Equipment, +24%): AGCO’s differentiated “retrofit” business model benefitted as high interest rates made tractor purchases prohibitively expensive to farmers experiencing an industry downcycle. The company’s premium Fendt brand was also less susceptible to inventory gluts and avoided fire sales that competitors had to enact.

As you can see, the VIS portfolio has very little correlation between its stocks and should outperform the S&P500 if 2026 happens to be a down year, as peak US valuations strongly suggest. The lack of Mag 7 concentration risk should also reduce maximum drawdown, leading to a greater Sharpe ratio as investors navigate an increasingly uncertain market.

Something Buffett is well known for is his description of “Tap Dancing To Work”. In fact, there’s even a book named after it.

Perhaps you want to become a portfolio manager one day. This article will help you understand what it takes to win in markets. And why passion tends to be one of the first things employers look for in candidates in this field.

You’ve probably heard that passion is important to win in markets. But what does that even mean? What makes it so crucial for developing sustainable alpha? And how can an emotion from the heart be correlated with a logical investment outcome? This isn’t romance!

This article will spell out with detailed examples what it takes to become a proficient portfolio manager. By the end of this article, it will explain why not falling in love with markets is unlikely to lead to consistent outperformance in markets — value investing or not.

TABLE OF CONTENTS: 

1. Why Passion Is Important In Valuation

2. Why Passion Is Important In Business & Sector Analysis

3. Why Passion Is Important In Financial Statement & Accounting Analysis

4. Why Passion Is Important In Macro & Portfolio Management

5. What Tap Dancing To Work Really Means

Why Passion Is Important In Valuation

The first thing you’ll need to analyze stocks well is a good grasp of valuation. Typically, this involves understanding the basics of valuation, which usually means the DCF model. To oversimplify, the DCF model attempts to forecast the future FCF of a business and discounts those cash flows by an appropriate discount rate in order to derive the company’s fair value.

To digress, I don’t think most investment practitioners intend for the DCF to be used this way. While in principle the concept of enterprise value being the sum of its discounted future cash flows is true, it remains an extremely clumsy tool when trying simplify it down to a neat model. Almost anyone will tell you that the use of terminal value to represent business cash flows into perpetuity is unrealistic and unreliable. This is why you tend to hear investors discussing valuation on Bloomberg or CNBC in terms of multiples, rather than in terms of the discount rate they’re thinking of (I almost never hear this) — which is actually a more accurate barometer of uncertainty, rather than cost of capital per se.

In any case, the DCF model is still the current valuation standard and part of institutional inertia, so for now we’re still stuck with it. The biggest gripe you often hear when using the DCF model lies in the use of WACC — just changing the discount rate by 1% throws off the entire terminal value estimate so as to render the entire valuation worthless. Value investors will also criticize the use of beta in the WACC calculation to represent cost of capital — it’s a top-down methodology which assumes a static yield spread between a business’s cost of equity capital and borrowing costs, in stark contrast to the bottom-up methodology of how most businessmen think about shareholder return (i.e. profit dilution vs. uncertainty).

If so, how can we improve on it? If you start digging into the components of WACC, you’ll realize that it seeks to represent the cost of equity as a function of a regression analysis of its historical stock price. The general idea in statistics is that volatility equals risk, since it represents points in history where stock prices have deviated from the long-term mean trendline, thus introducing noise into further extrapolation of stock prices.

If you really think about it, the cost of equity formula is just y=mx+c. The fulcrum of this formula lies in ‘mx’ — where ‘x’ represents excess business returns over market returns, while ‘m’ represents the slope for extrapolating future excess returns from its historical trend.

I’m sure you can see where the problem with this assumption lies. Firstly, the world is chaotically non-deterministic and business returns do not behave nicely the way statistics does, so you can’t extrapolate future business returns from historical business returns in a straight-line manner. Even if you could, stock price trajectory on public markets add another dimension of chaos to the equation.

However, that doesn’t mean that the WACC formula is useless — one simply needs to know where its weaknesses lie, and make the appropriate adjustments for them. It’s like going to plane school and getting your 50-100 hours of pilot training under your belt, so that you know which switch to flip when the plane starts rocking side-to-side. This allow you to course correct for the imperfections within the WACC formula so that they more accurately resemble the real-life business conditions of a given circumstance.

…still with me? The point I’m trying to make is that one needs to be interested enough in markets to actually learn how to tear apart the engine of valuation and put it back together with parts leftover. This is before we even get into a discussion of efficient markets, whichthe DCF model is predicated on.

Why Passion Is Important In Business & Sector Analysis

Apart from valuation, a good fund manager usually also needs to have a deep appreciation for how different businesses and industries work. In this way, he can make the same course corrections in the valuation models as aforementioned for real-life business conditions, which is important since every business and industry operates differently. This is why you can’t apply a rule-based approach to valuation — a 10x multiple means something very different in an underperforming FMCG conglomerate vs. a risky venture-stage quantum computing business.

Rather than explain it, it’s easier to illustrate how having a good grasp of business models is key to understanding the different shades of grey when it comes to valuation. For instance, let’s start with valuing banks. While it’s conceptually true that bank valuations are a function of ROE x BV, their valuations (and worse, capital price trajectory) are based on so much more than that. Regional banks operate on different rules than money center banks, since the former tends to only be exposed to its local business environment. Measuring the risk exposure of money center banks requires understanding the Risk-Weighted Capital Ratio (RWCR), e.g. how the composition of risk-free assets to risky assets affects balance sheet health. Understanding the evolution of banking business models following the 2008 subprime crisis — from primarily spread-based lending to fee-based products — will lend color to why most large banks sport a Tier-1 Equity ratio higher than 10%1; and inform why management incentives are have changed since then. Moreover, understanding the intricacies of central banking with the financial sector is crucial to developing a matured understanding of bank valuations, since many generate tons of trading income while serving as quasi-government intermediaries in an economic regime flush with liquidity.

Then we get to European banks. Oh boy. Let’s move on to the O&G sector instead. Why does Buffett favor OXY so much?

First, it’s important to draw a distinction between deepwater drilling and shale (plus everything in between) — not only are their financial models starkly different, their operating models are nigh incomparable. Just focusing on the shale sector, one needs a good grasp of the history of the industry from the mid-00’s to today — how Oil Boom 2.0 emerged from the revolution of horizontal fracking, founding a race to the bottom amidst excess capacity and the subsequent fiscal discipline of the sector. After understanding how the shale winter of 2014 forced sector developments that dramatically improved unit costs, one should appreciate the uniqueness of the Permian Basin in the context of oil drilling and OXY’s position in it. Now you can start to look into the special capital structure of the Berkshire preferreds and why they resemble a fixed-yield investment for Buffett.

Since it’s topical, let’s try understanding the AI sector next. Firstly, it’s important to gain an understanding of how LLMs work — the conceptual basis of the pre-trained generative transformer and how these bad boys infer semantic meaning by comparing adjacent distances in vector space. At the base level, all of the flagship LLMs are largely commoditized in that they are pre-trained on the same data (i.e. all historical human knowledge) with relatively small model differences. This translates into relatively low differentiation between them from a commercial standpoint.

However, 2025 is poised to be the year of AI as each flagship provider is actively focusing on developing their respective application layers or “useful AI” in different directions. OpenAI has graduated from simply aiming for performance leadership to innovative applications of inference-time scaling with the reveal of o3 and OpenAI’s Deep Research. Users of Claude AI will recognize that it’s somewhat of a frontier model in the space, and has a current focus of integrating with the local environment (MCP and artifacts). Perplexity has been recognized by Jensen Huang as having revolutionized AI-powered search; while Gemini is leaning into its huge hardware lead in TPUs by enabling paid competitor solutions for their free users and sourcing inexpensively from the wisdom of the crowds using AI Studio. Also, who can forget open-source — with Meta’s Llama quickly becoming one of the top-used local LLMs, while Deepseek has leapfrogged the competition via its innovative use of pure reinforcement learning. Qwen is also making strides as evidenced by Apple’s recent decision to partner with Alibaba for AI, while the “indie” space is littered with a plethora of highly distilled reasoning models that can run on mid-tier consumer hardware.

Each of the flagship AI models are innovating in different business trajectories, demonstrating how there is ample pie in the sector for all of the flagship models to share. It also shows how the economics of the AI sector will evolve away from simply taking performance leadership towards designing valuable human-AI interfaces, and that 2025 will likely be the first year where we see laymen truly grasp the integration capabilities of AI beyond simply being a Star Trek tricorder. Investors in the sector will subsequently need to understand how these different business trajectories differ from the fundamental generative transformer abilities that AI was first known for, and how they will likely be integrated in their various specialist domains.

These aren’t the only complicated sectors that a generalist will have to understand— there’s also insurance, media, semiconductors, auto, petrochemicals, commodities, etc. It gets even more complex when there are overlaps between sectors, such as fintech being banking plus technology. As any sector specialist will tell you, I don’t think it’s possible to shortcut gaining a good understanding of each of these sectors — one really needs to just give it time and slowly accumulate knowledge in each of them. And unless you’re Mike Ross from Suits with a photographic memory, that requires having an interest in understanding these sectors, since you’re unlikely to see a dime of sustainable profit from such investments until you do.

Why Passion Is Important In Financial Statement & Accounting Analysis

Remember how we saw earlier that a business’s value is based on their discounted cash flows? Well that’s what financial statement analysis seeks to uncover — following the cash flows of the business.

To do that, one needs to be able to reverse engineer the numbers from a business’s financial statements — which is basically the opposite of creating the numbers from real-world conditions. For instance, the ROUA balance of an airline should tell you what their airline lease conditions are; so too should the SBC activity of a gaming company about their remuneration practices. The goal of reverse-engineering business numbers is to give you a map of real-world conditions, not to simply serve as financial inputs of a valuation model.

To do so, one needs to understand GAAP/IFRS accounting standards and their rules for translating real-world objects into standardized numbers. To illustrate the importance of this, consider how the accounting rules for leases were adjusted during the pandemic. The normal accounting treatment for leases (e.g. warehouses, airplanes, etc) is to derecognize and re-recognize a lease if any changes were made to the original lease terms. However, this practice was obviously counterproductive during the pandemic, when everyone was universally extending their lease tenures. Hence, a temporary exemption on lease reclassification was allowed by the accounting standards bodies to avoid gigantic and unnecessary mark-to-market accounting losses being recognized during already trying times. Understanding the effects of these gave investors and analysts more certainty when reconciling their cash flow impacts.

When investing in value factor stocks with single-digit multiples, I find having a good grasp of accounting standards to be invaluable when sifting through the garbage can for gems. When trying to tell the difference between a mispriced asset and a real dud, it makes a huge difference between being able to see the business assets at play and their respective cash flows, or not. This is in stark contrast to growth stocks, where asset value is typically quite visibly on display. While I can’t speak for everyone, my personal experience with these quasi-cigar butt type stocks has been that the mispriced value is usually hidden just beneath the surface — and that understanding accounting standards makes the difference between seeing past their short-term tragedies to the long-term asset values lying underneath. A great example of this is when I inferred from SE’s gross margin performance that they hadn’t been abusing free shipping vouchers by shifting delivery fees from COGS to S&M expenses (below the GM line) — that alone gave me the confidence to feel optimistic about their trajectory, since that was by far their largest cash burn component.

It usually takes years to accumulate the broad array of knowledge about accounting standards in order to be able to follow a business’s cash flows at granular detail. Being able to do so can mean the difference between having diamond hands when holding a deep value stock and losing your nerve amidst short-term volatility — and being interested enough to actually put in the time to learn about accounting standards requires one to be passionate enough about them to try and understand them.

Why Passion Is Important In Macro & Portfolio Management

Everything we’ve discussed up to now is arguably the easy part. The hard part about forecasting share price trajectory actually starts here — gaining a deep understanding of macro factors and how they impact markets.

As I’ve discussed at length before, this isn’t our grandparents’ markets anymore, where market prices are solely dictated by the Invisible Hand. We live in an economic regime where central bank interference in markets is not only tolerated, but expected — and boy does that impact stock prices. The recent inflationary scares over the past few years were in no uncertain terms contributed by excess Fed liquidity and TGA involvement (which significantly affects bank performance btw); whereas the inverse correlation between 10-year yields and policy rates can be explained by dynamics in real estate refinancing markets. The unravelling of the yen carry trade last year also had a significant impact on stock prices, while having a deep understanding of the contributing factors behind the strong dollar and the respective liquidity facilities at play would have most certainly calmed some market jitters.

Anticipating forex movements also requires having a good grasp over trade balances and geopolitics, while understanding the components of GDP can help investors see through the noise of scary headlines. This is before we get into truly advanced territory over topics like repo plumbing, central bank swaps or derivative impact on passive fund flows, which are the nightmare equivalent of learning in financial markets.

Then we come to implementation. Anticipating the portfolio impact of short-term share price trajectory is an exercise in managing portfolio beta, which requires having an understanding of the correlation of respective sectors and the beta factors at play within each position. The aforementioned central bank actions will also inform how stock prices fluctuate, and these need to be carefully monitored alongside other macro factors (like forex or trade) in order to be correctly implemented as portfolio management. It is also crucial to have at least some sense of how extraneous factors such as options activity and investor expectations impact share prices; and what kinds of black swan events can turn the tables on your portfolio correlations.

As one can imagine, getting a good grasp over these matters is not something which can be done overnight — it takes months just to understand all the financial levers on inflation, and years to understand everything else (that matters). Persevering through the time required to learn these lessons usually requires having a passion in markets.

What Tap Dancing To Work Really Means

This explains why employers tend to look for passion as a key ingredient in their candidates — it takes a long time to acquire these research skills, and someone who finds it boring is probably gonna tap out early. To be fair, there are most certainly easier ways to make money than spending years with your nose in a book — but it doesn’t change the fact that this is what’s necessary for sustainable alpha generation in markets.

As Druckenmiller alluded to above, there are just way too many people in markets who do it for the love of the game to make doing it purely for money tolerable. It’s a bit like soccer — if you’re not doing it because you enjoy it, you’re just not going to make the necessary investments to secure the skills required to consistently generate alpha. This leads to the natural human impulse to take shortcuts — which leads to all kinds of disasters in stock markets.

On top of that, the recent introduction of AI is going to dramatically switch up existing investment methodologies and cause everyone to stand on tiptoes. I can say without a shadow of a doubt that if you don’t start learning how to incorporate AI into your investment process, you are going to be overtaken by someone fresh out of college in 5 years time (outside of manager roles). The introduction of AI represents such a dramatic sea change to the equity research community so as to render many existing processes obsolete — and just like all of the aforementioned items, it takes quite a bit of time to learn how to effectively use it.

This hopefully provides a clear illustration of why passion is an indispensable element in the sustainable generation of market alpha. So is fund management for you?

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

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Value Investing & Buffett

1. How I Became 100% Convinced that Value Investing Was The Superior Investing Methodology

2. Was John Maynard Keynes A Value Investor?

3. Unpopular Opinion: Diversified Portfolio > Concentrated Portfolio

4. 2nd-Level Thinking: Exploiting Inefficient Share PRICES (Supply vs Demand)

5. Why Buffett BOUGHT Apple

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Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Value investing isn’t just about cheap multiples per se (i.e. cigar butts). It’s about price vs. value (i.e. what you pay vs. what you get), and how much your risk:reward exposure is. To boil it down to one word, it’s about asymmetry.

And who better to represent asymmetry in markets than George Soros — who infamously took down the Bank of England on Black Wednesday. His lieutenant at the time, Stan Druckenmiller, recently gave a sterling interview (pun intended) full of incredible lessons for professional value investors.

Not Investment Advice. Read Disclaimers.

Almost Didn’t “Never Had A Down Year” (43:05)

Druckenmiller is well-known for not having a down year throughout his entire 30-year career — but this was almost not the case. By his own admission, he apparently missed the peak of the dotcom bubble by an hour. This resulted in the Quantum Fund zeroing out all its gains within a week of the bubble bursting — and was down -17% by the time he liquidated all his tech positions.

Fortunately, his astute purchase of Treasuries towards the end of the year resulted in a quick +40% gain, which brought the fund back into the black. We’ll discuss his insights behind this trade below.

50% Dollar, 25% Oil, 25% Interest Rates = S&P Earnings Trajectory (46:50)

This part of the interview was particularly intriguing to me. Druckenmiller claims that a regression analysis by the renowned Ed Hyman composed of 50% dollar, 25% oil and 25% interest rates signaled the future trajectory of corporate earnings.

Those of you wondering what the correlation between the three might be should find this Reddit thread enlightening. User longshortequities described it as, “Inflation from oil price increases leads to higher rates leads to higher dollar, which is unappealing for the markets”.

In any case, it was this insight which led Druckenmiller to put on his aforementioned record-saving trade, thus allowing him to hold onto his throne of never having a down year.

Fed Has Declared Victory Too Early on Inflation (2:50)

There’s a pretty telling chart that’s been floating around recently — I’ll just leave it below and let you do the interpretation in conjunction with Druckenmiller’s quotes above:

Powell is Obsessed with Soft Landing (4:19)

AI Won’t Replace Human Fund Managers (39:57)

This is a sentiment I share. I find it difficult to imagine a financial layman having the ability to input adequate AI prompts — the need to comprehend so many different possibilities and the iterative feedback loop of output A serving as input B implies that you can’t reduce market analysis to a single all-inclusive prompt. Perhaps chain-of-thought reasoning can change that; but I highly doubt it, since there’s also a subjective behavioral economics aspect embedded in market prices.

However as Druckenmiller put it, I can see professional fund managers quintupling their output if they “sharpened the saw” by introducing AI methodologies into their existing financial workflow.

Don’t Get Into Markets Unless You’re Passionate About It (50:00)

I find myself agreeing with Druckenmiller’s quote. Markets move at a faster pace than the Tech sector — sands are consistently shifting at lightspeed, and if you snooze you lose. Peter Lynch has famously admitted to being a workaholic:

I haven’t gone to a football game in four years. I haven’t gone to a hockey game in six years. I haven’t gone to a Celtics game in five years. I think I read one book in one year. I don’t even read the newspaper.

I’ve worked every Saturday for seven or eight years — I mean seven in the morning. In the last six months I’ve started working some Sunday mornings at home. Three weeks in a row I worked 82 hours. — Peter Lynch

If you don’t enjoy it, you’re going to be looking for ways to optimize your workflow. Unfortunately that’s not how markets works — you genuinely need to consume information from the furthest reaches of the Internet in order to stay competitive. There are far easier ways to make more money than compounding capital by 15% in a risk-free manner.

Analyst Skillset ≠ Portfolio Manager Skillset (51:04)

Analyzing businesses exercises a different muscle in the brain as compared to managing portfolios — the former is quite left-brained, while the latter requires creative mental gymnastics. Businesses tend to operate according to a fixed set of rules, whereas markets move in ways that defy the imagination.

Understanding macro also requires an understanding of fiscal (Treasury) and monetary (Fed) policy; which in turn requires having a handle on economics. I’m just glad that PMs only have to manage market exposure — there’s an entire world foreign to even us at the central bank level (e.g. repo plumbing, CB swaps).

If you’re interested in entering this business, Druckenmiller is right in that it pays to figure out early whether you should specialize in stocks or managing portfolios. They’re both intellectually stimulating in different ways — unless you have the appetite for both.

“How Much” > “Win vs. Lose” (37:44)

In many disciplines, success is characterized as having a one-track mind to the goal (e.g. business, sales, etc.) In markets however, the excessive number of factors affecting prices requires investors to hold dozens of different considerations in their head and balance all of them against each other simultaneously. This renders the “one-track-mind to the goal” approach ineffectual; investors must consider all possibilities or risk getting sideswiped by a train.

Given the outsized number of possibilities involved in any given trade, the “target price” approach of forecasting precise market outcomes becomes less relevant. To minimize the mental overhead of predicting the impossible, the investor focuses on what he can control — by estimating exposure to both the upside and downside, with respect to both volatility and risk. This makes fund management a question of controlling for “how much” rather than “win or lose”.

The ideal scenario is one of risk:reward asymmetry — where regardless of the actual outcome, one either makes a lot or loses very little. This is encapsulated in Monish Pabrai’s quote, “Heads I win, tails I don’t lose much”. In Druckenmiller’s case, their bet against the pound involved either a 200% potential gain or an 8% potential loss. This was because markets were so sure at the time that the Bundesbank would do whatever it takes to keep the UK in the ERM.

Unfortunately, this was not to be so. Germany had just reunified a couple years ago, and West Germany’s rapid investment to rehabilitate East Germany’s industrial sector led to an economic boom. This led to the Bundesbank raising German rates to keep inflation under control — amidst a policy environment which as Druckemiller put it, was still carrying the scars of hyperinflation from the Weimar era.

The Deutschemark’s appreciation pulled up the entire basket of ERM currencies, requiring neighboring member countries to raise rates to stay within ERM guidelines — something the UK’s receding economy at the time could ill afford. Amidst the Italian lira’s recent 7% devaluation, Bundesbank’s President Helmut Schlesinger got the snowball rolling when he mentioned in an interview that “there would have to be a more comprehensive realignment of currencies in Europe”. This was taken by Druckenmiller to mean that the UK would have to exit the ERM — and the rest is history.

While Druckenmiller admits in the interview that they didn’t get a chance to fully implement their bet before markets caught on, it still demonstrates their tactical adherence to asymmetrical bets rather than precise outcomes. They did not have to win if losing only involved a maximum loss of 8%, while winning would yield a 200% return and write them into the history books.

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

By now, most of us will be wholly familiar with Buffett’s obsession with brands. Given their supernatural pricing power, it’s little surprise that many value investors gravitate towards strong brands to invest in.

However, for the longest while I wasn’t able to put my finger on what made brands special. Brands lead to pricing power, yes — but why? What was their secret sauce? I had analyzed countless branded businesses over the course of my career — yet the exact rules of what made brands special escaped me.

For instance, when we say that Apple has a strong brand, which cross-section of its branding are we referring to? Is it their name? Is it what the name implies, its attributes? The Apple brand stands for human design in consumer tech — but why does that give its business pricing power? Wouldn’t the flagship phones and laptops of Google, Microsoft or even Huawei today qualify that same description? If so, why don’t they share the same pricing power?

This exercise gets even more confusing when you bring in other brands. What about McDonald’s, what are its attributes? Starbucks? Porsche? Fastenal? Delta? Microsoft? Facebook? Chipotle? Heinz? Disney? Alibaba? Paypal? Intel? These are all household brands, yet they stand for radically different things.

So what is the common thread by which we describe them in equal measure, as brands? What is their shared element, their spark, which gives strong brands their pricing power or competitive edge? More importantly, what does the roadmap for building a successful new brand from scratch look like?

Attempting to understand what makes brands tick has been an exercise in frustration for me for the longest time. In the first place, what even is a brand? Is it equivalent to a flag? Okay, so how does a flag give a business pricing power? The CEO of LVMH, whose business depends entirely on branding, once described brands as the attributes of their business. Other platitudes include star brands “speaking to the ages” or being “timeless, modern, fast growing, and highly profitable”. That’s cool, but it doesn’t really help investors understand what makes a strong brand.

When attempting to understand what makes something tick, we usually start by understanding what their rules are. For instance, the margin bottleneck of an e-commerce business is its logistics backend, since that’s where increasing operating leverage delivers the greatest impact. A semiconductor foundry may be operationally complex, but its business model boils down to CAPEX and successful execution. Efficiency in tech companies is often expressed as revenue per employee, given how their cost base revolves around remuneration. Bank returns are always constrained by ROIC, while E&P returns are typically a function of unit costs. By understanding the rules of the game, one can figure out where the bottlenecks lie and plan four steps ahead.

However, trying to dissect the Rules behind Brands has often lead to headaches for me — a feeling which I’m sure many are familiar with. As the aforementioned Apple example demonstrated, their ethereal nature makes it difficult to put your finger on what their success factors are — specifically what gives them pricing power.

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It’s About The Consumer, Stupid

Naturally, one would start looking for the success factors of something within the thing itself. For instance, I might determine that the attributes of the Apple brand were what helped develop its loyal fanbase, which subsequently developed into pricing power. Thus, I’d take design cues from Apple products and transplant them to say, McDonald’s — for instance, by showing care in packaging design. However, doing so clearly doesn’t yield the same pricing power — which implies that business attributes aren’t what makes good brands.

As time went on, it occurred to me that the source of a brand’s power actually lies outside the business — in the minds of consumers. As Don Draper would say, you buy a Coke before you’ve even set foot in a store. That’s because Coca-Cola has developed such an entrenched position in the psyche of our collective consciousness that we don’t think twice about alternatives when we want a cool, refreshing soda. It’s also why soda ads always have this sound:

This implies that brands are not something which lie with the business — such as an “attribute”, “identity” or even a “reputation”. Rather, it’s a “mental asset” which lies outside the business — with the consumer. I would even go so far as to say that the brand asset is wholly separate and unrelated to the business.

Think about how ads of large businesses position themselves. Do they revolve around their products? No, they revolve around the consumer — the product is simply something that fits into the centricity of their lives. Brand-building speaks of value not from the role of the consumer, but from the perspective of the individual. Take a look at some of the ads below to see what I mean:

This has some interesting implications. If a brand is owned by the consumer rather than the business — and the brand-building exercise is centered around the consumer, rather than the business — then it stands to reason that the brand asset is actually part of the consumer, not part of the business.

Think of how Coca-Cola ads rarely talk about the cost per can, or even how great their trademark syrup tastes — they’re all about time spent with family and friends, or joy amidst festive seasons. Red Bull ads aren’t about giving you 24/7 energy to power through the day; they’re about life’s meaning found in extreme sports. Mercedes ads aren’t about superior German engineering, they’re about quiet luxury. What do any of them have anything to do with the product?

This doesn’t mean that brands do not communicate their business attributes — they merely do so only when it pertains to the consumer. Apple’s early ads distinguished themselves by not talking about megahertz & gigaflops like their competitors did — they were all about how Macs fit into your daily routine. Consider this: if brands were about their businesses, why would celebrity appearances help in brand-building? It’s not like anyone believes Ryan Gosling’s endorsement makes the beer taste better — but he does matter to the consumer.

Nor are brands simply about storytelling or invoking emotion per se. You’ve probably seen an ad that just goes for shock value and found it cheap. Good brand messaging comes from a very practical place — the only difference is that it revolves around the consumer, not the business. Emotion is merely the symptom of superior branding rather than their source, because the consumer is ultimately an emotional creature.

The long and short of this is to say that the element of good brands are NOT ABOUT THE BUSINESS. Good brands revolve wholly and exclusively around the consumer, with the products simply being a part of their lives. Understanding this makes all the difference in product positioning, especially given the prevailing misconception that businesses own their brands. Nothing could be further from the truth — the customer owns your brand.

The Rules for Brand-Building

Let’s test this theory by appling my rules for branding to this newsletter, Value Investing for Sophisticated Investors. Then we’ll contrast two approaches to brand-building — one where it revolves around the product, and one where it revolves around the consumer; and compare their different degrees of pricing power.

Those of you who have known this newsletter for the past 4 years will be familiar with all my past articles about value investing. These basically amount to the product of this newsletter — they unpack its investment principles according to Buffett and Graham, and demonstrate its relevance and application to modern-day stock markets.

However, someone who doesn’t actually care about value investing will probably find such a product boring. More than not recognizing you as a target customer, this newsletter has no relevance to you as an individual. It doesn’t recognize Harry who secretly yearns to be a musician; Sally who wants a better life for her kids than her mom gave her; Beatrice who wants to feel pretty; or John who wants to gain respect from his peers. How does value investing fit into any of their individual lives whatsoever?

Proper brand-building approaches product positioning by revolving it around the consumer, rather than the business. If I had to make an ad for this newsletter, this is how I would go about it. To Harry, value investing is the soul of stock markets, the harmony around which stock markets dance around. To Sally, value investing delivers a reliable way to generate safe 15% risk-free returns, which she can use to secure her kids’ higher education once they’re all grown up. To Beatrice, value investing represents beauty — if you can’t impress people with your looks, dazzle them with your intelligence instead. To John, value investing is the path to a prestigious job in high finance, where he can one day become a billionaire like Buffett.

Notice how by revolving the presentation of value investing around the individual, we’ve managed to tap into the potential of greater pricing power with a general audience? Good brand messaging isn’t just about using cheap tricks to tug at heartstrings — it’s about responding to the inalienable fact that we are all human, and not just human but individuals unique from each other.

Philosophically speaking, brand-building is fundamentally about self-actualization — the highest layer of Maslow’s hierarchy of needs. In a society which reduces us to faceless organization and roles, we’ve forgotten along the way that we are in fact human. Humans who do not simply represent surgical roles & responsibilities amidst a greater society, but who can individually live, love, laugh. Human.

More than that, good brand messaging celebrates the individual. You’re not just the product manager, soccer mom — or god forbid, the consumer. You’re Harry, Sally, Beatrice or John. Product value isn’t measured in terms of dollars and cents; it’s determined by how much it helps the human being self-actualize as an individual. In the weirdest way, good corporate brand positioning reminds us of our soul.

Notice how none of this description involves the business whatsoever? This is to say that the inherent value of brands are the furthest thing possible from business — they actually revolve around the human individual. Hence, good product positioning isn’t about communicating consumption; it’s about how the product fits into that part of that particular individual’s life. Not only is your business not the main character of your brand, it should barely register at all. Brands should be all about them.

Source of Pricing Power

By unpacking the Brand asset in this way, it becomes easy to see where brands get their pricing power from. The rare element of Brands, the spark which they all share regardless of corporation, is that they represent the human individual. They do not simply recognize the consumer role — they recognize Harry, Sally, Beatrice and John.

In this way, good brands become far more than just their products. They embody the human spark within the individuals themselves, and represent their ability to self-actualize. In this way, brands command far more value than simply the merits of their products — they represent the facets of the human spirit, noble characteristics like tenacity, generosity, intelligence and love. And because of that, good brands can command superior pricing power. They’re basically a wholly separate product.

The tagline of McDonald’s isn’t “reliable burgers for a great price”, but “I’m Lovin’ It” — they remind us not of their burgers’ great taste, but of how much we enjoy ourselves while we’re there. The Body Shop isn’t able to charge ripoff pricing because they have better-quality skincare products; it’s because they represent environmental sustainability and saving baby turtles. This definition of brands also explains why the Fast and Furious franchise is the 14th biggest in movie history — it’s not about fast cars, it’s about family.

Brands are not about their businesses — they’re more akin to a real human being helping customers to self-actualize as individuals. Likewise, products are not just something to tinker with — they’re a way to help Make Harry Great Again. And if your product can genuinely help Harry do that, boy is it worth more than the sum of its parts.

This settles the question of why strong Brands possess superior pricing power — and why legendary value investors the likes of Buffett and Ackman gravitate towards such businesses. The shared element of all brands, their spark or secret sauce, is that they self-actualize the human individual. That’s the Anatomy of a Brand.

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

Buffett’s famous quote above is something which most of us are familiar with. To my surprise, I wasn’t able to find a quote where Buffett directly says “Buy Low, Sell High” — but that’s the essence of what this quote means.

So if it’s such simple advice, why is it so difficult for so many to follow?

This article aims to break down and explain why it is so difficult to “Buy Low, Sell High” — and unpack the underlying drivers behind this phenomenon. By the end of this article, you should be able to understand it better and change how you approach markets to become a better value investor.

The Fallacy of “Lows” and “Highs” In Share Price Charts

To begin, I would like to address the fallacy of “lows” and “highs” in stock price charts.

Take a look at this chart of INTC’s share price above. At first glance, it seems like you should have sold it 5 years ago, right?

But what if we narrowed down the same chart to just the part between Sept ‘22 - Dec ‘23? What would the chart look like then?

Hmm. Kinda changes the perspective, right?

Now obviously I am cherry picking the timeframe to suit my purposes. Yet for more than an entire year, most investors would have considered INTC a Buy prior to Dec ‘23, and Sept ‘22 to be a bottom. One year is a god awful long time to be experiencing FOMO, right?

Now let’s take things one step further. If I sliced up that same chart in the completely biased manner below, it might even imply that INTC’s upside can only “revert to the mean”. To the moon, baby!

Now ask yourself this. When do you think most investors would be piling into INTC during this cherry picked period? In all likelihood, the closer you get to the end, the more investors would be buying into INTC and cheerleading it. Right? And yet hindsight would tell us that this is exactly the wrong thing to do.

This example emphasizes the fallacies of timing ‘highs’ and ‘lows’ in share price charts. The reality is that there is no such thing as a ‘top’ or a ‘bottom’1. What constitutes a ‘top’ and a ‘bottom’ really depends on what your reference point is.

What do I mean by ‘reference point’? The reference point is today’s share price, because that’s what we benchmark a stock’s historical performance against. If the share price today is higher than it was at some point in the past, we’d interpret the latter as a ‘bottom’. If the share price was higher, we’d interpret that same point as a ‘top’.

The problem with doing this is that the reference point is a moving goalpost — it changes literally everyday! As the charts above show, you can pretty much cherry pick whenever your reference point is to arrive at a completely different conclusion about INTC’s historical performance. E.g. if the reference point is today, then INTC would be underperforming. But if the reference point was Dec ‘23, then it would be outperforming. Right?

This isn’t a problem until we try and forecast the share price trajectory into the future. Let’s try and illustrate what I mean. This time, let’s extrapolate INTC’s share price trajectory to some imaginary point in the future. Just for fun, we shall use Jan 2026 as our reference point.

If INTC’s share price chart in Jan 2026 looked like the one below, we would consider it a Buy today. Right?

But if it looked like the one below, then we’d consider it a Sell today instead. Right?

The problem with respect to reference points in the future is that we don’t know what the reference point will be. If I asked how you’d go about forecasting INTC’s share price in Jan 2026 with 100% certainty, you’d probably give me a deer in headlights look. It’s one thing to look back with 20/20 hindsight — it’s another thing to look into the future with 0/20 hindsight.

And yet that’s the reference point which your performance will be based on when Jan 2026 rolls around. Which is kinda a problem, because as the charts above show, it can really go either way.

Pairing it with the earlier insight, this also implies that you’d be unable to time a ‘top’ or a ‘bottom’ in INTC's stock. Why? Because neither of them exist yet! They’d only exist in Jan 2026; and change in Feb 2026; and change again in Jan 2027! Any notion of ‘top’ or ‘bottom’ in INTC’s share price only exists on hindsight.

This is before we even go into Hard Mode. What about all the macro factors? Will there be a recession by Jan 2026? Will there be a Great War? Will there be some yet unknown new risk (e.g. AI)? How might such scenarios impact INTC’s share price, and change the reference point in Jan 2026? Or Feb 2026? Or Jan 2027 and beyond?

This demonstrates how you can’t exactly time ‘tops’ and ‘bottoms’ just by gawking at a stock price chart — since they only exist on hindsight, and are based on the latest share price. Which is a moving goalpost which changes literally everyday.

This completely dismantles the concept of looking for ‘tops’ or ‘bottoms’ amidst share price trajectory. It also explains why investors have so much difficulty with ‘buying low and selling high’, i.e. timing market ‘tops’ and ‘bottoms’. It’s because the entire notion of it is nonsense.

What Buffett Actually Means By “Buy Low, Sell High”

And yet, clearly Buffett implies in his quote above that one should ‘Buy Low, Sell High’. So how do we square this circle?

Buffett isn’t referring to timing ‘tops’ and ‘bottoms’ the way most people think about it. When most people talk about buying low and selling high, they’re talking about market timing or identifying share price trajectory. In contrast, Buffett is referring to buying assets when they are undervalued, and selling them when they are overvalued. In other words, buying a dollar for 50 cents and selling for $1.50.

Notice the underlying implication of this. It means that Buffett isn’t really trying to get the best price from anything — i.e. timing ‘tops’ and ‘bottoms’. Instead, he is trying to get a good enough price — undervalued when buying, overvalued when selling. He is not trying to be No. 1 by timing ‘tops’ and ‘bottoms’ — he is simply trying to be above-average.

A similar sentiment is echoed in Benjamin Graham’s notion of an “adequate return” in his famous quote below:

Thus when Buffett talks about ‘buying low and selling high’, his context is not share price trajectory, but rather the stock’s fair value. He really couldn’t care less about which particular point on the squiggly line he buys in or sells out of. This is markedly different from how most people interpret ‘Buy Low, Sell High’.

A subsequent implication of this interpretation of ‘Buy Low, Sell High’ is that Buffett isn’t really trying to compete with others whenever he makes an investment decision. Of course he’s the Oracle of Omaha — but he’s not really trying to be the Oracle of Omaha, nor does he care about defending his title. What he’s entirely focused on is buying 50 cents on the dollar, irrespective of what others think of him. And he simply trusts that by following the process (i.e. value investing), he will eventually become No. 1 someday.

Again, and it bears repeating, this means that ‘Buy Low, Sell High’ doesn’t refer to the market timing of share price trajectory. Rather, it is used in the context of buying undervalued assets and selling overvalued assets. The interpretation of the same quote could not be any more different.

This explains why most people have “so much difficulty” with buying low and selling high. It’s because they’re completely misinterpreting what it actually means — it does not mean to time ‘tops’ and ‘bottoms’ in markets. Rather, it simply means to have the guts to buy when everyone else is selling, and the logical conviction to sell when everyone else is buying. In other words:

Click one of the links below for more articles about Value Investing!

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13. Click HERE For More Value Investing Articles

Take a gander at our prior stock research and see for yourself if any of them are ‘Buy Low’!

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

Not Investment Advice. Read Disclaimers.

Most people would not think to associate George Soros with Value Investing, yet he is undoubtedly one of value investing’s biggest contributors. As a reminder, value investing concerns itself with the gap between price and value, rather than low price multiples (i.e. cigar butts) per se.

Aside from his infamous pound trade on Black Wednesday, Soros is best known for his discovery of a market phenomenon known as “Reflexivity”. Reflexivity is not a very intuitive concept, but it’s easier to understand once you contrast it against the Efficient Market Hypothesis (EMH).

While EMH is typically used to describe the existence of efficient markets, the underlying premise of EMH is that financial markets merely reflect fundamentals/reality. That is to say, they reflect reality but are completely independent from reality. This is just like how a mirror reflects the real world, but the world in the mirror doesn’t actually interact with the real world (or even exist).

Under the efficient market premise of EMH, financial markets (“mirror”) simply reflect fundamentals (“real world”) but do not influence them — in the same way that a mirror only reflects the real world, but does not influence what happens in it. What the notion of Reflexivity is trying to suggest instead is the reverse — that financial markets do influence the real world, i.e. what happens in the mirror actually does influence the real world!

This would be akin to a Mirror Ghost trapped in a mirror reaching out of the reflection and strangling the observer. Truly spooky — yet an undeniably real phenomenon in financial markets!

Reflexivity is crucial to recognize because it has all kinds of implications on market prices. Imagine if financial markets didn’t merely reflect fundamentals, but actively influenced fundamentals as well. Wouldn’t it throw out all your assumptions about how financial models work, since the models themselves aren’t supposed to impact fundamentals??

In a system with Reflexivity, fundamentals wouldn’t be an isolated system — they’d be swung around wildly by extenuating circumstances which affect financial markets themselves. Given the feedback loop nature of such a system, wouldn’t recognizing the existence of Reflexivity be of utmost importance when attempting to value businesses?

Let’s use a present-day example to demonstrate Reflexivity in action — $INTC!

Reflexivity & The INTEL-ligent Investor

Unless you’ve been living under a rock, you’ve probably heard about Intel’s catastrophic share price dive by now. It’s gotten so popular, even the share price trajectory has become a meme!

However, a very interesting phenomenon can be observed in its share price trajectory — Reflexivity. On one hand, the recent slide in INTC’s share price was initially caused by its deteriorating fundamentals. However, as developments in financial markets progressed, we can observe management taking actions in response to the share price decline.

This stands in stark contrast to what EMH would prescribe — which assumes that financial markets are an isolated system from fundamentals, like the reflection in a mirror. Assuming otherwise would necessitate modeling a feedback loop system — where the ghost in the mirror influences the real world, and such influence affects the reflection as well. Obviously, this wouldn’t play nice with financial models that are trying to model static systems.

However in INTC’s case, it’s pretty clear that Reflexivity is in play. Following the initial share price drop after Q2 results, CEO Pat Gelsinger immediately sought to calm financial markets by introducing several new suggestions. One of them was segmenting their internal foundry into its own subsidiary (so that it could raise funds independently from the Group); while another was entertaining acquisition offers from Qualcomm.

Given that neither of these events had happened over the prior three years since Pat had become CEO, it’s unlikely that these options had been considered before their latest Q2 results. And since these developments most certainly did impact Intel’s share price, that would confirm the existence of Reflexivity — i.e. the man in the mirror reaching out of the reflection to influence reality.

As Soros alludes to, it’s incredibly important to recognize the existence of Reflexivity — i.e. how financial markets can influence fundamentals, and not just how fundamentals can influence financial markets.

In Intel’s case, it’s actually pretty easy to understand the source of this Reflexivity — the massive (un)popular tide turning against Intel today can only be described as an “emotional” outpouring. Such irrational processes should have no place in our perfectly rational financial status quo — and yet they unmistakably exist.

If Reflexivity didn’t exist, Intel’s management probably wouldn’t be trying so hard to calm financial markets, since they’re actually cash flow positive. Consequently, they wouldn’t have to worry about the “political” crisis of confidence brewing around their stock, potentially compounding fundamental issues (e.g. causing high employee turnover).

The chart above demonstrates Reflexivity in Action, as it pertains to $INTC. The takeaway here is that if an investor assumed that Reflexivity didn’t exist, he would miss the completely new trajectory that Intel’s share price could’ve taken (blue bubble) — and potentially arrive at a completely wrong target price based on the old trajectory (prior to assuming Reflexivity exists).

If you take some time to think about it, this kind of feedback loop — where share prices impact fundamentals, and such altered fundamentals subsequently inform new share price trajectories — can potentially play out ad infinitum, resulting in the final share price outcome being completely different from the old expected trajectory. With the underlying premise of the DCF model assuming perfectly static external environments, it’s no wonder that the sellside gets share price forecasts wrong so often.

The very existence of such an emotional “political” component to the determination of stock prices renders the concept of perfectly rational markets (as dictated by EMH) irrelevant. Markets ARE emotional — hence Keynes’ famous saying “markets can stay irrational longer than you can remain solvent”.

In this way, we have managed to amply demonstrate what Reflexivity looks like in markets. It may feel relatively insignificant, but it’s clearly extremely present in markets. And not acknowledging its existence can clearly lead to making mistakes in markets.

Reflexivity in Other Stocks

If you thought was just a special basket case suffering from this phenomenon, think again. Reflexivity is everywhere — you can’t help but notice it once your eyes are opened to its existence.

Extending the “Man in the Mirror” analogy above, I’ll be using the terms “mirror” and “real life” to more obviously highlight the feedback loop relationship between financial markets and fundamentals with respect to Reflexivity. Here are some examples:

• NVDIA announcing a share split at all-time highs in response to its surging share price (“mirror”); hoping to cultivate greater confidence in Sales & Marketing (“real life”) from having a very publicly inflated valuation (“mirror”);

• OXY rapidly buying back Berkshire preferreds upon the surging of its stock price in 2022 (“mirror”); which has since dramatically improved its gearing from 210% at its peak to 65% today (“real life”);

• GME and AMC issuing shares (“mirror”) following the meme stock craze, which actually improved their balance sheet conditions (“real life”);

• SEA Ltd responding to its share price collapse in 2021 (“mirror”) by rapidly cutting costs in various areas (“real life”), in order to rehabilitate shareholder confidence (“mirror”) — thus allowing its business extra breathing room to navigate autonomously, without which they’d be in trouble (“real life”, feedback loop!)

In each of the above examples, new and unexpected developments in financial markets ended up impacting management decisions in real-life — creating entirely new business fundamentals and thus share price trajectories. Notably, none of these outcomes would’ve likely been caught by a standard DCF model valuation, given its assumption of static external influences on fundamental valuations.

The point of all this is to demonstrate the importance of simply recognizing that Reflexivity exists. It’s not so much something about Reflexivity being all-important, moreso that not recognizing it can be deadly.

This also provides ample evidence for how EMH isn’t exactly a perfect descriptor for how markets work. Financial markets are ultimately about human prediction, which involves all kinds of emotional and non-rational behavior — what we call behavioral economics. As I’ve gone to great lengths to describe in other articles about Value Investing on this newsletter (also see links below), this makes risk management the lynchpin of good investing; rather than return management.

One reason why many value investors end up beholden to the School of Graham & Doddsville is because of massive gaps in orthodox statistical valuation theory like this. It’s not so much that we care incrementally about Value Investing, but rather that we can no longer ignore the flaws which exist in the financial status quo — with all their real-life portfolio consequences. To authentic investors in underlying businesses, we have no choice but to identify as value investors.

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

I’ve been seeing a lot of posts about why Buffett might have sold his substantial AAPL position recently. For instance, the two articles below provide some pretty decent insight into what Buffett’s thought process might be:

Security Analysis

Deconstructing Warren Buffett's Apple Sale

Buffett’s Sale of AAPL…

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2 years ago · 11 likes · 1 comment · Value Stock Geek

In light of this, I thought it might be cool to take a trip down memory lane and revisit my old article about why Buffett BOUGHT Apple — all the way back in 2016.

As I explained, Buffett probably didn’t expect Apple’s share price to take off the way it did after he bought it, nor was he likely thinking about it in terms of its Tech moats. Rather, he was probably thinking about it as more of a Tech version of Coca-Cola — given its incredible brand equity as a Consumer product (i.e. pricing power).

Perhaps more importantly, Apple’s financial profile in 2016 closely resembled that of KO — e.g. high cash balances, negative ex-cash Equity position (i.e. post-share buybacks). Coupled with its 8.8x trailing PE at the time, that made it a classic cheap stock — I honestly don’t think Buffett knew it would eventually become his most profitable investment ever.

Without further ado, let us dive into how Buffett likely saw AAPL at the time… Coca-Cola!

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Financial Analysis: AAPL in 2016

In early-2016, was just coming off from the highs of their “iPhone supercycle” — having just achieved a record-breaking 13 million iPhone 6S & 6S Plus units sold (its first Plus model) within its first weekend of launch.

However, I still recall that its stock was trading at a low 11-12x trailing PE at the time — as there was a genuine concern that their future growth then was fleeting. AAPL had already saturated its China TAM by then, and markets perceived that their incremental China TAM was plateauing. While India did represent another equally sizable market for AAPL, it didn’t have the same levels of income per capita or flagship smartphone market share amongst its local population.

As a result, markets opined that AAPL’s future growth would weep, as there were no more worlds for it to conquer.

Oh how wrong they would be.

As shown in the chart above, Buffett acquired his first stake in 1Q16. Much like his OXY purchases today, his early AAPL purchases were large & gaping — like a hungry toddler. We can see how by 4Q16, Berkshire was entertaining stock purchases of 100-200 million shares per quarter.

However, just because was perceived by the Oracle of Omaha as a Branded Retail champion in 2016 — and was trading at an ex-cash trailing PE of 8.8x —that didn’t automatically justify it as the largest stock holding in Berkshire’s stable of moaty businesses.

What else could Buffett have seen in AAPL at the time? The following quote from this excellent interview with Todd Combs sheds some light onto the matter:

Combs goes to Buffett’s house on many Saturdays to talk, and here’s a litmus test they frequently use. Warren asks “How many names in the S&P are going to be 15x earnings in the next 12 months? How many are going to earn more in five years (using a 90% confidence interval), and how many will compound at 7% (using a 50% confidence interval)?” In this exercise, you are solving for cyclicality, compounding, and initial price. Combs said that this rubric was used to find Apple, since at the time the same 3-5 names kept coming up. 

In the spirit of Yefei Lu’s book, I actually went back and performed a cursory financial analysis of AAPL in 2016 — the way Buffett might have saw it. As a reminder, AAPL’s iPhone business at the time was perceived as being at the tail-end of their growth “supercycle”; and their iPhone business in China was also seen as hitting a glass ceiling of growth, with no immediate replacement market. This perhaps explains why AAPL was only sporting a Market Cap of $600B and an Enterprise Value of $460B by end-2015 — despite posting an FY15 Net Income of $53B. (ex-cash PE ratio of 8.8x)

Now let’s take a look at AAPL’s FY10-16 balance sheet in the chart above, i.e. what Buffett might have seen at the time. As we can see, their historical Net Cash balance had regularly exceeded their Total Equity since 2012 — implying that the company’s solvency was never in question.

Furthermore, they were spending significant amounts annually on Repurchase of Common Stock relative to their equity base — which made sense when you consider that the earnings yield obtained on those share buybacks was simply the inverse of their PE ratio of between 10x - 12x (i.e. 8% - 10% earnings yield) when Buffett initiated his AAPL stake:

In my previous P/B ratio article, we saw how the P/B ratio had a direct relationship with ROE — i.e. Earnings Yield x P/B = ROE. Given that AAPL was regularly sporting 30% - 40% ROE at the time, even their P/B ratio of 4-5x at the time could still result in a shareholder’s Earnings Yield of 8% - 10%. Imagine if you were Buffett — wouldn’t that be enough?

Resemblances with KO

So the question remains… what did Buffett See in AAPL in 2016? The unexpected answer: COCA-COLA!

As I’ve described before in this tweet, there are a startling number of parallels between Buffett’s investment in & his investment in :

• AAPL had by then become a one-product moat business with an identically outsized ROIC as Coca-Cola;

  • AAPL’s Net Cash position was higher than its Total Equity by FY15 — which meant that it could theoretically recreate KO’s negative Total Equity balance via share buybacks overnight. (Figure 1 below)

  • Its iPhone business was sporting a very similarly lucrative ROE/ROIC profile as Coca-Cola; and so were its margins. (Figure 2 below) For context, most retail businesses tend to sport Net Margins of 10% or below.

• By 2016, AAPL was already showing signs of prioritizing shareholder returns, via taking on debt and channeling its practically unlimited FCF towards dividends & share buybacks (of its undervalued stock) — alá The Outsider CEOs:

  • Long-time value investors will understand why Buffett prioritizes this quality so much in his investments.

  • This enormously simplified AAPL’s cash flow model, dramatically improving future earnings visibility and reducing uncertainty (and therefore risk). Coincidentally, this is also exactly how I described Buffett’s current investment in OXY! (link below)

• AAPL occupied an entrenched position in the highly moaty Branded Retail sector:

  • This gave AAPL pricing power, Buffett’s favorite business characteristic.

  • Its iPhone business also adequately fulfilled Buffett’s quote below:

Hence, going back to the Todd Combs’ quote above, how did AAPL fare in 2016 based on Todd’s investment requirements above?

1. How many names in the S&P are going to be 15x earnings in the next 12 months?

Answer: AAPL was already trading at below 15x earnings in 1Q16, and even consensus at the time agreed that its earnings would still post positive growth going forward (albeit slightly muted). It was highly likely then that AAPL would remain at >15x earnings within the next 12 months (i.e. 1Q17).

1. How many are going to earn more in five years (using a 90% confidence interval)?

Answer: Even without any incremental TAM growth from China going forward, it would be highly unlikely that an investor in 2016 would have imagined AAPL posting negative cumulative earnings growth over the next 5 years.

3. How many will compound at 7% (using a 50% confidence interval)?

Answer: The valuation exercise above has adequately demonstrated how an investor in AAPL in 2016 could have estimated a LT total shareholder return of 10% quite conservatively.

Todd goes on to say that, “In this exercise, you are solving for cyclicality, compounding, and initial price.” Maybe Berkshire was special since it had the privilege of entertaining LT yields of 10% while still considering it satisfactory — nonetheless, we can see how AAPL in 2016 could quite easily cleared all of Buffett’s hurdles, and therefore justify its top dog status in Berkshire’s already legendary stock portfolio.

But wait, there’s more!

There’s a notable elephant in the room here — none of the investment requirements above imply that Buffett had bought knowing in advance that it could clear +30% CAGR over the next 7 years! In contrast to the popular narrative, it seems far more likely that he had made his investment decision into AAPL thinking that there was simply no way he could possibly lose money on it — and he was perfectly fine with the 10% yield or whatever that he could get out of it. If true, this would align magnificently with Ben Graham’s following quote:

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

The three quotes above by the founders of value investing — Benjamin Graham and Warren Buffett — suggest that the protection of investment principal is paramount. This serves as the unyielding bastion of value investing — the principle of capital preservation.

So, how do we reconcile that with the title of this article — The Intelligent Gambler? And why do I call such an investment methodology ‘The Intelligent Investor on Steroids’?

As many value investors can identify with, it is difficult to square Buffett’s Rule No. 1 of “Never Losing Money” with the promise of value investing, “generate excess returns over the long-term”. This is what The Intelligent Gambler seeks to reconcile — enjoining capital preservation with risk:reward asymmetry in order to generate excess returns, even in efficient markets.

It’s also a framework which sheds extra light on Buffett’s following quote:

“The most important quality for an investor is temperament, not intellect. You need a temperament that neither derives great pleasure from being with the crowd or against the crowd.”

As its namesake implies, The Intelligent Gambler has to be okay with jumping into risk/danger; but also be very calculative in doing so. In other words, he is a calculated risk-taker. Those are two oxymoronic traits — one leaning conservative & measured, the other leaning aggressive & instinctive — quite a rare combination to be found in the same person.

But those who are wired differently and have a steady hand amidst risk/danger can enjoy the fruits of market outperformance. Michael Burry’s recent outsized positions in Chinese stocks demonstrates this — his appetite for managing outsized levels of Uncertainty is admirable, a trait which was most certainly also present during his subprime mortgage trade in 2008.

Also, notice how such an investment process couldn’t be any more different from the status quo, i.e. forecasting target prices accurately? Doing so implies reaching for absolute certainty; whereas in contrast, The Intelligent Gambler deliberately entertains massive uncertainty, only seeking to control risk once beyond the statistical pale.

The ‘gambler’ part alludes to the necessity of considering success from the lens of uncertainty (bottom-up) rather than achieving outcomes (top-down); whereas the ‘intelligent’ part requires the individual to be very deliberate about risk-taking, rather than throwing caution to the wind. In this article, we shall unpack his secrets and understand how adopting an Intelligent Gambler framework can help you generate excess returns — amidst and despite efficient markets.

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Creating 10x Leverage by Gambling with Uncertainty

One concept that you will often come across in political commentary is “gambling”. For instance, Macron’s gamble by announcing the French snap elections, or the Democrat party’s gamble to replace Biden with Kamala Harris.

The premise here is that once a particular subject matter reaches ultra-massive scale (e.g. macroeconomics, policymaking, geopolitics), it becomes impossible to sufficiently control for all possible factors. This is especially so once you add in the human element (e.g. how your opponent will react) which introduces butterfly effects into the equation.

Such excessive levels of uncertainty makes trying to chart a direct path to success an exercise in futility (e.g. forecasting share prices). As such, the business world recommends “just do(ing) it” — i.e. turning a blind eye to risk and simply charging ahead recklessly as a means of overcoming obstacles. However, the status quo in the fields of markets, politics and war is somewhat different — they recommend the application of asymmetric risk:reward to controlling risk amidst excess levels of uncertainty.

An asymmetric risk:reward strategy suggests taking a very measured and calculated approach to risk control, in order to manage outsized levels of uncertainty. This is fundamentally a bottom-up approach which recognizes the futility of goal-setting amidst excess uncertainty — which stands in stark contrast to the top-down status quo of forecasting share prices. The fulcrum of such a strategy lies in the “gamble” — where outcomes are uncertain (hence the gamble), but one optimizes the distribution of possibilities on a best-effort basis from a statistical standpoint.

By rolling the dice intelligently, The Intelligent Gambler creates leverage in potential outcomes — by adding to his moveset outcomes which were not previously available to him. This widens the aperture of possible outcomes beyond what is afforded by the status quo, at the expense of greater risk. And by capturing a smaller potential of that wider aperture, he is capable of creating better absolute outcomes — i.e. 10% x 1,000 > 90% x 100.

Of course, this can only be done at the expense of significantly greater risk, since The Intelligent Gambler is now entertaining a much greater realm of possible outcomes, many of which are beyond his control. Hence, it is the mastery of risk control (rather than profit maximization) which allows him to participate in excess opportunities previously unafforded to him — without getting sideswiped by a bus in the process.

Let us use Macron’s Gamble to illustrate the phenomenon of The Intelligent Gamble in politics. Prior to the snap elections, his Centrist party had been stunned by the EU elections, which had seen a resurgence by the far-right. By calling for a snap election, he entertained two gambles:

1. The 1st gamble was to capitalize on the recent shock of the far-right’s surge, hoping that it would result in a higher voter turnout. This would offset the more organized turnout that fringe parties typically sport, e.g. Marine Le Pen’s National Rally or the NRA wing of the US Republicans.

2. The 2nd gamble was that the two-round French elections (in contrast to the one-round EU elections) would favor the less bad candidate rather than the better fringe candidate. This would favor the larger & more vanilla Center/Left coalition over Le Pen’s smaller and more fringe far-right.

With the benefit of hindsight, we now know how his gamble played out. Macron’s plan to keep the far-right out of power played out according to plan; even if it ended up with his own party taking a backseat to the newly resurgent Left.

This example illustrates the phenomenon of Leverage in Gambling. By embracing rather than shirking uncertainty in potential outcomes, the gambler positions himself with greater leverage via exposure to a higher number of possible outcomes — more specifically, including those beyond his control. At the same time, he approaches the incremental risk with great respect rather than throwing caution to the wind, and applies expert risk control to maximize his chances of positive outcomes.

The sum of this creates an enormously potent cocktail of differentiation, which exposes The Intelligent Gambler to a significantly larger universe of potential outcomes — allowing him to generate excess returns with sufficient risk control. This is what I mean by 10% x 1,000 > 90% x 100 — if you have 10x greater potential, you can outperform even with 10x lesser efficiency.

Of course, doing so is not a free lunch, as leverage by definition involves greater risk. Hence, it is not the “gamble” per se but the mastery of risk control that generates excess returns. Simply gambling would amount to a “just do it” approach — something which may work in business, but certainly not in markets. Or politics. Or war.

The Art of the Intelligent Gamble = Asymmetric Risk:Reward

A similar “gamble” phenomenon exists in markets as well. Market prices tend to involve an infinite number of determinants owing to macro factors, making it practically impossible to accurately forecast share price trajectory. And since investors hate uncertainty with a passion, they tend to crowd into trades with highly certain outcomes.

Such hyper-competitive arbitrage behavior in efficient markets naturally leads to rising valuations in stocks exhibiting lower uncertainty, and vice versa. Entertaining the latter provides opportunity for gain — since where there’s risk there’s reward, and where there’s reward there’s also risk.

Now, the Intelligent Gambler cannot predict future outcomes better than anyone else. What he can do better than others, however, is make more intelligent gambles — this creates new opportunities without an excessive increase in risk. For instance, he might be willing to take on risky positions despite their heightened uncertainty — but only where the odds represent an excessive level of good sense. This exposes him to the possibility of excess upside as compared to others who merely stick to absolute certainty, without the excessive downside.

The competitive differentiation of doing this lies in how most people abhor putting themselves in such a position — uncertainty involves danger. They would rather snuggle in the warm embrace of certainty (e.g. safety in numbers) despite rising valuations that all but guarantee loss. In other words, human nature is so strongly wired to prioritize emotion over logic that we would rather entertain emotional certainty over logical uncertainty.

If so, then the vector of excess returns lies not in the domain of higher logic as suggested by the status quo, but in higher emotion. Specifically, The Intelligent Gambler has the capacity to override his own faulty intuition after repeated validation that his estimations are correct. Thus, by diving into high levels of uncertainty where others are unwilling, he gives himself the opportunity to participate in excess returns. This is ultimately what I think Buffett meant by his aforementioned quote:

Let us use Meta in Nov 2022 as an example to illustrate what the description above looks like in a stock market context.

At the time, Zuckerberg had just doubled down on the Metaverse following its botched release — while simultaneously entertaining a two-front war against Apple’s ATT and Tiktok. Stock investors responded by violently fleeing Meta, concerned that a madman with absolute voting control would teleport their capital into oblivion.

Yet as my article explored at the time, a closer look into Meta’s stable of businesses reveals a much gentler outlook than consensus expectations:

• Given its global scale, there was no true alternative to replacing Facebook. Fears of attention spans waning might have impacted growth, but not cash flow.

• Even then, Instagram’s Reels was in no danger from being rendered utterly irrelevant by Tiktok, since India had banned the latter.

• Whatsapp had yet to be monetized in a scalable manner.

• The entire company was valued at 8x trailing PE. Even accounting for future Metaverse CAPEX of $100B, their normalized PE would only rise to 12x.

• In a worst-case liquidation scenario, the company could likely sell its global database as an advertising concern for at least 12x PE — if not much more.

This is what I mean by only taking risk after repeated validation of estimates. At some point, the opposite of hubris becomes true — undeniable and recurring evidence that valuations have become detached from fundamentals, despite herd mentality implying otherwise. At this point, logic would dictate that Meta’s valuation was significantly mispriced and consensus fears had been overblown, given the distribution of possible future outcomes.

However, if the facts above could’ve been easily observed, why did most investors flee Meta instead? The reason was simple — there remained too much uncertainty. Even if logic told them that all of the above was true, Meta’s persistently cratering share price would be ringing warning bells like crazy — “what else could I be missing”? And it’s precisely that lack of certainty which causes people to lose their nerve — the same visceral gut punch from having a lion charge straight at you.

Now, The Intelligent Gambler is not immune to this either as he is every bit as human as anyone else. However, here is where he differs — rather than requiring certainty, he entertains gambles when the facts on the ground supports taking them. In doing so, he is able to override his intuition and observe logic when it’s needed most.

What Buffett Really Meant

This is what Buffett means by “Rule No. 1: Never Lose Money”.

It doesn’t mean to play it safe — on the contrary, it means to deliberately step into the unknown as a necessary condition for generating excess returns in efficient markets. But once there, one needs to have a very disciplined risk budget in recognition of the outsized levels of risk in doing so.

This combination of Gambling with Uncertainty + Margin of Safety is what it means to be an Intelligent Gambler.

It’s worth repeating here that describing it as a “gamble” doesn’t imply recklessness. Rather, it is called a “gamble” simply because there are too many factors outside of the investor’s control — and he has no choice but to accept excessive levels of uncertainty in order to generate excess returns in efficient markets.

However, those excess levels of uncertainty are tempered by taking a very measured approach — and having a healthy respect for risk, rather than a lack of it. This is the opposite of reckless abandon.

Like Macron above, The Intelligent Gambler recognizes the futility of trying to generate excess returns by merely sticking to the status quo — hence he takes risk because he has to, but only when the odds make extremely good sense. This is about the furthest thing possible from throwing caution to the wind; it’s more akin to becoming a master of threading the needle.

If you really know what you’re doing, you can come out ahead by taking far more conservative stances on positions involving much higher uncertainty than others who take a riskier stance on more predictable positions. And in doing so, The Intelligent Gambler entertains greater returns. To illustrate it in numerical terms:

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Check out my previous articles about Value Investing:

1. What Did Buffett See in AAPL in 2016? Coca-Cola

2. Is EBITDA Really Bullsh*t?

3. How To Create A Low-Volatility Value Investing Portfolio

4. When To Sell Stocks, According To Warren Buffett

5. Unpopular Opinion: Diversified Portfolio > Concentrated Portfolio

6. Was John Maynard Keynes A Value Investor?

7. RISK: The Definitive Value Investing Definition

8. MUNGER | Warren Buffett's BFF

9. Value Investors = Business Owners. Here's The Irrefutable Proof.

10. How I Became 100% Convinced that Value Investing Was Superior

11. Click HERE For More Value Investing Articles

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

The 6 "Notices" (see below):

1. Notice how it's about risk-first, profit-later?

2. Notice how it organically results in a long-term investment horizon?

3. Notice how it makes investors chase very different stocks?

4. Notice how it renders market volatility irrelevant?

5. Notice how it makes investors purely focused on fundamentals?

6. Notice how it demands a very large Margin of Safety (because he can't sell)?

Buffett is quite well-known for his quote above about “when to sell”. At first glance, this makes sense. Anyone who is familiar with Buffett will know that he tends to buy and hold his successful positions without selling them1 — e.g. he has held onto Coca-Cola since 1989, and more recently has held onto Apple since 2016.

However, many value investors get stumbled by the subsequent implications of such an investment approach. If one buys and holds forever, how do they enjoy their returns? Surely profiting from dividends alone isn’t ideal, right?

It may surprise readers to discover that Buffett’s quote above actually has plenty of incredibly complex subtext, both for holding periods as well as how to think about stocks. In this article, I’ll unpack them for the hungry acolytes attending the school of Graham & Doddsville.

“When Should You Sell?”

Most people think about stocks as pieces of paper — i.e. acquire them for a price, hold onto them for awhile, and then sell them later for a profit. Even value investors tend to think this way, albeit over much longer timeframes.

What Buffett actually means by “our holding period is forever” is to genuinely consider stocks as pieces of a private business. I know this sounds unbearably cliché, but really think about what that means. It just means what I’ve implied above — that Buffett only intends to realize his gains via dividends or share buybacks (i.e. total shareholder return).

While this is something easily understood on the surface, the actual implications of such a methodology are harder to embrace. For instance, think of the hedge funds across the world who would balk at such a rigid approach. How does one even run a fund with a rule of “never selling”?

What happens if the investee business deteriorates? Does the fund manager simply dogmatically stick to his principles, and risk going down with the ship? Where are the boundaries for this principle drawn, and at which times is it okay to forego the rule?

As aforementioned, Buffett’s holding period of “forever” implies that he only intends to realize gains from dividends and buybacks. That simply means to treat the stock investment as buying shares in a private business.

To be clear, this is indeed how most value investors frame their investment decisions — where valuation is purely a function of underlying profits. However, Buffett’s quote seems to go deeper than that. He isn’t merely saying that valuation should purely be a function of fundamentals — his quote implies literally recovering your capital via dividends and buybacks alone, without ever selling the stock. This is where I think the majority of self-identifying value investors and Buffett himself would go down separate paths.

Consider two value investors: one who buys a stock planning to flip it after 5 years; and another who buys a stock planning to never sell it. Ever. What would be the differences in attitude that both would have when buying stocks?

Firstly, while the former may very well intend to hold his stock for ultra-long periods by most respects, he still has an escape path should things turn sour. This means that he would likely have a higher risk threshold than the latter — in the worst case scenario, he can still sell and get out of the position to recover some of his capital.

Meanwhile, the latter investor understands that if he buys a stock and it fails, he goes down with the ship. Notice how this is a risk that most investors wouldn’t even think about? If the investor has to consider the possibility of being handcuffed to a sinking ship, he’d likely demand a much larger Margin of Safety, right?

This is also where Buffett’s quote “the trick is, when there is nothing to do, do nothing” becomes highly relevant. A practitioner of such an investment philosophy is going to find very few stocks that meet his significantly higher-than-normal risk criteria. One might only come across 1-2 stocks per year that fits the bill.

To clarify, when I say “risk”, what I mean is the permanent loss of capital, not business risk. As I’ve explained in last week’s article, it is possible to buy a significantly undervalued stock and not experience any loss even if the business subsequently deteriorates — as such business risk had already been priced-in. Hence, just because a business appears risky on the outside, that doesn’t automatically equate to capital risk (and vice versa).

The 6 “Notices”

1. Notice how it's about risk-first, profit-later?

2. Notice how it organically results in a long-term investment horizon?

3. Notice how it makes investors chase very different stocks?

4. Notice how it renders market volatility irrelevant?

5. Notice how it makes investors purely focused on fundamentals?

6. Notice how it demands a very large Margin of Safety (because he can't sell)?

As aforementioned, most investors think of profiting from stock investments as reselling a stock at a higher price for capital gains. This usually involves some hazy, intangible estimation of valuation multiples in the future — or an equally ethereal comparison to peer multiples.

While this is a legitimate approach to valuation, it’s ultimately a mystical art with no well-defined rules. If you’d like to test it out, ask an analyst who came up with their comp-based valuation to put their money where their mouth is — and watch their reaction.

In contrast, most analysts tend to widely agree on how to estimate future profits. This is because profits exist in the tangible world, and are constrained by real-world “rules” which form the boundaries of our imagination. While the estimation of profits are ultimately subjective, their estimations are subject to significantly less abuse than multiples are.

However, when investors are forced to think about a future exit price, that invariably involves an estimate of future exit multiples. This is where you get hazy justifications like “10x PE for no-growth” or peer multiple comparisons — which begs the never-ending infinite “why?”. Add in a sprinkle of macro volatility, and that’s a recipe for hubris in valuation.

Now let’s consider how Buffett would approach valuation instead — based on his quote above, “our favorite holding period is forever”. That implies that he never intends to sell, right? Subsequently, wouldn’t it also mean that he wouldn’t have to estimate an exit multiple?

As aforementioned, Buffett is actually more interested in recouping his capital via business profits over time rather than by selling the stock — this ultimately boils down to dividends + share buybacks. This is why it’s called “RETURN of capital” — it’s the company returning the investor’s investment, in the form of profit distribution.

Let’s pause here and consider the implications of adopting such an investment process. An investor who truly practiced such an investment process would end up choosing VERY different stocks, right? Since he only intends to recover his investment via profits, he would first and foremost be highly concerned with the price paid for the investment relative to profits (i.e. multiples).

While this doesn’t preclude high-multiple stocks if sufficiently high growth can be justified, it does motivate the investor to prioritize recovering his capital before even thinking about profiting from his investment. This is in stark contrast to the behavior of most stock market participants, which is to consider profit first.

Firstly, notice how this a a risk-first narrative, as opposed to a maximum profit narrative? At the risk of repeating myself, someone who truly intends to recover his investment via business profits alone would most certainly prioritize recouping his capital before thinking about gain. In fact, this is exactly how most M&A operators behave — it’s just normal business logic.

Secondly, notice how having such an investment mindset organically results in a long-term investment horizon? If you truly cared about recovering your investment only via business profits, you would automatically have an investment horizon spanning 10-20 years at a minimum. Anything earlier than that tends to be a bonus.

Thirdly, notice how such an investor would be chasing remarkably different stocks than the ones which get most market participants excited? Consider something like GM, which David Einhorn has been invested in for the better part of the past decade — and which has stayed at single-digit multiples the entire time. BORING, right?

However, after including dividends, I bet Einhorn managed to get his 15% required annual return on the GM investment while assuming miniscule risk. What percentage of Bitcoin or Tech megacap “HODL-ers” can truly say they beat his performance over the past decade?

Fourthly, notice how such an investment approach renders market volatility completely irrelevant? If an investor only cared about recovering his investment via business profits, would he really worry about daily fluctuations in the stock price? As long as it doesn’t affect the business — and it usually doesn’t — who cares what the stock price is at any given day?

This goes back to what Buffett was saying about not monitoring stock tickers. Since he only cares about business profits, whatever the stock price does is truly irrelevant to him, despite Buffett obviously being capable of assessing macroeconomics. This goes back to another quote of his — the about not knowing what the stock price would do tomorrow, a week from now, or a year from now.

Fifthly, notice how such an approach automatically makes Buffett truly an investor in purely business FUNDAMENTALS? I think this part is self-explanatory — if one only cares about recouping the investment via business profits, they shouldn’t really mind what the stock price does from day-to-day.

And finally, notice how practicing Buffett’s investment approach demands a very large Margin of Safety — since the value investor’s never intends to get out of the position? We’ve already covered this above.

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Lesson: Only Expect To Breakeven From Profits

This is what Buffett means by having a holding period of “forever” — it means to only ever expect to breakeven on the stock investment from business profits. Some might say that I am simply referring to the PE ratio — but rather than expect to sell the stock at a higher stock price, value investors should only expect to get their capital back from profits/EPS! Given such a constraint, doesn’t that significantly change your attitude towards stocks?

As a true-blooded value investor who took such a long time to arrive at such insight, I can testify without a shadow of a doubt that understanding what Buffett really meant has changed how I invest. Not only because it gave me such a stark form of competitive differentiation in terms of how I invest — in a way that barely any competitors (i.e. other market participants) will bother to replicate — but because it feels like something I can truly put it into real-life practice to grow my personal wealth.

And now that you’ve read this article, hopefully you feel the same way too!

Check out our previous stock reports:

1. Click Here For More Value Investing Articles

2. Nvidia ($NVDA)

3. SEA Ltd ($SE)

4. Floor and Decor ($FND)

5. Tesla ($TSLA)

6. Disney ($DIS)

7. Intel ($INTC)

8. Paypal ($PYPL)

9. Occidental Petroleum ($OXY)

10. My LinkedIn

11. My Twitter

Disclaimers:

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

"The beauty of such an investing principle lies in the versatility of its application. It can take the form of Graham’s cigar butts, Buffett’s compounders, Peter Lynch’s diversified growth, Howard Marks’s counter-cyclicality, Michael Burry’s deep value, Monish Pabrai’s asymmetric risk:reward or Li Lu’s high conviction. None of them exclusively represent Value Investing; yet all of them observe its fundamental first principles." 

TABLE OF CONTENTS:

1. Could A God Beat EMH?
2. Exorcising Black Swans
3. It’s Market Outcomes That Matter (Not Real-Life Outcomes)

4. How To Be A God (In Markets) i.e. a Value Investor.
i. Low-probability events matter in investment decision-making
ii. It is not real-life outcomes that matter, but market outcomes.
c. Investing Like Gods: Combining i. and ii.

5. Low-Probability, High Impact Investing

Q: Could you invest like an all-seeing god who can see the future?

To answer this question, let us first clarify the definition of the Efficient Market Hypothesis (EMH). For the purposes of this article, we will only be discussing strong-form EMH1.

Many value investors seem to think that strong-form EMH means that markets are always correct about the future, by virtue of having millions of eyes on the same asset, and therefore pricing it efficiently. However, the actual definition of strong-form EMH according to Investopedia doesn’t actually imply that:

The strong form version states that all information, public and not public, is completely accounted for in current stock prices, and no type of information can give an investor an advantage on the market.

The existence of EMH doesn’t imply that markets are correct about the future all the time — it merely says that there’s no point in stockpicking, since market prices have already accounted for all known information across society, thus arbitraging away any further upside based on fundamental values.

The logical corollary here is that that such “all known information” has to be at least “known” by some humans in the world in order to be priced-in. But what about “unknown” information that nobody except a god would know — such as information which lies in the future?

Shout-out to Tech Investment’s excellent article about HBM and SK Hynix below!

Tech Investments

The battles for the HBM and AI cloud markets, AMD's large opportunity no one is talking about, SK hynix the deep value AI play, and KLA signals a semicap ramp

The battle for the HBM market High bandwidth memory (HBM) has become a key enabler of the wave of innovation in LLMs by providing GPUs with high speed access to stacks of co-packaged DRAM, speeding up both AI training and inferencing. In HBM, DRAM dies are connected by high-bandwidth through-silicon-vias (TSVs) and microbumps to a logic die at the bottom…

Read more

2 years ago · 30 likes · Tech Fund

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Could A God Beat EMH?

Let’s assume that one of the Greek gods came down from Mt. Olympus, and decided to try their hand at modern-day stock markets. Unlike us mere mortals, these gods have the uncanny ability to be able to see into the future.

Would EMH thus apply to Them? The answer is no, because a true God would be privy to even “unknown” information — i.e. information which only exists in the future, and which doesn’t yet exist in the present-day. Thus, they could prophesy which stock would outperform in the future, and simply buy it today in truly risk-free fashion.

What might such “unknown” information look like? Think of some of the global developments which have occurred recently that could be categorized as “unknown” future information. The pandemic, Ukraine war, Israeli-Gaza war, the rapid improvement of the US economy — all of these would be widely considered as “unknowable” in advance, no matter how good the investor.

Statisticians would call these “black swan events”. In essence, these events have such low probabilities of occurrence (e.g. single digits) that no rational human actor would consider pricing them into market prices. It would simply be too “inefficient” to do so.

The problem with such a position is that black swan events actually occur with regularity in macroeconomics — the past three years should bear testament to that. And as past share prices have demonstrated, all (human) market participants in aggregate miss these low-probability events all the time. This is why Howard Marks said in a recent interview that “an economist is a portfolio manager who never marks to market”:

However, clearly a true god who can perceive the future would not have such a problem. By virtue of having an all-seeing eye, He would be able to identify exactly which low-probability event in the future would happen, and pick a stock which hasn’t priced-in such future “unknown” events yet.

The reason why I’ve incorporated literal gods into this illustration is to really drive home the weakness of even strong-form EMH in correctly predicting future market outcomes — only an actual god could do that consistently. No human could, not even a JP Morgan analyst.

In truth, our statistical framework of market valuations is quite flawed in representing the truth about the distribution of future probabilities. And yet in benchmarking an investor’s performance to future investment outcomes, our financial status quo sets market expectations at the level of an all-seeing god.

Exorcising Black Swans

Think about the weight of what I’ve just described. Just because a market event has a low-probability of occurrence, that doesn’t mean it cannot happen — which is how we tend to treat black swan events. In reality, these kind of low-probability events happen ALL THE TIME, with devastating market impacts.

But why do low probability events happen all the time in markets? It’s simple — the world is inconceivably vast. When you have a gazillion different Category 5 risks simmering under the surface at any given time, just one of them materializing could trigger a cascade of other risks like dominoes, often culminating into a newsworthy global tragedy.

This is where the dissonance between statistical expectations and actual portfolio outcomes hides. If your portfolio is ant-sized, even a slight nudge of your anthill would be enough to collapse it. And just because a particular risk has a low probability of occurrence is irrelevant. In the grand scheme of things, the sheer vastness of the world virtually guarantees that at least one such event has a reasonable chance of happening in your backyard at any given time. Couple that with the contagion effect of different risks, and you can see how reasonable this assessment is.

Lesson No. 1: Low-probability events matter in investment decision-making. Ignore them at your peril.

Obviously, a god wouldn’t have a problem with this, since they’d just peer into the future and plan around it. So how can value investors incorporate such divine prophesy in their portfolio decisions?

It’s Market Outcomes That Matter (Not Real-Life Outcomes)

If the world is truly so vast as to render even low-probability events potentially earthshaking to our ant-sized portfolios, then obviously we cannot ignore low-probability risks in our investment decisions. But what can we do then? Surely it’d be unrealistic to account for every single risk in the world?

The good news for (human) investors of public stock markets is that we aren’t actually beholden to future real-life outcomes. We are actually beholden to are future market outcomes.

This is an important distinction to make, because market prices tend to be efficient — i.e. prices and fundamental values tend to equilibrate. For instance, high-probability risks tend to result in low share prices; whereas low-probability risks tend to result in high share prices.

Hence, it is not the development of actual risks in real-life that matters, but the impact of risk on the trajectory of market prices. In other words, if the development of a risk in real-life results in no impact to market prices, that’s totally fine!

Let’s illustrate this with an example. Suppose a bank business isn’t doing so well today due to an egregiously inverted yield curve. Markets would therefore price-in the future risk of real-life underperformance, resulting in a lower valuation. Hence, even if that risk materializes in the future, its valuation shouldn’t fall further — because it’s already priced-in.

Now let’s imagine that the risk doesn’t actually materialize. Since that anticipated risk has already been priced-in, its evaporation in real-life should result in the bank’s valuations reversing back up.

This example shows how it is not actual real-life outcomes which matter, but their impact on stock prices which do. And that depends very much on whether those outcomes will impact share prices, rather than the occurrence of those outcomes per se.

And it is here that we can begin to wield the power of the gods — by exploiting not just market probabilities, but market impacts.

Lesson No. 2: It is not real-life outcomes that matter, but market outcomes.

How To Be A God (In Markets), i.e. a Value Investor.

As we’ve explored above, strong-form EMH only prices-in what humans can foresee. It doesn’t price-in what only gods can foresee, but humans can’t.

Hence, to beat the market the solution is simple: invest in outcomes that only gods can predict. Simple, right? But as mere humans who can’t predict the future, how can we put this into mortal practice?

The good news is that we don’t need to invest in real-life outcomes that only gods can predict. Rather, we can invest in market outcomes that only gods can predict!

To illustrate this, we need to combine the two lessons we’ve learned above:

1. Low-probability events matter in investment decision-making.

2. It is not real-life outcomes that matter, but market outcomes.

Lesson No. 1: Low-probability events matter in investment decision-making

Imagine if you had invested in a low-probability outcome and it turns out wildly in your favor — whereas everyone else had missed out on it. You’d look like an investing god right?

One such example of this might be when I invested in META right at the bottom in Nov 2022 — it’s up nearly 450% now. Did I predict that this would happen? Certainly not, in fact I was quite upfront about not knowing what would happen in that META article.

However what I did know even then was that META’s valuation was roughly 8x trailing PE at the time. To me, it sounded completely absurd that even the emergence of a rival Tiktok feed would render its database of 2 billion people in the global middle-class population irrelevant. At worst, it could simply diversify into the advertising business — more than justifying an 8x trailing PE.

Obviously, markets considered such a contrarian take a low-probability event, as evidenced by its share price at the time. And yet, it most certainly ended up mattering. This naturally segues into…

Lesson No. 2: It is not real-life outcomes that matter, but market outcomes.

Notice how I described my thought process behind META in Nov 2022. I described it as trading at 8x trailing PE, more than enough to justify the worst-case scenario.

That means that what I cared about wasn’t META’s real-life outcomes, but rather its market outcomes! While markets were worried sick about Facebook potentially being disrupted by Tiktok, I was thinking about how markets had already priced-in such a risk, and therefore the downside was practically nil.

Even if Facebook’s business did get disrupted by Tiktok as expected, META’s share price was unlikely to fall by too much more — even if it did something radical like diversifying into the advertising business! This is exactly how I framed my bank stock example above.

And similarly to my bank stock example above, the subsequent rapid evaporation of the Tiktok risk (which nobody could have predicted, including myself) resulted in META’s market valuations correcting back up — as the anticipated risk that was priced-in failed to materialize.

This is what George Soros meant by his following quote:

As we can see, Soros was not preoccupied with the likelihood of occurrence of real-life outcomes (“right or wrong”). Rather, he was preoccupied with their market outcomes (“how much money you make/lose” when they occur).

Investing Like Gods: Combining Lessons No. 1 and 2

So how do value investors exploit the overlap between these two lessons? Allow me to use my META example above to illustrate further.

Firstly, META was only valued at 8x trailing PE at the time because markets had considered a rebound in its fundamentals a low-probability event. In other words, investors are unlikely to find bargains in high-probability events widely agreed on by market consensus, since EMH equilibrates share prices and fundamental values.

At the same time, META’s low valuation at the time (contributed by low upside probabilities) also meant that further downside risk was low, since markets had already fully priced-in such risks.

Conversely, markets had failed to price-in any possible upside to META — resulting in anyone who had bought their stock at the time looking like an investing god today.

Do you see how value investors “Invest Like Gods” now? By turning our attention away from:

1. the normal probability distribution of real-life outcomes built into consensus valuations, towards

2. the “abnormal” distribution of market outcomes, which can deviate from the normal probabilities of real-life outcomes (built into consensus valuations)

…we can exploit market inefficiencies by taking contrarian positions (i.e. low upside probabilities) — which, should such low probabilities actually materialize, would make you look like an investing god!

The only mandatory caveat here that must be observed is that care must also be taken to ensure that even if such low probability events fail to materialize, one does not incur any risk.

Luckily, underperforming stocks whose battered valuations have already priced-in future risk typically naturally sport significantly reduced risk — by virtue of their battered valuations alone.

By doing so, we truly put into practice Soros’s quote above:

Low-Probability, High Impact Investing

In fact, this is not a particularly novel application of low-probability, high impact strategies which only belongs to value investing. Classical finance also advocates for such an investment approach — you may have heard of it before: Asymmetric Risk:Reward.

At its very essence, this is what Value Investing means. It is to invest with a Margin of Safety, where you Never Lose Money no matter what happens, with a portfolio designed to promise safety of principal and adequate returns.

The beauty of such an investing principle lies in the versatility of its application. It can take the form of Graham’s cigar butts, Buffett’s compounders, Peter Lynch’s diversified growth, Howard Marks’s counter-cyclicality, Michael Burry’s deep value, Monish Pabrai’s asymmetric risk:reward or Li Lu’s high conviction. None of them exclusively represent Value Investing; yet all of them observe its fundamental first principles.

If you’d like to know more, the articles below will get you up to speed on these value investing principles:

The only difference between value investors and actual gods is that the latter is able to see the future; while the human value investor is merely exploiting the inherent inefficiencies in statistical attribution of market prices to future real-life outcomes2 — and positions his portfolio for low-probability but high impact outcomes3.

In fact, many of the legendary value investors are actually quite upfront about their inability to forecast future market outcomes — these include self-made billionaires like Warren Buffett, Charlie Munger, Benjamin Graham, Howard Marks and Seth Klarman. Ironically, in teaching us to try and accurately forecast market outcomes, it is classical finance theory that assumes that we are gods who can actually see the future.

I’d invite you to read some of my previous stock reports on this newsletter to determine for yourself whether I’ve actually been faithful to the value investing methodology as I’ve described above. This is what Value Investing really means!

Check out our previous stock reports:

1. Click Here For More Value Investing Articles

2. Nvidia ($NVDA)

3. SEA Ltd ($SE)

4. Floor and Decor ($FND)

5. Tesla ($TSLA)

6. Disney ($DIS)

7. Intel ($INTC)

8. Paypal ($PYPL)

9. Occidental Petroleum ($OXY)

10. My LinkedIn

11. My Twitter

Disclaimers:

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

Not Investment Advice. Read Disclaimers.

Benjamin Graham’s greatest contribution to the global investment community was the widespread recognition that stocks were not just pieces of paper. In stark contrast to Jesse Livermore’s wanton bucket shop trading in the early 1900’s, Graham recognized that stocks in fact represented a claim on the underlying business assets — and proceeded to profit from it by acquiring them at below market value. This approach wowed young Buffett — who purportedly would not shut up about his mentor after reading The Intelligent Investor — and later came to be popularized as the “cigar butt” style.

Both Graham and Buffett made a pretty penny through their careers by taking last puffs from cigar butts — e.g. Sanborn Maps, Blue Chip Stamps, Wesco Financial, Nebraska Furniture Mart, Berkshire Hathaway — but ultimately the style fell out of favor. This was because as the cigar butt style came to be more well recognized by the wider investing community, market prices broadly reflected and eventually persistently surpassed the value of business working capital and book value. Buffett later also heeded the advice of Philip Fisher and Charlie Munger, both of whom were instrumental to his pivot away from “cigar butts” to “wonderful businesses at fair prices”. These include some of his legendary investments such as Coca-Cola, See’s Candies, GEICO, Gillette, etc.

For the longest time, it was an indisputable fact that investing in companies with business moats and long reinvestment runways was a superior strategy to investing in cigar butts. This was only further cemented by the rise of Internet companies, who represented such moats to a T, and eventually became the Tech megacaps of today. It remains arguably true even today that such companies represent the best types of businesses, all else being equal.

However, not all else is equal. Just as the “cigar butt” style stopped being a reliable strategy all those years ago — once markets warmed up to it and arbitraged away excess returns from buying businesses below working capital value — so to has the “wonderful business” style arguably become less relevant amidst the widespread recognition by markets of the advantages of businesses with superior moats. And while strictly unrelated, the proliferation of index funds and widespread implementation of QE by global governments have also contributed to bidding up the valuations of such “moaty stocks” (which tend to occupy the top spots of stock indexes), thus further handicapping excess returns from acquiring shares of such “wonderful businesses” in efficient markets.

How is this relevant to the topic of portfolio concentration? Well, obviously portfolio concentration only makes sense when it involves exclusively “wonderful businesses”. What’s the point of having a portfolio composed of just 1-5 cigar butts? For a concentrated portfolio to make any sense at all, it clearly needs to be composed exclusively of stocks representing “wonderful businesses”.

Herein lies the problem. What’s the point of having a concentrated portfolio of “wonderful businesses at expensive prices”? While it certainly remains possible to find such stocks that are undervalued (e.g. Meta in late-2022), opportunities for excess returns in such stocks only tend to appear precisely when the narrative surrounding them becomes “they’ve lost their moats” (i.e. disrupted) — thus rendering the entire point of investing in “moaty businesses” irrelevant. For instance, you’d have to not care about moats at all to have bothered with Meta in late-2022.

If so, the logical corollary would be that a concentrated portfolio of such “wonderful businesses” has also stopped automatically being the superior choice, as compared to a diversified portfolio. To be clear, I’m not saying that the reverse is true — i.e. that a diversified portfolio has automatically become superior to a concentrated one given recent market developments. I’m just saying that due to the aforementioned arbitrage phenomena of “wonderful business” stocks in particular, the dilutive impact of higher prices on the shareholder returns of a concentrated portfolio of “wonderful businesses at expensive prices” has rendered such concentrated portfolios less invincible than they used to be.

This dilutive hit to shareholder returns has arguably reached a point where even a diversified portfolio of “less wonderful businesses at more wonderful prices” — or even a diversified portfolio of the same “wonderful businesses” — could end up leading to superior LT yields from a portfolio perspective. Anyone who understands macroeconomics, geopolitics, market history and their attendant impact on future market prices (and excess returns) will tell you the same.

This sets the context for why the New Normal has likely transformed into diversified portfolios possessing a competitive advantage over concentrated portfolios over the next generation of value investing. In this article, I’ll try to comprehensively justify why I think so. TL;DR: It’s not your grandpa’s (Buffett) stock market anymore.

Diversified > Concentrated Portfolios in Modern-Day Markets

Aside from the aforementioned “wonderful businesses at expensive prices” phenomenon undercutting excess returns of concentrated portfolios in modern-day markets, diversified portfolios do offer many other legitimate advantages in comparison:

1. Diversified portfolios are less subject to volatility (i.e. perceived risk), and therefore knock-out risk. This can lead to a reduced ability of giving LT theses the opportunity to play out to their full intended extent.

   1. For instance, someone with a 3-stock portfolio would see their investment net worth dive by 15% if just one position experiences 50% downside volatility — which as the past few years have shown us, is utterly plausible. This can have consequences external to the portfolio, e.g. business going concern, sleepless nights.

2. Diversified portfolios allow more positions, and therefore a higher probability of success in any given position.

   1. For instance, a 3-stock portfolio which gets 1 of 3 positions right would have the same upside probability distribution as a 20-stock portfolio which gets 6 of 20 positions right. Given violently uncertain macro environments, the latter scenario has a far higher chance of occurring at any given time — which is important in an industry where the best practitioners only have a 60% hit rate.

   2. George Soros’ quote (paraphrased) — “It’s not about whether you’re right or wrong that matters, but how much you make when you’re both right and wrong” — implies that probabilities matter as much as outcomes in terms of final investment returns. Diversified portfolios deliver much more optimized portfolio probabilities, which make much more sense in the context of infinite uncertain futures (as opposed to 100% certain forecasts).

   3. This is doubly true in the short-term, where it is far more likely for all 3 stocks of the 3-stock portfolio to be down in any given year as compared to all 20 stocks being down in a 20-stock portfolio. Once again, this can have attendant consequences external to the portfolio.

   4. Buffett has a famous quote, “Diversification is protection against ignorance. It makes little sense if you know what you are doing.” The implication here being that if you’re right on all of your positions, why bother with nothing but your best ideas? On the other hand, how sure are you about being right? (on any given position) In the context of extreme macro uncertainty, diversification remains the best protection against ignorance.

   5. In an industry where downside volatility is often described as “2 years or out”, there are hugely legitimate reasons in certain cases to have a more diversified portfolio.

3. Macro Doesn’t Matter… Until It Does. On one hand, it’s true that good businesses run by good operators will likely deliver good performance over the long-term, independent of macro factors. On the other hand, that’s not the same as saying that you can just draw a straight line from today to positive results in 5 year’s time as long as those criteria are met.

   1. Good business operators are good precisely because they actively recognize that macro matters, and take proactive steps to manage uncertainty stemming from macro. They don’t do it by sticking their heads into the sand and pretending that macro doesn’t exist.

   2. While a properly constructed 2-stock portfolio (e.g. negatively correlated in every possible way) could theoretically withstand outsized volatility, a “just do it” portfolio with 2-3 stocks is unlikely to handle macro uncertainty well. The past 3 years of macro volatility is ample proof of that (without the benefit of hindsight) — this is before we even get into any outright macro shenanigans like QE.

   3. While there are certainly concentrated portfolios which have succeeded spectacularly (e.g. Nick Sleep), history is also littered with the carcasses of concentrated portfolios which have not (e.g. Bruce Berkowitz). If we consider the full dataset of portfolio managers running concentrated portfolios, the jury is still out on whether concentrated portfolios are 100% absolutely superior to more diversified portfolios. This is unlike say, the conclusive time-tested evidence for LT fundamental approaches being superior to ST trading approaches.

   4. The only way I can see a “just do it” portfolio of 3-5 stocks working out is if those “wonderful businesses” were acquired at significantly below fair value. Unfortunately for moat advocates, those types of share price opportunities only appear in “wonderful businesses” precisely when their moats are widely perceived to have disappeared (e.g. Meta in late-2022). This is precisely when most people run in the opposite direction.

4. Diversification protects against blind spots. Whether within a single position or at the portfolio-level, any investor’s biggest risks are their own blind spots — i.e. what you don’t even know you don’t know, or “ignorance” as Buffett puts it above. Diversification provides an ample buffer even against blind spots, simply by virtue of how margin of errors/safety act as a broad risk buffer against anything and everything (at the expense of efficiency).

To offer some credibility that diversification as a superior methodology falls well within the value investing status quo, consider the investment approaches of the following two famous value investors. Buffett’s Rule No. 1 has always been to Never Lose Money — he in fact reiterated this point in Berkshire’s recently published annual report:

“One investment rule at Berkshire has not and will not change: Never risk permanent loss of capital.”

Also, Peter Lynch rose to fame by practicing a highly diversified portfolio of equally “wonderful businesses” in his Magellan Fund at Fidelity. These are value investors who have practiced both having a diversified portfolio and investing in “wonderful businesses” — the two don’t have to be mutually exclusive.

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.

Not Investment Advice. Read Disclaimers.

TABLE OF CONTENTS:

1. Retained Earnings = Cumulative Lifetime Investment by Shareholders

2. ROE = Shareholder yield

3. Earnings Yield = True shareholder yield

4. Tying it all together: How a Stock Investment = a Business Investment

5. Value Investing = Picking Stocks Like Billionaires

6. What "15% CAGR Over 5 Years" really means

Many people ask (rightfully) how there is even any relationship at all between their stock market purchase and directly investing into the business whose stock they are buying (e.g. Apple) — besides through dividends or at the IPO stage. When you buy a stock of a company on public markets, your funds do not get “invested” directly into the company, but rather go to some 3rd party instead. If so, how can we truthfully call our stock purchase “investments”?

This lack of transparency makes it difficult for many buyers of stocks to subscribe to the idea of being business owners, since they cannot directly relate their stock purchase to profits from the underlying business — other than through arcane financial formulas and dividends. And since value investing proclaims to be all about investing in the long-term prospects of the underlying business — rather than trading paper profits — I think this is an extremely fair question.

In this article, I will satisfactorily address how value investors are indeed business owners by using highly objective financial data to demonstrate how your funds flow directly into the underlying business when you purchase its stock. We will also see how value investors view themselves as participating directly in the profits of the underlying business. In other words, we will see with utmost clarity what it means to be a value investor.

Retained Earnings = Cumulative Lifetime Investment by Shareholders

Summary:

Scenario 1:

1. Net Profit -> Retained Earnings (RE)

2. RE - dividends paid = RE less dividends

3. Same dividends reinvested back into company by same shareholders. Company issues new shares in exchange for investment = Share capital+

4. End result: Share capital+ and RE- but no difference to Total Equity


Scenario 2:

5. If company never paid dividends, same end result to Total Equity.

6. Only difference is dividend amounts remains in RE, instead of being moved to Share capital.


Conclusion:

8. Most of Total Equity = RE = Cumulative lifetime investment by shareholders

To begin, let’s set some context. Most people are familiar with how a company’s annual Net Profits flow to Retained Earnings on the company’s balance sheet. After deducting dividends paid, the remainder of Retained Earnings are reflected in the following year’s balance sheet. Hence, the Retained Earnings of a company represents its cumulative Net Profits after dividends since its inception.

The Retained Earnings of most mature businesses (e.g. Apple, Disney, Nvidia) represents the bulk of Total Equity or Book Value. The value of any Share Capital that had been issued at its IPO >20 years ago tends to be completely obscured by the cumulative Net Profit after dividends generated by the company over those 20 years. Hence, for argument’s sake, we can say that a company’s Retained Earnings represents most of its Total Equity or Book Value.

Why is this important? In business cash is king — so think about what those Retained Earnings represent in cash terms. As we saw earlier, the Retained Earnings of a company represents all cumulative Net Profits after dividends since the company’s inception. While Net Profits are not strictly cash in nature, they do represent cash profits as long as there isn’t any fraud going on. This is why over the long term, a company’s Cash Conversion Ratio (NP/OCF) should average at around 100%, otherwise it’s a red flag.

Dividends are clearly paid out in cash. When they are paid, those dividend amounts are deducted as a double entry from both Retained Earnings and Cash & Cash Equivalents on the company’s balance sheet (Dr Retained Earnings, Cr C&CE). Hence, when we say that the Retained Earnings of a company represents all its cumulative Net Profits after dividends since the company’s inception, it simply means that Retained Earnings represents all the cumulative cash profits belonging to shareholders that have been reinvested back into the company.

Example: Let’s say a company has a 100% dividend payout ratio, i.e. it pays out all of its annual Net Profits as cash dividends. In that case, its Retained Earnings would persistently be zero (assuming no losses). The average Net Profits of that company over the long-term can also be likened to the interest of a fixed income instrument (e.g. 5% US Treasuries).

In the above scenario, the company pays out all of its annual profits as dividends every year. However, when a company has profitable opportunities to pursue, shareholders might opt instead to plow those “interest payments” back into the business, in pursuit of growth. Those related cash flows would subsequently be used to acquire new assets for the business, which naturally would be expected to increase future Net Profit.

In cash flow terms, this could be likened to if the company had paid out all of its Net Profits as dividends every year — but subsequently took back those cash dividends as share capital, by issuing new shares to the same shareholders in order to reinvest those dividends back into the business. In this scenario, those reinvested profits would be reflected under Share Capital.

However, if it hadn’t paid those dividends and simply held onto the cash instead, those amounts would simply remain in Retained Earnings. However, they would make zero difference to Total Equity/Book Value (or cash flow) as compared to if the company had simply decided not to pay dividends and reinvested those profits back into the business instead.

Hence, the Retained Earnings amounts on a company’s balance sheet represents the share of Asset value contributed by shareholders over the entire life of the company. In other words, they represent the cumulative lifetime investment by shareholders into the company.

If you really think about it, this is also why we call Total Equity = Net Assets. As noted earlier, such cash flows in the business are reinvested into the business’s assets. After netting off liabilities, Net Assets represent the identical cumulative amounts reinvested by shareholders into the company.

ROE = Shareholder yield

Of course, just knowing that the Retained Earnings of a company represents the cumulative lifetime investment by shareholders into the company doesn’t tell us much in isolation. What matters to investors is understanding its role in determining shareholder yield, i.e. ROE.

ROE = Net Profit/Total Equity. Its real-life implications are easy to understand in business terms — it’s simply the annual Net Profits divided by the lifetime cumulative investment by shareholders. Hence, it represents shareholder yield.

Given the context above, we can see how ROE is comparable to the interest yield of a fixed income instrument (e.g. 5% yield of US Treasuries). A company’s LT average ROE should approximate the shareholder yield of the business. Hence, we can directly compare the opportunity cost between the shareholder yield of a business (e.g. 5% ROE) and the interest yield of US Treasuries (e.g. 5% YTM). The investment with the higher yield is more profitable, form notwithstanding.

Earnings Yield = True shareholder yield

Now that we have established that a company’s ROE represents its shareholder yield, we are ready to take the next step towards understanding how a stock purchase represents a direct investment into the underlying business.

At this point, most people can agree that ROE represents shareholder yield at the business level. However, that doesn’t equal shareholder yield at the shareholder level. For example, there are many businesses with triple-digit ROEs (e.g. Apple’s 150% ROE in FY23) — yet it clearly does not reflect the actual shareholder yield for those who acquire Apple’s shares on public markets. What gives?

This expectations gap can be explained by the fact that those shares are being acquired on public markets — rather than a direct investment into the business assets at their legacy values. When you acquire Apple shares on the NASDAQ, you are not paying their Book Value price. Rather, you are usually paying a significant premium to Book Value to acquire their shares, as represented by the Market Cap. This market premium is reflected in the P/B ratio of the company, e.g. Apple’s trailing P/B = 35x.

At the end of the day, it doesn’t really matter what form that investment takes — what actually matters for shareholder yield is the price paid. When you buy Apple’s shares at 35x P/B, you are effectively diluting your ROE by 35x as well. ROE represents shareholder yield, hence if you pay 35x Book Value instead of 1x, your “true ROE” is reduced by 35x. The official term for this “true ROE” is simply the Earnings Yield, which itself is simply the inverse of the PE ratio.

Hence, we can see how the Earnings Yield represents “true” shareholder yield for shareholders that acquire a business’s shares on public markets — in contrast to one who had invested directly into the business all those years ago. But circling back to our original question — how does that stock purchase of Apple shares on public markets equal a direct investment into Apple’s business?

Summary:

1. ROE = Net Profit / Total Equity

2. ROE = Shareholder yield

3. P/B = Market premium

4. ROE / P/B = Earnings Yield (inverse of P/E)

4. Earnings yield = "true" shareholder yield

Tying it all together: How a Stock Investment = a Business Investment

Now that we’ve established the aforementioned 3 concepts, we can jump back and forth between them to explain how acquiring Apple’s shares on the NASDAQ represents a direct investment into Apple’s business.

As we’ve noted above, the Retained Earnings of a company represents the cumulative lifetime investment by shareholders into the company. When you acquire Apple’s shares on the NASDAQ at their Market Cap value (e.g. $2.6T), you are simultaneously paying for:

1. the value of their Net Assets/Total Equity/Book Value;

2. the market premium as represented by their P/B.

Example: Apple’s latest Book Value is worth $75B, however their Market Cap is worth $2.6T or $2,600B. Hence, when you pay their Market Cap of $2.6T to acquire their shares, you are simultaneously paying for both their Book Value of $75B + market premium of $ 2,525B ($2,600B - $75B) — with the latter “spread" being represented by their 35x P/B.

Why do I segment their Market Cap into two parts this way? It is to make a clear distinction between the amounts which you are investing directly into Apple’s business vs. the amounts which you are not.

Their Book Value of $75B represents your direct investment into Apple’s business, when you acquire their shares on the NASDAQ. This is because when you buy Apple shares on public markets, you are effectively liquidating an existing shareholder’s investment capital and replacing their invested CAPEX amounts into Apple’s business. Hence, this Book Value represents the amounts directly invested into Apple’s business.

However, Apple’s Market Cap of $2.6T that you are paying to acquire their shares on the NASDAQ also includes a substantial $2,525B worth of “non-Book Value” amounts. As we’ve noted earlier, these amounts are reflected in their P/B ratio. These market premium “spread” amounts are not direct investments into Apple’s business. Rather, they represent the market premium that you are paying to participate in Apple’s future profits. This market premium/discount exists since these future profits involve uncertainty — in contrast to historical ROE which has zero risk, and therefore is priced efficiently.

In essence, if you are willing to buy Apple’s shares at 35x BV, it simply means that you are willing to accept 34x less in shareholder’s yield than the actual business yield (e.g. 150% ROE / 35x BV = 4.3% Earnings Yield). For instance, this could be because you think that their current Earnings Yield can continue growing in the future to justify that P/B market premium.

This is why we say that a company’s fair value (e.g. NPV) is represented by its future discounted cash flows or future earnings. Few will disagree that a company can command fair value relative to its current shareholder yield or ROE. However, it is the business’s future discounted cash flows, which embody future uncertainty, that commands a much more subjective market premium to Book Value. Nonetheless, it doesn’t take away from how “true” shareholder yield can be represented by Earnings Yield.

Summary:

1. Market Cap = Book Value + Market Premium (P/Bx)

2. Book Value = Amounts invested directly into the business

3. Market Premium (P/Bx) = Amounts representing future uncertainty; are not invested directly into business

4. NP/Market Cap = Earnings yield = "true" shareholder yield

Value Investing = Picking Stocks Like Billionaires

With these concepts in place, we are finally ready to tackle the topic of determining shareholder yield from a value investor’s perspective.

As widely recognized, value investing proclaims to be about investing directly into the underlying business, rather than simply trading paper profits. So how do we as value investors determine whether we are getting an adequate shareholder yield from our investee businesses — e.g. 15% CAGR over 5 years?

The common approach to thinking in terms of shareholder yield is capital appreciation, i.e. the upward movement of stock prices. Having said that, as value investors we are more concerned with business yields. So how do we square between capital appreciation and business yields with respect to measuring shareholder yields from a value investor’s perspective?

Consider how a businessman thinks about shareholder yields — they’d typically just think of it as ROIC, or payback period. If I invest $100 into a business and get an annual profit of $15, then I generate a 15% return (payback period of 6.6 years). However, I may also be willing to entertain a lower return in year 1 (e.g. 5%) if I think those profits can grow in the future, to eventually equal a LT average return of 15%.

Importantly, we are describing 15% CAGR from the perspective of the initial investment capital — not the earnings growth of the business. The focus here remains shareholder yield, not profit growth per se. Earnings growth is simply one function of the calculation of shareholder yield. Hence, value investors interpret 15% CAGR returns from the same perspective as businessmen — which is entirely logical, since value investors actually do think of themselves as business owners.

As we’ve expounded on above, value investors interpret shareholder yield as Earnings Yield. Therefore, when a value investor says that they’re aiming to earn 15% CAGR over 5 years, they do not necessarily mean it in the context of share price capital appreciation — which can be a matter of share price volatility. Rather, value investors genuinely intend to earn 15% CAGR as a matter of Earnings Yield from the underlying business profits — similar to how a businessman thinks about shareholder yield. The corollary is that value investors truly treat their investment capital as “investments”, rather than simply “renting” shares for a quick flip.

This example is easier to illustrate if you think about stock investments from the perspective of a billionaire. As a billionaire, it can be difficult to find sufficiently large private businesses to invest in which can absorb all of your available capital — hence, it makes sense to look for business returns in public markets. If a billionaire feels that getting 5% returns from investing in US Treasuries isn’t adequate, he might be willing to invest in a listed company with higher risk for 15% returns. In this case, he’d be treating his stock purchase as a business investment — in the same way that value investors would.

What 15% CAGR over 5 Years really means

This also explains why value investors tend to gravitate towards relatively cheaper multiples. Whether in value investing, private equity or vanilla business M&A, by far the largest lever determining your investment yield is the acquisition price. A low acquisition price can offset lower business earnings growth for years; whereas a high acquisition price can likewise offset higher earnings growth for years. And since there is typically a direct relationship between growth and price, you can see how it is not one or the other which matters more, but rather the relationship between growth and price (alá growth:price ratio).

In private markets, this growth:price ratio is usually quite efficient, and therefore the chances of mispricings occurring is quite minimal. Luckily for value investors, Mr. Market tends to offer mispriced opportunities on a relatively regular basis. This is not to say that such opportunities are immediately obvious to everyone — those get arbitraged away quickly — but anyone with a keen eye and deep analytical ability can testify to how surprisingly regularly they appear in public markets.

Of course, this is not to say that capital appreciation doesn’t matter in stock markets — after all, what more objective way is there to measure performance than by observing market prices? Fortunately, efficient markets tend to accurately arbitrage a business’s Earnings Yield by raising its share price in public markets. Hence, a 15% Earnings CAGR at the business level tends to also be reflected as a like increase in its LT share price, ex-volatility. Over the course of a full market cycle (e.g. 5 years), there are usually ample opportunities for efficient markets to reflect improving business performance via a like capital appreciation in its share price.

However, it remains crucial to observe the distinction between 15% CAGR from capital appreciation, and 15% CAGR from an Earnings Yield perspective. The latter is almost always part of the former, but the former is not necessarily the latter (due to volatility) — just like how a chicken is always a bird, but a bird is not necessarily a chicken. While public accountability over performance will always be important, at the end of the day value investors interpret shareholder yield as a matter of Earnings Yield, not capital appreciation per se.

Hence, the value investor’s interpretation of “15% CAGR over 5 Years” simply means to look for businesses which can deliver enough earnings growth relative to their acquisition price to generate an effective shareholder yield of 15% over a full market cycle. Crucially, this focus on yield rather than price activity means that it is not just underlying business growth that matters — the acquisition price matters too.

Disclaimer: This document does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein or of any of the authors. To the best of the authors’ abilities and beliefs, all information contained herein is accurate and reliable. The authors may hold or be short any shares or derivative positions in any company discussed in this document at any time, and may benefit from any change in the valuation of any other companies, securities, or commodities discussed in this document. The content of this document is not intended to constitute individual investment advice, and are merely the personal views of the author which may be subject to change without notice. This is not a recommendation to buy or sell stocks, and readers are advised to consult with their financial advisor before taking any action pertaining to the contents of this document. The information contained in this document may include, or incorporate by reference, forward-looking statements, which would include any statements that are not statements of historical fact. Any or all forward-looking assumptions, expectations, projections, intentions or beliefs about future events may turn out to be wrong. These forward-looking statements can be affected by inaccurate assumptions or by known or unknown risks, uncertainties and other factors, most of which are beyond the authors’ control. Investors should conduct independent due diligence, with assistance from professional financial, legal and tax experts, on all securities, companies, and commodities discussed in this document and develop a stand-alone judgment of the relevant markets prior to making any investment decision.