Why Value (factor) Investing > Growth (factor) Investing
My 2nd primer on Value Investing - and how investing in Value Factor stocks helps you sleep better when investing in Emerging Markets (e.g. ASEAN)
If heightened uncertainty in the short-term means that it is practically impossible to determine the future trajectory of share prices, then the answer is simple - only invest in stocks where all possible future outcomes are favorable!
For the purpose of visualization, this nearly 7,000-word article is divided into 6 chapters:
Chapter 2: How Contemporary Financial Methodologies Fail To Capture Heightened Uncertainty
Chapter 5: (Stock Market) History Is Written By The (Stock Market) Victors
Chapter 6: Why Value (factor) Investing > Growth (factor) Investing
Chapters 1, 2 & 3 set the context for the topic at hand, Chapters 4 & 5 provide the investment objective and its justification, and Chapter 6 explains how investing like this achieves the investment objective.
(The above links to jump to the relevant chapters will only work in Google Chrome. If you’re using a different browser, simply scroll to the relevant chapters below.)
Summary
Contemporary financial methodologies like the DCF model and VaR fail to acknowledge the presence of heightened uncertainty in markets - and using statistical procedures to estimate market outcomes without recognizing their limitations can be lethal.
The DCF model attempts to estimate a company’s valuation through the forecasting of future cash flows - which makes the false underlying assumption that there can only ever be one possible future, and that management has reasonable control over securing business outcomes. Nothing could be further from the truth.
In hindsight, it is difficult to distinguish between a skillful investor and a lucky investor. But there is a litmus test - a lucky investor will claim to have known all along what today’s share prices would be, while a skillful investor will admit the existence of heightened uncertainty in markets and then explain how he worked around it.
An investor of superior skill is not one who knows how to forecast future share prices. Rather, he is one who admits that he doesn’t know how to forecast future share prices - but can articulate how he still manages to achieve his investment objectives despite it.
Stock market history is written by the stock market winners - hence the only acceptable investment strategy is to ensure that all possible future investment outcomes are favorable. The only way to do this consistently is to aim to Don’t Lose Money.
Investing in Growth Factor stocks leaves one exposed to valuation risk - while investing in Value Factor stocks is capable of fulfilling the necessary criteria of ensuring that all possible future investment outcomes are favorable. Because of this, investing in Value Factor stocks is superior to investing in Growth Factor stocks as a category.
When investing in Emerging Markets (e.g. ASEAN), investing in Value Factor stocks is the better approach as it is able to mitigate the existence of heightened uncertainty.
If you’ve read my earlier article about Value Investing (linked below), you’ll know what I mean when I say that Graham’s and Buffett’s original definitions of the term “Value Investing” has been distorted by contemporary finance to mean something else entirely:
The original meaning of “Value Investing”, as coined by Graham and Buffett, simply means to buy something for a price less than its value - i.e. investing in value. However, contemporary finance has embraced a divergent popular definition of “Value Investing” in what the industry calls the “Value Factor” - which is broadly defined as investing in stocks with low earnings multiples (e.g. P/E, P/B, EV/EBITDA).
This is because most of the “value investments” performed by Graham and early Buffett happened to be stocks which exhibited these low earnings multiples traits. This practice of investing in stocks with low earnings multiples is often contrasted with its opposing brethren of investing in stocks with high earnings multiples, which the industry endearingly terms the “Growth Factor”.
However, the definition of value investing as it was originally coined does not exclusively encompass the realm of investing in stocks with low earnings multiples - as evidenced by Berkshire’s relatively recent entry into Amazon and Snowflake. Even a “growth factor” stock with eye-popping earnings multiples like Snowflake can constitute a value investment - as long as its intrinsic value is significantly higher than its investment cost.
Hence, when I say that “investing in Value Factor stocks is better than investing in Growth Factor stocks”, I do not mean that “Value Investing is better than Growth Investing”. Both value factor stocks and growth factor stocks can represent Value Investing. I just literally mean that Value Factor stocks are more likely to outperform than Growth Factor stocks over the long-term, ceteris paribus.
Now that we’ve gotten these pesky definitions out of the way, let’s return to the topic at hand: Why investing in Value Factor Stocks is better than investing in Growth Factor stocks.
Chapter 1: Heightened Uncertainty & Lack of Control
When an investor is graded on his investment performance, we tend to look back at his historical performance and assess how well he foresaw the future share price trajectory of his chosen stock. The underlying assumption here is that the investor was capable of predicting with a high level of certainty which stocks would outperform in the future, utilizing their superior analysis of markets and business fundamentals. Indeed, that’s basically the underlying framework of the DCF model, the gold standard of the industry’s valuation framework - which assumes that an astute investor is capable of determining what a company’s intrinsic value is likely to be by forecasting its future cash flows.
Contrast this with how an entrepreneur who intends to sell his business thinks about the valuation of his business. Sure, he has a gut feel of what his future revenues and profits might look like based on his business’s historical performance, but he doesn’t even begin to try and nail down the range of profits he might earn in a particular year. For instance, when WhatsApp’s founders sold their business to Facebook for a cool $16 billion in 2014, the company hadn’t even begun generating revenue (much less profits) - and it would have been nigh impossible to even begin to harbor a guess at what their profits in 2020 might be.
Now some might point to that particular example being a fringe case (since most selling businesses do tend to have some revenue), but it does represent a typical example of how entrepreneurs think about the valuation of their businesses. Far from exclusively trying to predict the future cash flows of their businesses in a mechanical fashion, they tend to explore a broad spectrum of qualitative factors in their estimation of their company’s valuation ranging far beyond simply the domain of financial considerations - e.g. whether such an opportunity might arise again, what their regrets might be if they didn’t sell now, what the scenario analysis might look like if the winds turned in/against their favor, whether they could reinvest the liquidated capital at a higher rate of return, etc. Notably, they are preoccupied with all the things that could go wrong (i.e. eliminating downsides) rather than maximizing upsides - with a heavy focus on managing outcomes with high uncertainty (as they can’t make accurate estimations on these).
Now let’s circle back to how the DCF model approaches the valuation exercise. Firstly, the DCF model is 99% preoccupied with estimating the upside - the only downside consideration is an afterthought which involves raising the discount rate in an arbitrary fashion. This discount rate tends to be a WACC formula that is contingent on a cryptic cost of equity formula - which is itself dependent on an ambiguous beta formula that most industry practitioners can’t even articulate what it represents in real-life. Fortunately for you, I have unpacked all this (and more) in my essay-long rant about the outdatedness of the CAPM as a measure of cost of equity, laid bare in all its gilded glory below:
With more complexity comes more possible points of failure, and this is the case for the WACC formula as it is for anything else. The way the DCF model accounts for risk is to increase the discount rate represented by the WACC; and it so happens that changing the WACC by just 1% can result in a completely unrelated valuation - rendering the entire exercise of forecasting cash flows bunk. This is the blunt instrument equivalent of trying to bludgeon a nail into a wall with a sledgehammer - and we haven't even gotten into all the other similar weaknesses of the DCF model yet (e.g. estimating terminal value).
Secondly (you thought I was done?), the utilization of the DCF model assumes the existence of certainty - i.e. that future revenues, costs and profits can be estimated with a reliable amount of precision, or at least within a reliable range of outcomes. The underlying assumption here is that a reasonable amount of control exists - that as long as management fulfills their fiduciary responsibilities, they are completely capable of achieving predetermined outcomes - i.e. “if there’s a will, there’s a way”.
Anyone who has ever run a business can tell you that this is a complete fantasy - there are simply way too many factors outside management’s control to even hazard a guess as to what the future might look like, even as little as 12 months down the road. This results in a heightened level of uncertainty which significantly broadens the potential range of future outcomes that any single business might experience. Try entering figures into a DCF model where every single input could potentially sway 50% either way after 12 months - you might as well throw the entire valuation model away, and throw a dart instead.
In summary, the way most entrepreneurs approach valuation is through a Risk framework (rather than a Reward framework) - where heightened uncertainty and a lack of control exists; and hence the valuation exercise is preoccupied with estimating and mitigating the downside, in contrast to maximizing the upside. Very few businessmen will confidently estimate what their business should be worth in a disposal and try to shoot for the top dollar - their thought process will be constantly flitting back and forth between the various downsides of both the sell/don’t sell scenarios, with visibility of the future constantly blurred by a fog of uncertainty. Rather than trying to pin down the highest absolute value from selling their business, they will be trying to minimize the potential regret from all scenarios, with the entire decision framework being summarized as one of Risk Tradeoff - i.e. a risk:reward framework, in contrast to an exclusively reward framework.
Again, it bears repeating that the only reason why they bother with all this trouble in the first place, is due to the existence of Uncertainty - the presence of a wide range of possible future outcomes with probabilities too small to be able to estimate with statistical usefulness. It is here that we begin to understand the importance of managing Risk, in its application to stock markets.
Chapter 2: How Contemporary Financial Methodologies Fail To Capture Heightened Uncertainty
Let’s circle back to what we were referring to earlier about how a stock market investor is typically graded on his investment performance. The way we typically judge whether someone is a good investor or not is by assessing what his historical performance was like over a certain time period - with the unspoken assumption being that his ability to attain his current performance is entirely contingent on their skill. This assumption is so ingrained in our institutional consciousness that we even have a name for it - alpha, or the portfolio return attributable to an investor’s skill alone.
However, recall what we said earlier about uncertainty? The thing about daily fluctuating share prices, is that they are influenced by so much more than just what is within the control of the entrepreneur. While it is true that over the long-term, some degree of certainty can be had that share prices will eventually reflect intrinsic value (due to extrinsic factors cancelling themselves out via destructive interference) - predicting future share prices within any time period shorter than 5 years (i.e. the shortest reasonable period for one full market cycle) is as good as a dice roll. Just ask the people who were invested in China Big Tech last year, or in airlines prior to the pandemic.
To be fair, the industry does account for these types of uncertainties - for outcomes with statistical probabilities which are too small to be materially useful - through the concept of “tail-risks”. The “tail” here refers to the tails of the bell curve (i.e. normal distribution) where outcomes with extremely low statistical probabilities materialize, typically expressed via a standard deviation figure - e.g. an outcome with a probability of occurrence within one standard deviation of the mean has a 68.27% chance of happening, while that within three standard deviations of the mean has a 99.73% chance of happening (i.e. near-certainty).
This statistical framework is embodied in its financial equivalent - the Value-at-Risk (VaR) framework. The VaR basically represents the inverse of the normal distribution, where the amount of invested capital at risk is represented by 100% less the probability of the upside event materializing - e.g. if the chance of upside is within three standard deviations of the mean, that means the VaR is estimated at the total amount of capital invested multiplied by (100% - 99.73% = 0.27%), typically a negligible amount.
On the surface, this might seem like an exceedingly logical way of approaching the estimation of risk - figure out what your maximum downside exposure might be. However, the problem arises when you have multiple possible future outcomes laid out before you - but only one will actually materialize. How would you go about estimating the VaR if there are 100 possible future outcomes, and you don’t know exactly which one will happen?
The way many industry practitioners address this is by trying to aggregate the VaR from all possible outcomes. That is to say, if Risk Scenario A has a VaR of -$10 and Risk Scenario B has a VaR of -$20, then we average the two values to obtain an aggregate VaR amount of -$15. Or we perform a Monte Carlo analysis on a computer which attempts to run through every single possible outcome a million different times to increase the output’s statistical relevance - and basically do the same thing.
Then we plug that figure into some risk input in our valuation model - and then proceed to forget about it forever while we concentrate on estimating the next input, regardless of whether those inherent assumptions continue to hold true or not for all subsequent calculations.
Investors who were long US real estate found out about the weaknesses of the VaR method the hard way in the aftermath of the 2008 Global Financial Crisis (GFC), when the nationwide collapse of the US housing industry materialized despite being a 5-sigma event - i.e. 1 in 3,488,555 chance of happening (0.00003%). These investors who had adopted a false sense of assurance from the fact that there had never been a nationwide collapse of the US housing market since the country’s Independence, suddenly realized far too late that their aggregation of maximum loss exposures from a 5-sigma event into an average statistical VaR figure, led to their aggregate VaR estimations being woefully inadequate. The statistical gods had failed them, but still demanded their sacrificial lambs.
Of course, all this seems obvious with the benefit of hindsight. But if you were an investor in 2005 prior to the GFC (when Michael Burry first bet against the US housing market), the likelihood of a simultaneous nationwide collapse of the US housing industry would have seemed as remote as the end of the world happening in 2012 - as predicted by the Mayan calendar.
And that’s exactly the problem with aggregating VaR amounts - it pretends that the outcome of a low probability risk event materializing is somehow related to its low likelihood of occurrence. When in actual fact a $1 billion loss is a $1 billion loss - probabilities be damned.
This is exactly what I meant earlier when I discussed the concept of Uncertainty - defined as an outcome where the probability of occurrence is too small to be statistically meaningful. When there is too much uncertainty obscuring your view of the future, it renders traditional estimation methodologies which rely on the having the benefit of hindsight worthless.
Keep this definition of Uncertainty in mind going forward, as we’ll be diving beyond the mainstream and into PhD territory now.
Chapter 3: Is It Skill… or Luck?
Let’s circle back to what we discussed earlier about how we grade an investor’s performance - by looking at how their chosen stocks have performed over a certain period in the past. The underlying assumption here is that the investor was able to predict the share price’s future trajectory at the time he made the investment - through his superior skillfulness. Therefore, the investor who outperforms the most is regarded as the most skillful investor.
There are several problems with this narrative. First of all, as we’ve seen above, the crystal ball revealing the future is perpetually obscured by fog - resulting in heightened levels of uncertainty, which cannot be offset by skill alone. One comprehensive way the industry refers to this phenomenon is Macro - i.e. macroeconomic events represented by portfolio beta exposure. These are the systematic risks which affect all portfolios equally - e.g. inflation, interest rates, central bank policy, geopolitical developments, etc.
It is widely acknowledged that trying to be a consistently successful pure macro investor is a fool’s errand - many intelligent people have tried, and the number of them who can actually boast decades-long outperformance in macro investing over the past century can probably be counted on your fingers and toes.
The reason for this is because there are just way too many moving parts in Macro; and if that’s not enough, each of those moving parts dynamically affect each other - e.g. inflation affects central bank policy, who raises interest rates to counter inflation; which affects economic sentiment, which affects unemployment; which influences central bank policy, who lowers interest rates to stimulate unemployment; but also affects inflation. So factor A affects factor B, which affects factor C, which in turn affects factor A; now multiply that by all the letters of the alphabet. This overt dynamism inherent in macroeconomics leads to both extremely volatile and extraordinarily unpredictable share prices in the short-term - and trying to predict these short-term fluctuations with precision is basically impossible, due to the heightened levels of uncertainty involved.
For this reason, the DCF model - which presumes the existence of certainty in forecasting the future outcomes of business fundamentals - is internally inconsistent with its objective. If there is heightened uncertainty regarding a particular input within the DCF model - and that input plays a significant role in estimating the final valuation output (e.g. discount rate, terminal value) - then your estimated valuation from the DCF model is basically trash. If you need empirical proof of this, look at how sell-side target prices consistently overshoot or undershoot the actual trajectory of future share prices:
The bigger issue beyond the integrity of the DCF model though, is this - if the future is perpetually clouded by uncertainty, can we really attribute an investor’s outperformance exclusively to superior skill? An empirical illustration can be found in today’s markets - if someone had made a lot of money investing in US Big Tech two years ago, would it be fair to say that they had correctly predicted that the pandemic would happen? Conversely, if someone had invested in airline stocks immediately prior to the pandemic and subsequently lost a lot of money, would it be fair to say that they weren’t skillful? Put another way, is it even possible to know which stock will outperform two years down the road, purely as a function of superior forecasting ability?
If the given investment horizon is ultra-long (e.g. a minimum of 5 years), then it might be possible to answer the above in the affirmative - since any given stock would likely have gone through at least an entire market cycle after 5 years, and a well-run business would have likely experienced at least one peak and one valley in that period (i.e. you would have at least one chance to sell high).
However, as we are well aware, many industry practitioners regularly use the DCF model to estimate 12-month target share prices. Given the heightened uncertainty inherent in Macro, how can anyone presume to be capable of precisely identifying target share prices of any given stock - in any period shorter than one entire market cycle?
And herein lies the problem: if it is impossible to precisely determine the future of any given stock’s share price in the following 12 months, and someone correctly predicts its share price 12 months later - can we really attribute that outperformance to superior skill? Or would it be more correct to attribute that outperformance to luck?
The answer - as with all things of such scale - is that it depends. If that investor is going around shouting from the rooftops about how he correctly predicted what today’s share price would be 12 months ago, he is either lying to you or lying to himself. However, if he admits that he didn’t know what the share price would be when he made that investment 12 months ago - but can articulate how he addressed the presence of heightened uncertainty in his investment framework - then you have probably found an investor of superior skill.
Chapter 4: An Investor of Superior Skill
What do I mean by this?
Consider everything we’ve discussed so far - that heightened uncertainty exists in markets; that it is impossible to precisely forecast the trajectory of future share prices in the short-term; and therefore that short-term outperformance can more likely be attributable to luck than skill. How then should an investor position himself in the short-term - especially when short-term performance has very real implications for the investor? (e.g. career, risk tolerance, branding, etc)
If heightened uncertainty in the short-term means that it is impossible to practically determine the future trajectory of share prices, then the answer is simple - only invest in stocks where all possible future outcomes are favorable!
If all possible future outcomes are favorable (within reason), then heightened uncertainty about the future no longer matters - because regardless of how the future unfolds, you’re good! A good illustration is a stock position which does well if your forecast of their future business outcomes in the short-term ends up being correct - but even if you end up making an incorrect forecast, the worst-case scenario is that you don’t lose any money.
In fact, this narrative is nothing new - and was certainly not invented by me. Here is legendary investor George Soros recommending the exact same advice:
The idea is to cover ALL your bases - so that regardless of whichever ONE from the HUNDREDS of possible future outcomes actually ends up materializing, you’ll at least still be able to attain baseline expectations. This way, you won’t have to correctly predict which of the hundreds of possible permutations in the crystal ball’s scenario tree actually ends up manifesting. A layman’s way of visualizing this is to create a DCF model for every single possible outcome; and only invest if all constructed DCF models result in a positive valuation - rather than trying to average all possible outcomes into one aggregated valuation.
It should be noted here however that black-swan events don’t count in the estimation of possible future outcomes - as it would be impossible to hedge ourselves against all unfavorable black swan outcomes (e.g. a meteor striking Earth, or the covid pandemic happening). However, since nobody else is capable of hedging against all unfavorable black swan exposure either, at the very least we shouldn’t underperform consensus if such an event should occur - and still be in a position to rewrite history to suit our own narratives.
Emeritus Professor of Finance of London Business School, Elroy Dimson, describes this phenomenon best in his following quote:
![Elroy Dimson quote: "Risk means more things can happen than will happen...](https://substackcdn.com/image/fetch/f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fc48c4a5a-d1de-4764-b808-38ca3f2262e0_850x400.jpeg "Elroy Dimson quote: "Risk means more things can happen than will happen...")
What Dimson is saying here is that the future is cloudy to the investor, making it impossible to predict exactly what will happen in the future - hence representing investment risk.
Further evidence supporting the validity of this approach can be found in the performance metric considered as the industry standard KPI - Risk:Reward; in contrast to simply Reward. If the goal was just to accurately predict which stock would go up the most within a given time period, then Reward as a KPI should suffice. But due to the existence of heightened uncertainty surrounding share price trajectories in the short-term future, it also becomes necessary to determine what possible downside scenarios might exist - and preferably, to enforce a floor beneath the maximum downside.
Another famous business mogul (and incidentally, also a former US President) also appears to agree with this advice:
What I imagine he means by his quote above, is that due to the existence of heightened uncertainty, we shouldn’t be troubling ourselves with trying to guarantee future outcomes - as long as we ensure that we don’t get kicked out of the game altogether. The general idea is that since history is written by the victors, the ideal objective is to ensure our victory no matter what - but since that is generally considered an unrealistic proposition, an alternative and much more feasible goal is to ensure that we don’t lose no matter what. We can always rewrite history later to delete any unfavorable narratives along the way.
Coincidentally, this sentiment is also echoed by another legendary investor:
As alluded to above, perhaps a more layman’s way of appreciating the wisdom behind this oft-mentioned Buffett quote is Winston Churchill’s “History is written by the victors”. I know this might sound off-topic, but give me a chance to explain how this philosophical view might be applicable to stock markets.
Chapter 5: (Stock Market) History Is Written By The (Stock Market) Victors
If we can establish that the future is unknowable no matter how much effort we put into forecasting it, then it further implies that there is no such thing as superior skill in attempting to divine our fates from the tarot cards. Hence, an investor who claims to be able to forecast what the 12-month target price of any given stock might be, is just the modern-equivalent of a caravan gypsy waving her hands over a crystal ball.
However, markets will continue to do what they are wont to do, independently of the predilections of their human participants - so even if nobody knows exactly what will happen 12 months later, something will still happen.
Here’s where things get interesting - despite the fact that we’ve established how no human investor could possibly have known what the present-day held in store 12 months prior, there are still people trumpeting today about how they managed to accurately predict last year that their chosen stock’s share price would go up. Just turn on CNBC and you’ll probably be able to hear from some of these talking heads yourself. (hint: he shares the same initials as the son of God himself)
In his quote above, Churchill describes this group of people as “the victors”. These are the investors claiming credit today for their outperforming stock ideas - despite the fact that they couldn’t possibly have known in advance how they would have performed. But because luck was on their side, they can now rewrite history to suit their narrative - as if they had known all along.
Conversely, the opposite group of people (who we’ll just call “the losers”) also similarly couldn’t possibly have known how their chosen stocks would perform in 12 months time - the only difference being that they were unlucky, in that their share prices went in the opposite direction from their predictions. As a result, they will be considered as lacking in skill by others, and nobody will afford them a chance to explain their views - hence their version of history will be overshadowed by the victors’ version.
Notably, neither side was actually able to predict in advance which way their stock prices would go - but one party was able to pretend that they had superior forecasting ability, while the other party was unable to pretend as such. Historians would therefore call what “the victors” did ‘rewriting history’ - despite the fact that they didn’t know in advance whether their chosen share prices would go up or down, they can claim credibility for it after the fact even though they were just lucky.
However, a problem arises for these “victors” when they are asked to repeat their successes in the next 12 months - they still can’t tell which stocks will outperform in the following year (just like they weren’t able to know for certain which stocks would outperform last year)! Hence, simply trying to consistently become “the victor” in the stock market is not an enduring strategy - since the victor only exists in hindsight. The fact remains that nobody on earth knows which way any given stock will go in 12 months time.
At this point, we can safely establish that since it is impossible to predict in advance the trajectory of future share prices, the only way to claim victory is to get lucky - and then rewrite history by pretending that you knew how things would play out all along. Doesn’t exactly sound like a reliable investment strategy, right?
But if we circle back to what we mentioned earlier - we actually don’t need to know what will happen in the future, as long as we ensure in advance that all possible future outcomes are favorable. By doing so, regardless of which ONE of many possible outcomes actually ends up materializing in 12 months time, we can still claim to be the victor - and then rewrite history by saying that we knew that’s what would happen all along!
The practical application of this advice is to sit tight and do nothing until you come across a stock idea which fulfills this criteria (i.e. one where all possible future outcomes are favorable). Naturally, stumbling across such a stock idea with such a demanding criteria is exceedingly rare - one might only come across one or two such stock ideas per year. But the beauty of this method is that you don’t actually have to swing when there are no favorable pitches - you can simply do nothing and hold cash until such an opportunity reveals itself. This is what Buffett meant by the following quote:
Now contrast this with market sentiment amidst the status quo, where the Fear of Missing Out (FOMO) rules supreme. The significant majority of market participants simply cannot stand to miss out on potential gains, even at the expense of potential loss - asking them to do nothing while potentially missing out on hundreds of stocks going up around them each year is a ludicrous concept to their tribe. However, such a strategy is equivalent to placing your fate in the hands of the investing gods, and sacrificing a cow or two every year.
Famed value investor Howard Marks of Oaktree Capital describes in one of his investor letters his observation about how the most successful investors demonstrate a long-term track record which dominate the top quartiles - yet only tend to occupy the second quartile of performers in the short-term. This description mirrors the outcome from the investment strategy described above - since these patient investors don’t get to participate in as many stock ideas (due to the presence of heightened uncertainty in the significant majority of them), they let many eventually performing stocks fly by them, resulting in 2nd quartile performance in the short-term. But because they also don’t experience the catastrophic losses resulting from assuming exposure to heightened uncertainty in other short-term periods, over long periods of time they tend to rise to the top ranks of performers.
Chapter 6: Why Value (factor) Investing > Growth (factor) Investing
Now that we have established the objective for how best to approach the task of investing - i.e. optimal Risk:Reward, or where all possible future outcomes are favorable - we can move on to the next step, how to implement it practically.
As we have discussed earlier, we are looking for a stock idea where all possible future outcomes are favorable. Consider a typical “Growth Factor” stock trading at high earnings multiples - e.g. ASEAN e-commerce titan SEA Ltd, which is trading at around 20x trailing P/S today:
There are plenty of legitimate ways to hedge against unsystematic risks such as sector exposure, geographical exposure or credit exposure, but there is typically only one way to hedge against valuation risk - i.e. buy puts against the company’s share price. Understandably, this doesn’t tend to be a particularly attractive way to hedge - since the options premium would have already baked in consensus expectations of the future share price, making hedging valuation risk costly (e.g. rolling puts into perpetuity).
As a result, “Growth Factor” stocks with high earnings multiples will by their very definition make it difficult to adequately hedge against valuation risk while still leaving sufficient room for upside. This leaves a loose end open when investing in a “Growth Factor” stock - which fails to meet our criteria of ensuring that all possible future outcomes are favorable (besides black swans).
The resulting risk of permanent loss of capital from valuation risk materializing while holding onto a stock trading at 20x P/S is especially real - since valuation risk is of the psychological variety, even the slightest shift in sentiment against its sector (or for any other reason whatsoever) can result in a cratering of multiples; despite negligible change to actual business fundamentals (e.g. shipping stocks recently). In contrast, business fundamentals which are tangibly rooted in the real world usually take a relatively long time to change trajectory - typically measured in months rather than days.
This is not to say that investing in a “Growth Factor” stock cannot be profitable, simply due to their high earnings multiples. The consideration here isn’t potential upside, but potential downside; we are concerned about Risk, not Reward. The past decade has amply demonstrated that “Growth Factor” stocks can continue to outperform despite their already high valuations; but that doesn’t change the fact that an investor in such stocks would have to assume the possibility of valuations suddenly and unexpectedly cratering overnight throughout their entire holding period (e.g. late-2018), with no way of adequately hedging against such a scenario.
Now consider the alternative of investing in a “Value Factor” stock - defined as a stock with low earnings multiples. Typically, such a stock would be characterized by an underlying business with poor or declining fundamentals; otherwise the share price wouldn’t reflect low earnings multiples. For this reason, the majority of market participants tend to shy away from such stocks in favor of “Growth Factor” stocks with uber-exciting future business outlooks.
However, that doesn’t necessarily mean that you can’t make money from a “Value Factor” stock. If you’ve been following my stock ideas over the past year, you’ll know that I have been a fan of AirAsia, Hibiscus and Innature - all of which would have been solidly classified as “Value Factor” stocks amidst the lockdowns of the covid pandemic last year.
Here is how each of these “Value Factor” stocks have performed YTD:
The point I’m trying to make is that you can make the same level of returns from a “Value Factor” stock as you can from a “Growth Factor” stock, despite their apparently poor fundamentals - where the upside doesn’t necessarily come from improving business fundamentals, but rather a depressingly low share price. Just as excessive optimism can lead to share prices becoming unrealistically buoyant relative to intrinsic value, so can excessive fear & uncertainty lead to share prices becoming unbelievably depressed relative to intrinsic value.
In fact, I am currently invested in a stock where the share price is currently so depressed relative to intrinsic value, that it’s truthfully hard to imagine its share price declining further even if their poor fundamentals were to deteriorate further. This is the proverbial “Margin of Safety” that we value investors just won’t shut up about:
Sign up for a 30-day FREE TRIAL to gain exclusive access to my upcoming research report about this stock - which is coming out by the end of this month!
However, the beauty of investing in a “Value Factor” stock doesn’t lie exclusively in their magnificent room for upside - but in the absolute lack of room for downside. For instance, when I recommended Innature in May 2021, the company was paying a dividend yield of approximately 4% and had nearly zero going concern risk - despite their brick & mortar Body Shop stores being forced to stay closed amidst the covid-induced government-mandated lockdown. It was honestly difficult at the time to imagine a scenario where share prices declining further wouldn’t instead improve the investment case for it (read it by clicking the link below):
Contrast this with the example of investing in a “Growth Factor” stock as I’ve provided above, and you’ll see what I mean when I say that investing in a “Value Factor” stock represents a relatively superior Risk:Reward investment case in comparison - as not only can you benefit from huge potential upside, but also put a floor on your potential downside as well! (of course, this assumes that you’ve done your homework properly)
The other bonus benefit to investing in “Value Factor” stock is that it helps you sleep better at night when investing in Emerging Markets (e.g. ASEAN)! This is because unlike investing in Growth Factor stocks, investing in Value Factor stocks is able to mitigate the existence of heightened uncertainty. In the same way that especially high valuations relative to intrinsic value represent a catch-all risk that cannot be adequately hedged against, especially low valuations relative to intrinsic value allows the investment position to tank deteriorating business fundamentals regardless of their nature.
Whether it’s idiosyncratic factors like falling profits resulting from poor management decisions, systemic factors like industry headwinds, macroeconomic factors like adverse central bank policy, or miscellaneous factors like poor corporate governance - having a healthy buffer between a properly estimated intrinsic value and the entry cost of your investment ensures that even in the worst-case scenario, you’ll always be able to observe Buffett’s advice:
In summary, a properly researched “Value Factor” stock enables the prospect of fulfilling our aforementioned investment objective criteria of only investing in a stock idea where all possible future outcomes are favorable. Since “Growth Factor” stocks are unable to adequately hedge against valuation risk, they are unable to fulfill this criteria - which makes them less attractive as a category.
Conclusion
In summary, let’s wrap up everything we’ve covered so far:
Contemporary financial methodologies like the DCF model and VaR fail to acknowledge the presence of heightened uncertainty in markets - and using statistical procedures to estimate market outcomes without recognizing their limitations can be lethal.
The DCF model attempts to estimate a company’s valuation through the forecasting of future cash flows - which makes the false underlying assumption that there can only ever be one possible future, and that management has reasonable control over securing business outcomes. Nothing could be further from the truth.
In hindsight, it is difficult to distinguish between a skillful investor and a lucky investor. But there is a litmus test - a lucky investor will claim to have known all along what today’s share prices would be, while a skillful investor will admit the existence of heightened uncertainty in markets and articulate how he worked around it.
An investor of superior skill is not one who knows how to forecast future share prices. Rather, he is one who admits that he doesn’t know how to forecast future share prices - but can articulate how he still manages to achieve his investment objectives despite it.
Stock market history is written by the stock market winners - hence the only acceptable investment strategy is to ensure that all possible future investment outcomes are favorable. The only way to do this consistently is to aim to Don’t Lose Money.
Investing in Growth Factor stocks leaves one exposed to valuation risk - while investing in Value Factor stocks is capable of fulfilling the necessary criteria of ensuring that all possible future investment outcomes are favorable. Because of this, investing in Value Factor stocks is superior to investing in Growth Factor stocks as a category.
When investing in Emerging Markets (e.g. ASEAN), investing in Value Factor stocks is the better approach as it is able to mitigate the existence of heightened uncertainty.
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Well written! Keep it up Aaron :)
This is really good stuff