There has been a tremendous amount of focus placed on the efficient market hypothesis in recent years. In particular, the argument is advanced (quite boisterously) that the efficiency of the capital markets matters to your investment decisions. Since the financial markets are highly efficient, advocates reason that outperformance is impossible, active management is dead, value investing is pointless, and everyone should just embrace the mediocrity of passive index investing. However, this conclusion couldn’t be farther from the truth. The reality is that market efficiency is irrelevant to long-term investors and active/value investing remains as viable a path to achieving long-run outperformance as ever.
The fatal flaw in the efficient market argument lies in a fundamental failure to understand (1) the theory itself and (2) the fact that it is merely one component of a far more complicated equation. In this article, we’ll explore the concept, demonstrate why it is irrelevant to long-term investors, and discuss what this means for the retail investor.
Before we delve into the details, it is important to establish that there are two definitions of efficient markets: the strict definition and the broad definition. It is important to differentiate between the two.
The efficient market hypothesis argues, in a strict sense, that a market in which participants share low-cost access to the market and equal access to available information is an efficient one.
In other words, an efficient market represents a level playing field. However, it does not determine nor impact outcomes (performance).
This is akin to the NFL. The league maintains a level playing field—teams have equal access to participate/compete and equal access to information and analytics. However, this in no way precludes any given team from outperforming others.
I’m not a fan of the Patriots; however, they have clearly outperformed the league average. Is this because they had better access to players, equipment, or information? Of course not. So clearly, there is something else at work beyond simply an efficient “market.” In other words, the efficient market in and of itself cannot explain the empirical variance in market performance.
Today, the financial markets are, in fact, highly efficient. Nearly all participants now have low-cost access through brokerages and nearly instant access to information through a plethora of free media sources (e.g., CNBC, Yahoo! Finance, brokerage tools, government and company websites, etc.).
As such, there is no edge to be found within the strict definition of an efficient market. This means it is impossible to consistently outperform the market based on cost or access to information.
However, this in no way determines outcomes or eliminates the potential to outperform—as so many claim it does.
As with football, something else must be responsible for shaping outcomes.
In the financial markets, that something else is known as asset pricing.
Broad market efficiency introduces the second component of the performance equation: asset pricing.
This is typically the market efficiency that most people are referring to. In a broadly efficient market, they argue that the amount you pay for a given stock and the return you receive when discounted for risk equals a net present value (NPV) of zero—meaning there is no way to consistently beat the market.
This view is purely theoretical (based on a perfectly efficient market) and is divorced from reality.
If true, it would mean a stock could never be over or undervalued—it would always be priced exactly right.
Common sense and even the most rudimentary exposure to our financial markets would indicate that this isn’t realistic. It’s akin to believing cute little purple unicorns live at the end of every rainbow.
However, some would argue that even if a stock was “undervalued,” it would represent a higher risk and therefore, though it may provide a higher return, the NPV would remain zero due to the risk adjustment.
However, this is not true either. In fact, many undervalued stocks produce higher returns with less risk due to an increased margin of safety and a number of other factors. This statistically-significant edge was demonstrated by Fama and French based on five independent risk factors (we’ll discuss this in more detail later).
This is precisely why value investing trumps growth investing over the long run.
Furthermore, this position ignores how asset pricing actually works—including the degree to which available information is actually used, how that information is interpreted, the impact of the business/economic/market cycles, investor behavior (emotion), and time constraints (investing horizons).
All of these factors—and many others—reduce the efficiency of the financial markets. And where there is any lack of efficiency, there is the potential for an edge if it can be identified and capitalized on by a consistent process.
To understand why the broad take on market efficiency—that active and value investing is dead and you can’t outperform the market—is wrong, we need to look more closely at asset pricing, also known as the market equilibrium pricing theory.
Assuming a level playing field is present (strict market efficiency), the foundation of the financial markets is asset pricing.
Market performance is a two-factor equation, and asset pricing represents the second (more important and complex) variable.
In its most simplified form, investors base pricing on future expected earnings:
In a broad sense, market efficiency depends on (1) how rationally market participants are in evaluating this and (2) how consistent they are in acting on it (i.e., not allowing emotion or other constraints to influence or override their determination).
As Fama famously stated in 1970, “A market in which prices always ‘fully reflect’ available information is called ‘efficient.’”
The inherent problem in the efficient market hypothesis is that it hinges on the notion that if there is available information indicating an asset’s value will be higher in the future, then—all other things equal—investors will buy that asset today… thereby increasing its price.
Again, this depends on how market participants (1) determine that future value, (2) how they define “future” and (3) how consistently they act on that determination. Everyone has access to the information, but how each interprets it is entirely different. Furthermore, transactional decisions (buy/sell) depend on valuations at different future points in time. Finally, emotions and other constraints (e.g., short-run performance expectations) can influence or even override logical price determinations.
Additionally, the discount rate depends on determining the inherent risk—which can vary greatly and is also impacted by time horizons.
As a result, markets tend to be much more efficient in the short-run… but far less efficient over longer time horizons. This generates a huge time-arbitrage edge for retail investors who can invest for longer time horizons (but we’ll get to that later).
The important thing to understand at this point is that (1) the financial markets are efficient in a strict sense (i.e., equal, low-cost access to the markets and information), (2) asset pricing is subjective and highly-sensitive to short-run catalysts, and therefore, (3) broad market efficiency is greatest in the short-run but decreases as time-horizons expand. Not coincidentally, this correlates well with chaos theory.
With a basic understanding of both the Efficient Market and Asset Pricing, it is worth looking at the academic development of the Efficient Market Hypothesis.
The journey begins in 1900 when Louis Bachelier noted that stock prices seemed to be random in nature (an empirical finding).
Work in the 1950s and 1960s further confirmed this notion of a “random walk” nature for stock prices. Again, this was based on empirical analysis—there was still no theoretical hypothesis to explain it.
In 1965, Paul Samuelson released his “Fair Game Model” regarding stock price behavior. He reasoned that “in a well-functioning and competitive market, we would expect prices to change as investors’ expectations adapt to new information.” This was the first theoretical framework to explain asset pricing, and it marked the beginning of the academic pursuit of a unified asset pricing model.
In 1970, Eugene Fama released his groundbreaking paper Efficient Capital Markets: A Review of Theory and Empirical Work. The biggest takeaway was that it formalized an empirical approach to testing the theory of market efficiency—providing a potential bridge between theoretical thinking and empirical analysis.
Fama never claimed the market was perfectly efficient. That would be an ideal (theoretical) state that is unachievable in the real world. Thus, the question becomes—from both a theoretical and empirical perspective—how close can the real market approach perfect efficiency?
Unfortunately, the efficient market hypothesis cannot be definitively proved or disproved. This was acknowledged by Fama in the second big takeaway from his work: The Joint Hypothesis Theory.
As we noted earlier, market performance is defined by both the efficient market hypothesis and the market equilibrium pricing theory (asset pricing model).
Fama argues that because these are two interrelated and co-dependent variables, we are presented with what he called the Joint Hypothesis Theory.
In a nutshell, you can’t prove or disprove the efficient market hypothesis because it depends on the asset pricing model. If an outcome appears to contradict the efficient market hypothesis, it could mean (a) the efficient market hypothesis is invalid or (b) our asset pricing model is wrong.
Thus, the efficient market hypothesis is only as useful (or accurate) as our model for asset pricing is.
Again, everything boils down to the asset pricing model—not necessarily the efficient market hypothesis.
The first official asset pricing model was the Capital Asset Pricing Model (CAPM). However, as an early model, it was deeply flawed. Since the 1970s, a great deal of academic focus has been directed towards improving this model.
The greatest advancement was made in 1992 when the Fama-French 3-Factor Model was released. Fama and French sought to identify independent risks that were predictive of future outperformance—factors not reflected in the CAPM model.
The 3-Factor Model identified three such independent risk factors: the market factor, the size factor, and the relative-price factor. Analysis confirmed that a pricing model based on these factors improved the efficient market hypothesis’ ability to explain market outcomes.
In 2014, Fama and French added two more factors—producing a 5-Factor Model: the profitability factor and the investment factor.
Over the years, factor research has exploded, and hundreds of potential factors have been identified by academic research and analysis. However, almost all of these represent subsets of the original 5 factors—meaning they can be explained by simply referring to the impact of the five major factors.
The key takeaway from the new factor model is that outperformance can be achieved by (1) knowing which risks to be exposed to and (2) having the discipline to consistently maintain the exposure.
The asset pricing model matters for two reasons: (1) it identifies risk-adjusted alpha opportunities and (2) it is time sensitive.
First, because it identifies empirically-backed and theoretically-sound opportunities for risk-adjusted outperformance, it absolutely refutes the notion that active investing is dead. Regardless of the degree of “active” management employed, the 5-Factor Model for asset pricing demonstrates that a real edge exists for selective investing—meaning, selecting stocks with the right risk factors will provide a statistically-significant amount of potential alpha when compared to a passive approach.
Second, the asset pricing side of the equation matters because it ties directly to the basic market value formula investors utilize to make pricing decisions—one that is time sensitive.
This means that there is a potential time-arbitrage edge available to retail investors in addition to the risk factors.
The corollary to this is that the market’s efficiency is irrelevant to long-term investors. It doesn’t matter whether the efficient market hypothesis is valid, invalid, weak, semi-strong, or strong. Rather, it is the asset pricing side of the equation that matters because that is where potential edges exist—despite the claims to the contrary by the passive “can’t beat the market” pundits.
The reality is that the investing horizon for most investors has shrunk dramatically over the last few decades. No longer are investors focused on results over 5, 10, or 20+ years. Rather, most market participants now expect results over 1, 2, or 3 years. Instant gratification (largely based on recency bias and secular changes) has replaced patience and persistence.
The consequence of this is that fund managers must now continuously deliver short-run results or face massive capital outflows as investors bail to chase the newest shiny object with a more attractive one-year return.
Add to this a strong bull run in which all boats were raised by the tide. This market environment (1) made it difficult to outperform the broader market and (2) raised the penalty for underperforming—even if it was only for a short period of time.
This has resulted in two critical repercussions.
First, most public actively-managed funds have resorted to benchmarking to the broader market. This is why recent statistics tout that active managers are failing to outperform passive index funds. The truth is they are not rewarded for seeking longer-run outperformance (and are actually penalized for it). However, the market environment will inevitably change and, when it does, the new “reality” will change, and active managers will once again outperform the passive benchmarks.
Second, the market has become even more sensitive to short-run information catalysts. Active managers can no longer simply ride-out the short-term volatility—even if they know it will be rewarded in the long run—because they can’t take the short-run hit to their performance… investors will bail if they do. While it could be argued that this actually represents a heightened-level of efficiency in the short-run, it undeniably and unescapably leads to decreased market efficiency in the long-run.
Here’s just one example of this from 2000 to 2010: Of the top quartile (25%) active managers of the best performing institutional funds, nearly half of them (47%) spent at least three of those years in the bottom decile (10%). That simply wouldn’t fly today. They would never be able to achieve this level of 10-year outperformance because investors would bail during those down years. They simply can’t stomach the volatility or maintain the patience required to outperform the markets over meaningful periods of time!
Don’t believe that? During the same period, the best of those funds produced an annualized gain of 18%–smashing the market return over that period. And yet, the average investor managed to actually lose 11% a year on a dollar-weighted bases. Why? Because they bought-in high when short-term performance was strong and bailed during the down years—they chased the herd and then couldn’t stomach the volatility! And that was twenty years ago.
That’s not good for the funds either—managers are evaluated based on assets under management (AUM). To avoid the outflows from uncommitted investors, they are being forced to abandon the very processes that are responsible for producing the massive long-run outperformance (but are inherently volatile) for short-run mediocrity.
Active investing works—always has—but it requires a long-term focus, risk tolerance, and the patience to stick with it… things that are in very short supply in today’s market!
Add behavioral finance to the mix (retail investors exhibiting herding, loss aversion, anchoring, recency bias, etc.) and you have strong short-run overreactions to the upside and downside. The markets have been, are, and always will be an emotionally-charged playing field. Models can predict based on historical data, but the emotional component will always skew things over the short-run at critical moments.
This decrease in long-run market efficiency produces a time-arbitrage edge for retail investors that have a long-term focus and the discipline to stick to it. You can identify long-run value opportunities in stocks that are out of favor in the short-run, as well as further capitalize on short-term overreactions.
I find it interesting that the “death” of active management only seems to be impacting public funds. The available data seems to strongly indicate that private active funds continue to perform quite well (without the constraints introduced by having to satisfy the fickle, weak-stomached, short-term investors).
A final note on the declining popularity of actively-managed funds is that they obviously come with a higher cost for investors. That inherent cost requires even more outperformance, which—again—is hard to deliver in a strong market updraft. However, a retail investor can actively manage their own portfolio with no added cost other than time and effort—another advantage.
As we have seen, there are lots of factors that contribute to market outcomes. While the financial markets are reasonably efficient, there are several key things that limit that efficiency:
Current efficient market and asset pricing models are able to explain roughly 90% of market outcomes. However, the 10% these models can’t explain—though it may sound minor—represents a massive gap in systemic efficiency.
As such, retail investors have the opportunity to outperform the market through long-term active investing by not only leveraging specific risk factors but by capitalizing on that efficiency gap.
The reality of efficiency constraints and gaps can be clearly seen in the price moves of Facebook over a one-year period:
Does this represent a high-level of market efficiency? Did the value of the company really change that dramatically over the span of just one year? Or, is this an example of (1) informational catalysts significantly impacting asset pricing over the short-run and (2) the power of emotional behaviors in the markets that lead to overreactions?
We can debate the degree of market efficiency until pigs fly and all the cows come home… but it is absolutely irrelevant for the long-term retail investor.
As retail investors, we do not acquire an edge by gaining a cost advantage or better access to information.
However, to stop there and somehow argue that there is therefore no edge available at all, no advantage to active or value investing, and no opportunity for outperformance is to perpetrate a felonious fraud of logic and yield to intellectual dishonesty at an absurd level.
What is absolutely relevant is how the market prices assets—or the equilibrium pricing model.
Factors matter. Investing time-horizons matter. Emotions matter.
The retail investor has a distinct advantage in being able to freely capitalize on both risk factors and time arbitrage—further abetted by overreactions to short-run catalysts and ever-present emotional behavior.
Absolute claims are almost always invalid. Claims that (1) active and value investing are dead and (2) market outperformance is no longer possible both fit squarely into this category of specious hyperbole. Always be wary of such claims.
Conversely, this does not mean that all active investing will lead to outperformance. It requires an effective process and proper mindset. However, I would argue that the potential to outperform is an entirely realistic one for the average retail investor… and the alternative is to settle for mind-numbing mediocrity. You don’t have to settle for passive-based mediocrity… there is another option.
Take the blue pill and the story ends. You wake up to live out a life of passive-investing mediocrity.
Take the red pill and you get to discover how deep the active-investing rabbit hole goes… and gain the opportunity to achieve market outperformance.
Remember, all I’m offering is the truth… nothing more lol!
That mediocrity might seem acceptable when markets are ripping higher… but what about when they are ripping lower or trading sideways for a decade?
Be cautious of recency bias—the empirical data indicates that we have consumed quite a bit of future potential and may be headed for an extended period of consolidation—meaning passive returns of 2%, 3%, or maybe 4% rather than the 10%+ that passive investors have become used to over the current bull run.
If that should happen, you will see the re-birth of active/value investing being unabashedly trumpeted by the media and industry (though it never really died!).
If you took the red pill and you’re interested in dividend-growth investing and/or looking for valuable insights into value investing, then you’re in the right place!
At Wicked Capital, we focus exclusively on helping others become as successful as possible with dividend-growth investing predicated on an empirically-backed factor framework and we hope you’ll continue to return to our site to learn, grow, sharpen your skills, and find effective and positive ideas and motivation!
Soak it all in, take and use what you want, modify it to fit your unique situation, and keep building that DGI portfolio with a solid process and winning long-term investing mindset!
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