What is Value Investing? | An exposition of the definition of value investing

Value investing has gotten a bad rap due to its underperformance vs growth investing over the past decade. But is that really value investing?

Everyone is familiar with the term “value investing” by now. Coined by the ‘Sage of Investing’ Benjamin Graham and popularized by the ‘Oracle of Omaha’ Warren Buffett, value investing has come to be adopted by a legion of investing devout around the world - with 2019’s Berkshire Hathaway AGM being attended by 40,000 attendees. Fun fact: that’s roughly the average attendance of a Taylor Swift concert.

But what is value investing? To be sure there already exists a well-defined popular notion of it, but like with much of public opinion it may not necessarily be the best representation of it. Many reputable self-described value investors have knocked on this consensus definition of the term, claiming that the legalese doesn’t represent the original spirit of value investing. Hopefully, by the end of this article, you’ll have a better understanding of it.

The misconception

To understand what value investing is, it’s easier to begin with what “value investing” isn’t.

Contemporary finance’s definition of value investing tends to refer to investing in stocks with low valuation multiples (e.g. low P/B, low P/E, net-nets, etc). This was likely derived from observing both Graham’s and early-Buffett’s practice of investing in mostly such types of stocks throughout their investing careers.

However, the word “value'“ in the context of “value investing” does not mean cheap. In fact, nowhere in the Oxford Dictionary does this colloquial definition of “value” appear. Oxford defines value as “the quality of being useful or important”, while Merriam-Webster defines it as “relative worth, utility, or importance”.

This is the original meaning of “value” in “value investing”. It simply refers to the excess of benefit over cost. Other more everyday synonyms of “value” include: ROI, value-for-money, bargain. It is also what CEOs mean when they talk about “adding value”.

So when Benjamin Graham coined the term “value investing”, he did not use it to refer to investing in cheap stocks. He meant that there was an excess of benefit over the cost of investment, and therefore that there was utility in performing it. Specifically, he was trying to draw a comparison to speculation, in which the utility is often unreliable and inconsistent.

To further clarify the distinction, let’s analyze “value” from the perspective of contemporary finance. The general definition refers to investing in low-multiple stocks, with the rationale being that the market might have temporarily underpriced the stock relative to its intrinsic value (for one reason or another), which the analytically adept can see past and therefore take advantage of. By filtering signal from noise, this form of value investing advocates a pure focus on intrinsic value over market sentiment as the path to riches.

One commonly cited example of this practice is Buffett’s investment in American Express in 1963, when the company was hit by the Salad Oil Scandal (google it). The short version of this investing fable is that Buffett saw past the scandal and instead paid attention to the company’s bread-and-butter business of traveler’s checks, which were still transacting well despite the PR disaster that the investment community was obsessing over. He ended up investing 40% of his partnership’s funds into that one position, and it quickly doubled in a short period of time, helping his firm outperform the S&P 500 by 200% over that period.

However as public opinion is wont to do, contemporary finance takes this general concept of value investing and morphs it into its own version. Over time, the finance industry has developed a scalable version of the original concept of low-multiple investing, and christened it the “value factor”. How this manifests in real-life is the investor screens the universe of stocks for low-multiple stocks and buys them, usually with only rudimentary fundamental analysis. For a variety of obvious reasons this spray-and-pray strategy has led to disastrous results, leading to the value factor underperforming the growth factor for 14 years.

Of course, this is not a perfect representation of what the value factor encompasses in the real world (e.g. smart beta, quant); but it’s close enough to get to the heart of my point. Value investing is not low-multiple investing. It is so much more than that.


Principles of Value Investing

Investors who have read Graham’s and Buffett’s literature will already be familiar with most of these value investing principles. However, for the benefit of those who are new to value investing, or those curious to know what they mean in a practical sense, I shall list the more popular constituents of this philosophy:

“In the short run, the market is a voting machine but in the long run, it is a weighing machine.” - Benjamin Graham

“Games are won by players who focus on the playing field – not by those whose eyes are glued to the scoreboard.” - Warren Buffett

As we’ve discussed above, this observation boils down to focusing on a company’s intrinsic value, not its market value of the day. The fact is that there are many factors beyond business fundamentals which affect a company’s share price on any particular day, e.g. the coronavirus pandemic. By eschewing the crowd mentality of instant gratification and having the foresight to hold onto stocks for longer-than-usual periods (i.e. min. 12 months, max. indefinitely), one can exploit possible mispricings that may occur from time to time in the share prices of businesses due to non-fundamental reasons.

Volatility is not risk

Contemporary finance defines risk as the volatility of stock prices, represented by standard deviation. I’ve literally written an essay on why volatility is not risk, but it is generally accepted by the value investing community that volatility does not capture risk in its most primal definition - i.e. the permanent loss of capital.

In contrast, the broader finance community adheres religiously to the notion that volatility equals risk, with material investment decisions being made based on formulaic methods such as VaR models and the Sharpe ratio. While these methods capture statistical realities, they are unable to see around corners the way humans can and can potentially entirely miss the point of risk management.

Value investing adopts the definition of risk as the permanent loss of capital, which requires thorough analysis of business fundamentals to be able to quantify accurately, rather than relying on straightforward formulas.

Stocks are an investment in businesses, not prices

One cornerstone of value investing is that a stock investment represents an intention to profit from the business, as opposed to the fluctuation of prices. Hence, value investing emphasizes observing a company’s value from the lens of a CEO, in contrast to the stock market. Ideally one should be approaching investing in shares with the mindset of an entrepreneur - as an owner of the business.

In essence, investing in shares of publicly listed companies is no different from being a sleeping partner of the business - you may have no say in the operations of the business, but you have the same exposure to the risks & rewards of the business as the founding entrepreneur.

“It's far better to buy a wonderful company at a fair price than a fair company at a wonderful price.” - Warren Buffett

“(…) the greatest investment reward comes (…) from the occasional company that over the years can grow in sales and profits far more than the industry as a whole. It further shows that when we believe we have found such a company we had better stick with it for a long period of time.” - Philip Fisher

Extending the previous principle, this one says that rather than focusing on acquiring shares of poorly-run companies at cheap valuations (i.e. cigar-butt/low-multiple investing), a better investing strategy is to hold onto amazingly-run businesses for long periods of time and let compounding do its work - even if their shares might be more expensive to acquire at the outset.

The market is not efficient

One of contemporary finance’s most widely credited contributions is the Efficient Market Hypothesis (EMH). The EMH postulates that all public information has been priced into stock prices; hence it is impossible to gain an edge from superior analysis.

The basic idea behind EMH is that the army of Wall Street analysts have already discovered whatever information you might have heard about, hence bidding up stock prices to fair value and removing any chance for the layman to profit from it. This disadvantage translates to Wall Street analysts as well - chances are that someone else in the entire world would have already priced in that scarce information about the stock before it scrolls across your Bloomberg terminal.

However, given the volatility of even the most widely-covered stocks (e.g. AAPL), it is difficult to give this theory even the benefit of doubt. If arguably the brightest stock analysts from the likes of Blackrock or JPMorgan were capable of reliably estimating future stock prices (i.e. target prices), there wouldn’t be so much volatility in stock prices as all information about the company should have already been priced in from Day 1.

Just look at AAPL’s 1-year share price performance. Does this look like stock analysts knew in advance what the company’s intrinsic value would be today?

I’m not going to get into the finer details of EMH and why the chart above does not entirely disprove EMH - but it’s enough to make my point that the market may not be as efficient as suggested, and that there still is value in doing your own homework.

“Be fearful when others are greedy, be greedy when others are fearful” - Warren Buffett

The main message of this quote is that of contrarianism. In order to maximize profits from investing in stocks over the long-term, you need to go against the herd instead of following the herd. That means taking unpopular positions and perhaps underperforming for a short period of time, and relying instead on having your investment thesis justified over the long-term.

Now this principle may seem excruciatingly obvious in hindsight, but it is much more difficult to practice in real-time. Without future information, it is impossible to call a bottom and know when to enter a falling knife position, or call a top and exit one that has recently violated the speed of light. So while it is widely-accepted wisdom to buy when there’s blood in the streets, very few investors are actually able to implement it when it counts (e.g. investing in airlines/banks/O&G today).

So what is the secret to the successful application of this aphorism? Fret not, for it shall be explained below.

“An investment operation is one which, upon thorough analysis, promises safety of principal and an adequate return. Operations not meeting these requirements are speculative.” - Benjamin Graham

Value investing draws the distinction between what is considered investing and what is considered speculation. Generally speaking, what most retail investors do can be considered speculation, i.e. getting into and out of stock positions regularly, with investment timeframes measured in days or even minutes.

There are many ways to interpret this quote, such as the maxim that one should invest for the long-term instead of the short-term. But pay special attention to this part of the quote, “promises safety of principal and an adequate return”. What type of familiar investment comprehensively embodies this characterization?

If you’ve answered fixed income, you are right. A typical fixed income investment (e.g. loans or bonds) places paramount importance on downside protection since yields are generally fixed. So what Graham is advocating here is to buy stocks which behave like fixed income investments from an upside/downside perspective. Notice how the qualification of this definition assigns an essential element to the promise of safety of principal, while only requiring an adequate return.

This is quite distinct from the behavior of the overwhelming majority of stock investors, who mostly care about achieving maximum return while placing little emphasis on downside protection. In other words, perhaps 90% of stock market activity (including among professionals) is actually speculation, according to this definition.

“Confronted with a like challenge to distill the secret of sound investment into three words, we venture the motto, Margin of Safety.” - Benjamin Graham

In Chapter 20 of the value investing manual The Intelligent Investor, Benjamin Graham crystallizes the secret to sound investing, margin of safety. There is plenty of literature surrounding this topic, so I won’t elaborate too much on it here (there’s even an entire book named after it). But suffice to say many value investors consider this principle the preeminent investing yardstick to adhere to.

The basic concept of margin of safety is to assign a buffer to your entry price in case things don’t go as planned. In practice, this means investing in a stock only if the company’s intrinsic value is substantially above its current stock price (e.g. at least 20%). As you can imagine, this makes finding worthy investments much, much harder - stock valuations today are frothy enough already without first having to assign a 20% premium. But it also means that you can be very confident of an attractive investment candidate when you come across one which fulfills this condition.

“Rule No.1: Never lose money. Rule No.2: Never forget rule No.1.” - Warren Buffett

“Protect the downside and the upside will take care of itself.” - Donald Trump

I know it’s a bit sacrilegious to put Donald Trump in the same league as Warren Buffet, but he’s the most famous person to have mentioned some semblance of this quote, so I just quoted him. To be fair, many other people have said variants of his quote using different words and lengthier sentences, but Trump’s quote was the most succinct and still gets the message across.

The broad idea behind this investing principle is to focus on risk, i.e. potential losses rather than reward, i.e. potential gains. In fact, the practical application of this principle suggests focusing your attention entirely on the downside, even at the expense of the upside if necessary - which is what “the upside will take care of itself” means. This is in stark contrast to the way almost everyone evaluates an investment decision, which is to determine how much potential upside exists while utterly forgetting about the downside.

So why do this? The simple answer is that the nature of compounding penalizes losses far heavier than it compensates gains - e.g. if you make a 10% gain and then a 10% loss, you end up with less money than you started. And since financial crises tend to involve large drawdowns on stocks with the highest returns (and hence highest risk), the cumulative damage over several cycles to long-term average returns can be substantial.

The more complex answer is that businesses do not operate in a predictable linear fashion the way financial models suggest. From the perspective of a sleeping partner, the return profile of a business investment should behave formulaically according to its business model; but in reality, businesses are living, breathing organic creatures with hundreds of moving parts that all need to be kept in line in order to produce the desired financial results.

On one hand, investors should have a fair expectation that management will execute operations to mimic the business model as perfectly as possible; on the other hand, they should also be prepared in case things don’t go according to plan. Hence, investors and entrepreneurs alike should ensure that their financial returns reflect the perfect execution of the business model as much as possible, by diverting sufficient resources from maximizing profits towards proactively addressing possible threats to the business model that could potentially affect established financial objectives.

It's not whether you're right or wrong that’s important, but how much money you make when you're right and how much you lose when you're wrong.” - George Soros

“Heads I win, tails I don’t lose much.” - Monish Pabrai

“(…) every possible series of events is happening all at once. Live that way and nothing will surprise you. Everything that happens will be something that you’ve seen before.” - Littlefinger, Game of Thrones

Stock market participants are preoccupied with forecasting correct absolute outcomes for their stock investments, hence enabling them to determine correct absolute valuations. This is the basic premise behind the Discounted Cash Flow (DCF) model, which assumes that one has basically perfect foresight into the company’s future and is able to input those resultant discounted cash flows into the model to derive a correct absolute Net Present Value (NPV).

The presumption that follows is that if you are wrong about those inputs, then the resulting valuation will also be wrong. Since this is an article about investing principles, I am not going to launch into a sermon about how badly those inputs could potentially be compromised (e.g. WACC, terminal value). However, I will point out that the average business environment tends to be incredibly complex and involve hundreds of moving parts, while the average human being is generally incapable of fully grasping the financial implications of all those moving parts. So the balance of probabilities lies with the stock analyst more likely than not being wrong about their valuation of the company.

However, the DCF doesn’t accommodate one being wrong in their analysis. It kind of requires you to be absolutely or at least marginally correct. If you are wrong about a significant input, then your valuation is pretty much trash. Hence why stock analysts tend to divert all their attention towards procuring information that is as superior as possible.

However, what Soros and Pabrai are advising here instead is to factor in the possibility of error. Soros starts his quote by saying “it’s not whether you’re right or wrong that’s important” - which means that one shouldn’t put too much effort into forecasting a particular outcome correctly (i.e. it’s inconsequential to be wrong about it).

Then he goes on to say “but how much money you make when you’re right, and how much you lose when you’re wrong”. This means that you should have already estimated the financial impact of all reasonably possible outcomes, both to the upside and the downside. So even if you unintentionally forecasted the wrong outcome, you’ll still know what to expect (this is where the Game of Thrones quote comes in).

Building on that, you don’t necessarily need to accurately forecast a particular outcome in order to profit on an investment. As long as the financial outcomes if you’re right sufficiently outweigh the financial outcomes if you’re wrong (i.e. a positive risk:reward), and your positions are adequately diversified, your winners should be able to offset your losers with room to spare, and your overall portfolio should return a positive yield. This is basically how insurance companies work, by the way.

Notice how most of the principles above deal with risk, in contrast to the finance industry’s fanaticism with reward. It shall become apparent why later.


My personal application of Value Investing

They say wisdom is the synthesis of knowledge; so this is my attempt at wisdom. Having read all the sage sayings above, I naturally began to ruminate on their constituent parts and consider how I could pull them together into an executable strategy. Within the context of the above value investing principles, a coherent picture began to form.

Principle #1: Winner writes history

My process begins with performance. Naturally you’ll want to achieve a predetermined level of performance from your investments (e.g. 15% CAGR), and your goal should be to attain that performance no matter what. The natural extension of this is to look back in time and study what worked in the past (e.g. what kinds of investments yielded 15% CAGR), and try to replicate those characteristics going forward.

However, in my quest for truth I realized one thing - the winner writes history. In the context of investments, studying the historical share price of a company for clues of outperformance assumes that the path it took was the only path it could have taken. In reality, there may have been so many surprises and unexpected turns in the business environment that could have materially altered the original trajectory of the share price from the beginning of the timeframe being studied. Hence, only relying on the backward-looking analysis of successful investments could end up yielding incorrect conclusions about what investment conditions might lead to success in the future.

Let me provide a recent example. Warren Buffet famously campaigned on behalf of Hillary Clinton in the US 2016 presidential election. Why? Because at the time she was widely expected to win. However, as we all know Donald Trump eventually emerged the victor - even though that was widely considered to be an outlier outcome. And Buffett definitely faced financial consequences after Trump took office as a result of his public support for Hillary.

So did Buffett make a mistake by backing the wrong horse? Hindsight would most certainly say yes. Maybe he didn’t do enough homework and missed that certain swing states could have voted red instead of blue. But that’s looking back at the past using the present as a reference point, and rationalizing present-day outcomes by working backwards to connect the past to the present. However, recall that prior to the election results being announced, Hillary was widely expected by the majority of the world to win, and stock prices were essentially priced for her victory. So in the absence of (then) future information, it seems that Buffett was not alone at the time in thinking that Trump wasn’t likely to win.

But Trump did end up winning. So were markets wrong prior to the elections results being announced? I don’t think so. I think it’s more likely that Trump’s win was indeed a low-probability outcome given available information at the time. Investors colloquially refer to such outcomes as a ‘black swan event’ (e.g. coronavirus is also a black swan event).

However, if you were to try to develop a strategy based purely on backward-looking hindsight, you might end up with something which reproduces low-probability events, which is the antithesis of a good investment strategy. Remember that when making investment decisions you will never have the benefit of hindsight, so you’re always forced to make decisions based on incomplete information.

Thus, instead of developing a strategy that tries to accurately forecast absolute outcomes with precision, I have opted instead for a strategy built around investing in high-probability outcomes (e.g. a Hillary win in 2016). However, in recognizing that this strategy does sometimes get it wrong, I also at the same time ensure that my downside is limited even if the low-probability outcome materializes (e.g. a Trump win in 2016).

In essence, this is the practical application of Soros’ quote, “it’s not whether you’re right or wrong that’s important, but how much you make when you’re right and how much you lose when you’re wrong”. By maintaining a positive risk:reward at all times, I ensure that my overall return profile has an adequate margin of safety and that I never lose money (Rule No. 1) at the portfolio level.

Principle #2: Never lose money (Rule No. 1)

Allow me to preface this by restating the proper definition of risk: permanent loss of capital. This means that risk does not necessarily equal drawdowns, which can be temporary. It represents a loss of capital that is permanent, often as a result of a drop in the intrinsic value of an investment.

So in a world where winners write history, what is the appropriate forward-looking strategy? The common refrain is to win at all costs, because the end justifies the means. However, there is a slight problem with this method, namely that you can’t guarantee a win every single time. In fact, chances are that you will probably end up losing quite a few times no matter how hard you try - due to the simple fact that you can’t realistically predict every single outcome in advance, and that you are going up against the entire rest of the world.

In contrast, the other option recommended by Buffett is elegant in its simplicity: Don’t Lose. This may sound like semantics compared to win at all costs, but there is a meaningful difference. First of all, it means that winning the battle is no longer mandatory, so you don’t need to resort to pyrrhic victories if the ROI from letting go of your objective becomes higher - i.e. you can afford to incur Fabian losses, where you underperform in the short-term with long-term outperformance in mind. Secondly, it means that you shouldn’t stick your neck out so far that you can’t pull it back, if and when it ever becomes necessary.

As many business casualties are self-inflicted in the justification for growth (e.g. taking on too much debt, expanding too quickly, choosing risky strategies), playing it safe can make the difference between life and death if and when the next crisis hits (e.g. airlines during coronavirus). Then, by virtue of being among the remaining survivors, you’ll get your chance to write history.

Empirical evidence seems to support this theory. In Howard Marks’ 1990 letter ‘The Route to Performance’, he cites the example of a pension fund manager who significantly outperformed the S&P 500 over the long-term, but strangely had only ever occupied the ranks of second-quartile performers:

We have never had a year below the 47th percentile over that period or, until 1990, above the 27th percentile. As a result, we are in the fourth percentile for the fourteen year period as a whole.

This phenomenon can be observed even in the business world. This VC fund manager gives special mention to his ‘second-quartile’ performers, which while only delivering 15% of total returns were also their most reliable generators of value.

And of course, who can forget about Winning The Loser’s Game, which drew insight from the realization that tennis matches tend to be lost by the player due to their own unforced errors, rather than won by the opponent due to their superior skill. It concludes that winning at ‘loser’s games’ like tennis and stock investing has more to do with avoiding self-inflicted losses than trying to win the game. So the most efficient strategy becomes minimizing your own errors, rather than attempting to beat your opponent.

The lesson to take home is this: if you want a scalable investment strategy that can durably generate consistent returns over long periods of time, don’t plan on winning all the time. Plan on never losing.

Principle #3: Embrace Calculated Risk

Let’s assume that EMH is real, and that the market is truly efficient, i.e. all public information has been priced in and it is impossible to find an edge with superior analysis. Well then, what is an investor to do?

The key part that most retail investors miss about EMH is that it is only efficient with regards to public information. This means that any non-public information is not priced in with precision - which includes information about the future. I don’t care how superior your information is, nobody has a crystal ball.

The best anyone can do under those circumstances is to estimate the probability of an event happening. For instance, given a particular petrochemical plant, let’s say that the possibility of Process A getting choked up and forcing a plant-wide shutdown for 24 hours is 1.5%, and the productivity loss is $300,000. So to determine your loss exposure, you take the magnitude of that loss ($300k) and multiply it by the probability of it occurring (1.5%) - which gives you a loss exposure with an expected value of $4,500. Lay out all potential exposures from such risks & rewards in front of you (e.g. on an Excel spreadsheet), and it should give you a range from which you can now reliably estimate a business’s future intrinsic value.

Now of course, just because you do this doesn’t subsequently give you an edge in investing, because you are also part of the “nobody” in “nobody has a crystal ball”. But it is possible to differentiate yourself from the pack by adopting contrarian positions. For instance, let’s say that following the Process A shutdown, the share price of the aforementioned petrochemical company is now pricing in several severe shutdowns as a result of Process B, C and D also choking up. Well, you could decide to take the risk that maybe Process C doesn’t choke up, and therefore the company’s intrinsic value should be higher than the market price. Of course, this presumes that you have done enough homework and are highly confident that your position won’t end up with a huge loss even if Process C does choke up (i.e. limited downside). But you can see where I’m going with this.

The conclusion to all this is that the answer to consistent outperformance is embracing calculated risk. By taking intelligent risks on uncertain outcomes which the market is not pricing in, we can still profit in an efficient market if that outcome materializes. Thus you don’t necessarily require superior analysis in order to bag a win. You just need to be comfortable with taking risk.

In fact, there is historical precedent for this strategy. Take for example Soros’ bet on Black Wednesday, where he earned his reputation for breaking the Bank of England. I don’t remember exactly where I learned this (if someone could help me find the interview I would be most appreciative), but in one of his interviews he stated that his potential loss on that position was only 4%; whereas the potential gain was in excess of 100%. So he had a risk:reward of 1:25 on that position.

Clearly that was an extremely contrarian bet, given that the market at the time was pricing in 1:25 odds of Britain pulling out of the ERM. But Soros knew that possibility existed, however remote the market thought it might be. And even in the event he ended up being wrong (e.g. the Bundesbank agreeing to lower German interest rates, which remained a real possibility up to the 11th hour), he would only take a maximum loss of 4% in aggregate. That’s why he was confident enough to lever his firm up to the hilt on that bet; and on that day he ended up writing his own legacy.

Another historical precedent can be observed in Graham’s practice of only acquiring low P/B companies. The common reasoning behind this strategy attempts to explain the upside, which is that by only buying stocks that were trading below their book value, he would be able to liquidate the company’s net assets and sell them for at least book value (i.e. higher than his cost). But what the popular narrative tends to miss is that even in the event he was unable to successfully liquidate the net assets as intended, his downside was limited by virtue of the padded balance sheet (i.e. he would in all likelihood still be able to dispose of his shares at around book value). Heads I win, tails I don’t lose much.

Now this phenomenon may not appear to exist in form in today’s stock market, where net-net stocks tend to be quite rare. But it does exist in substance, in the context of the downside being limited. For instance, you could reallocate your preference to stocks with limited upside, where the balance of probabilities (and therefore market prices) lies with persistent underperformance (i.e. their low P/E ratios are fair); or are lacking a clear upside catalyst - but which also have limited downside, by virtue of having a robust balance sheet or one that is highly cash accretive.

Gamestop in 2H19 was an example of such a stock. The business outlook for the company at the time was frail, and there was no apparent upside catalyst for the stock given available information at the time. But the company also held more net cash than its entire market cap, which meant that the downside was limited. As of today Gamestop has since doubled on new information, which meant that contrarian investors of the stock who were betting on the two birds in the bush have since been rewarded handsomely, while only exposing themselves to limited risk.

Another modern practitioner of this is Michael Burry, of The Big Short fame. In 2019, he invested quite significant and roughly equal amounts into two dying retail companies (i.e. Tailored Brands and Gamestop). In light of the coronavirus pandemic - which he couldn’t have predicted - the former went to zero while the latter doubled (it actually tripled as of last month, but has since tapered off). So one could conclude that as of today, Burry has at least broke even on the two investments, with remaining upside optionality on Gamestop.

In an age where everyone has a Bloomberg and the same informational advantage, perhaps the best way forward for attaining outperformance isn’t through superior analysis of absolute outcomes, but by embracing calculated risk-taking. This also has the advantage of widening the investment universe to stocks which might have previously been considered untouchable, e.g. airlines/banks/O&G today.

Principle #4: If you can’t beat the house, become the house

If you walk into a casino, you can typically find a game called the Roulette Wheel. In principle, the game is played by rolling a ball into a spinning wheel with red & black markers, and bets are placed by betting on which color the ball eventually settles on when the wheel stops spinning.

In theory, there should be a 50/50 chance of winning this game since the ball can only fall on either red or black. However, the roulette wheel also has an additional “green” marker, which is typically numbered ‘0’ and gives an extreme 35:1 payout if the player correctly guesses that the ball will land on it (some casinos also add another ‘00’ green marker). Obviously this is extremely unlikely to happen, which is why the payout is so high.

Without the green marker, the casino has the same statistical probability of winning as the patron, i.e. 50%. However, by adding the green marker the casino has a slightly higher-than-50% chance of winning, because the odds of the ball landing on green is practically zero. While this does not materially improve the casino’s odds of winning any single particular game, the distribution of wins over a million games mimics the statistical distribution of the bell curve, which leads to slightly more-than-50% of average wins over losses. This unfair advantage is called the “house edge”, which leads to the saying “the house always wins”, i.e. over the long-term gambling at casinos is a losing proposition.

How is this relevant to value investing? Well, most stock market participants tend to think of picking stocks in binary terms, i.e. you can be either right or wrong. This is very similar to how gamblers think about the roulette wheel. Of course there are many other factors which go into stock picking, but how most investors think about it in principle is not that different from playing roulette.

This leads to the “buy high, sell low” mentality that the majority of stock market participants are plagued with. When stocks are going up it reinforces the notion that their bets are correct, hence becoming more confident and plowing more money into their investments. Conversely, when stocks are falling it reinforces the notion that their bets are wrong, leading to them getting jittery and exiting their investments. This is not a design flaw in human psychology; it is the natural risk-averse “flight” response that helps us avoid danger in real-life. But clearly it works to the detriment of stock market investors here.

However, if we put the aforementioned principles together, we can formulate a strategy which enables us to subvert this natural survival instinct to our own advantage. Since “the house always wins”, rather than trying to beat the house at its own game, we should become the house instead. In other words, rather than playing the game of roulette, we should create the game of roulette.

Remember what I said about Embracing Calculated Risks in my earlier principle? We can do that with our investments as well, by only picking stocks with a minimum risk:reward ratio of 1:3 (i.e. the upside if you’re right is at least 3x higher than the downside if you’re wrong). If you have enough such stocks in your portfolio (i.e. your portfolio is adequately diversified), then your portfolio should also naturally have a risk:reward ratio of 1:3 as well.

Keep in mind what having a risk:reward ratio of 1:3 means. It does not mean that you will have a guaranteed return of 66.66% (i.e. 2/3) on your stocks. Rather, it means that your portfolio as a whole should have a 66% chance of outperforming. To use the roulette analogy, it means that you are now the casino with 66% of the colors on the roulette wheel in your favor.

However, this also means that there is still a 33% chance of underperforming in any particular year - which is similar to the fact that the casino can still lose in any particular single roulette game. But over a long enough timeframe (i.e. an ample sample size), your real-life portfolio returns should reflect the statistical distribution of wins at 66% as designed (i.e. just like the casino).

This also helps immensely when applying Warren Buffett’s adage of “buy low, sell high”. If the chance of your portfolio going up remains the same at 66% no matter what (i.e. >50%), then all else being equal, you should be buying rather than selling when share prices fall (obviously this is simplifying things, but you get the basic idea). By having the confidence that there is still a 66% chance of your portfolio going up even as share prices fall, you will be incentivized to buy more as share prices fall since stocks are now even more of a bargain. This is how value investors have the stomach to “be greedy when others are fearful”.

Conclusion

To summarize, value investing cannot simply be represented by the value factor (i.e. low-multiple investing). It possesses an immensity of breadth and depth, and is much closer to contemporary finance than one might think - while at the same time maintaining some important distinctions. When you really boil it down to its essence, it is to invest in value, i.e. the excess of benefit over cost. As a solemn reminder, Benjamin Graham’s quote bears repeating here:

If your investments meet this qualification, then it is intelligent investing, and you are a value investor. May this article represent your introduction into the wonderful world of value investing!