Efficient Markets: Myth or Reality?

Blog Post by Best Fin Investment



Upward view of sleek, modern skyscrapers in the heart of Wall Street, New York, hinting at the dynamics of efficient and non-efficient financial markets.

Table of Contents:


Introduction:
The Efficient Market Hypothesis (EMH) has long been a cornerstone of modern financial theory, positing that asset prices fully reflect all available information, making it impossible for investors to consistently achieve above-average returns. However, recent years have seen growing skepticism about the applicability of EMH in real-world markets. In particular behavioral economists believe that the EMH framework cannot fully explain why market efficiency varies over time. In this blog post, we explore some of the various arguments surrounding the efficiency of financial markets, examining both the proponents' and critics' perspectives.

Homo Sapiens vs. Homo Economicus:
Before diving into the Efficient Market Hypothesis (EMH), it is essential to first explore the contrasting views of human behavior encapsulated by the terms Homo Sapiens and Homo Economicus. These two concepts represent different models of how individuals make decisions, which in turn shape our understanding of financial markets.

Homo Sapiens refers to the dominant species on this planet and literally means "wise man". Homo Sapiens also refers to actual human beings as they exist in reality. This model acknowledges the complexity, emotions, biases, and imperfections that characterize human decision-making. In financial contexts, Homo Sapiens are recognized for their psychological tendencies, such as loss aversion, overconfidence, herding behavior, and other cognitive biases (e.g. mental shortcuts and heuristics), that can lead to irrational decision-making. This concept is central to behavioral economics and finance, where the focus is on understanding how real people make decisions, often deviating from purely rational models [4,9].

Homo Economicus, or "economic man", is a theoretical construct that represents an idealized version of human behavior in economics. This model assumes that individuals are perfectly rational, fully informed, and consistently act in their own self-interest to maximize the so-called utility (or profit, in a financial context). Homo Economicus is depicted as a logical, unemotional decision-maker who always makes optimal choices based on available information and a clear understanding of risk and reward. This concept underpins much of classical economics and finance theory, where models often assume rational behavior to predict market outcomes, even though this assumption may at times oversimplify the complexities of human decision-making [4,9].

The contrast between these two models highlights the tension between traditional economic theory (which often relies on the Homo Economicus model) and behavioral finance (which acknowledges the more nuanced and less rational behaviors of Homo Sapiens).

EMH Definition:
The EMH [7] was first formally introduced in the 1960s by Professor E. Fama, co-recipient of the 2013 Nobel Memorial Prize in Economic Sciences (together with Robert J. Shiller and Lars Peter Hansen). The EMH forms nowadays the intellectual bedrock on which classical financial theory sits. The EMH is built upon several key assumptions as given here below.

- Rational investors: EMH assumes that Homo-Economicus is a rational and profit-maximizing agent, in other words that investors always act in their best interests based on available information.
- Prices as a reflection of exogenous factors: Prices faithfully reflect fundamental values and only move in response to exogenous, i.e. external, unpredictable news. This view of markets implies that bubbles or crashes can only arise from external shocks rather than from internal market dynamics.
- Random walk price behavior: This framework posits that asset prices follow a random walk, where each price change is independent of previous changes and hence is unpredictable. Brownian motion serves as a mathematical model for the random walk hypothesis, illustrating the unpredictable nature of asset price movements in an efficient market.
- Independent and identically distributed (i.i.d.) price variations: The assumption that price variations are i.i.d. is another fundamental aspect of the EMH. This assumption implies that each price change is independent of previous changes and follows the same probability distribution. In other words, the pattern of price changes should be consistent over time, with no systematic relationship between successive changes. This assumption aligns again with the random walk hypothesis and reinforces the idea that asset prices follow a random and unpredictable path in an efficient market.
- Bell curve distribution of price variations: According to this assumption, the distribution of asset returns should resemble a bell-shaped curve, or normal (Gaussian) distribution, with most returns clustering around the mean (average) and fewer returns occurring at the extremes.
- Information efficiency: The hypothesis assumes that markets are efficient in incorporating new information into asset prices. This means that prices adjust in a timely manner to reflect new information, leaving no opportunities for investors to exploit market inefficiencies.

Support for the EMH:
The EMH is founded on the belief that financial markets are inherently unpredictable, reinforcing the idea that attempting to beat the market is, for most investors, a futile endeavor. This belief is supported by the following observations:

1) The absence of linear autocorrelation in asset returns, particularly within time scales ranging from approximately a few minutes to a few weeks or months, stands as a key pillar supporting the EMH [6,10]. Hence past movements in stock prices cannot be used reliably to foretell future movements. The stock market has little, if any, memory and can thus be compared to a so-called random walk process. A random walk is one in which future steps or directions cannot be predicted on the basis of past history.
2) According to EMH proponents, asset prices incorporate all available information instantaneously (by quickly reflecting all the news that is available), leaving no room for investors to exploit predictable patterns. Essentially, the market is so efficient - prices move so quickly when information arises - that no one can predict future course in a superior manner, and no one can buy or sell fast enough to benefit [10].
3) In case "persistent patterns" are found in financial markets data, then these occur no more frequently than the runs of luck, and are thus just a statistical illusion [10].
4) Finally, in case some short-term momentum is indeed found in financial markets data, then any investor who pays transaction costs and taxes is unlikely to benefit from them [10].

Challenges to the EMH:
Behavioral economists argue that the EMH framework fails to account for the variability of market efficiency over time [13,15,18]. They suggest that market efficiency can fluctuate due to human biases, bounded rationality or even irrationality, limited intelligence, suboptimal decision-making, and herding behavior [11,13,15,18]. Furthermore, empirical evidence challenges or even contradicts several key assumptions of the EMH, as pointed out by Professors R. Shiller and R. Thaler, both recipients of Economic Nobel Prizes. Regarding financial markets, and as pointed out by by Harvard Professor A. Shleifer [14] and MIT Professor A. Lo [9] "Inefficiency is the rule, and efficiency is the exception".
In the sequel we briefly outline the key findings that question the EMH:

- Human intelligence is finite and humans are prone to errors, hence Homo Sapiens may opt for suboptimal decisions [2]. Even individuals considered rational may succumb to mistakes when faced with time constraints, as illustrated in chess, where even skilled players make errors under pressure [2].

- Sufficient investor diversity is an essential feature in efficient price formation. In case financial decision rules lose diversity, markets become fragile and likely susceptible to inefficiency [7]. Indeed, and as pointed out by Professor M. Mauboussin, diversity of opinion looks like one of the necessary conditions of a well-functioning market [12]. Unfortunately, imitation is a vital force with Homo Sapiens. Fashions, fads, and traditions are all the result of imitation, and since investing is inherently a social activity, there is every reason to believe that imitation plays a prime role in financial markets as well [12]. This leads to what financial economists describe as herding, i.e. when a large group of investors make the same choice based on the observations of others, independent of their own knowledge and judgment [12]. Such conditions are known to lead towards market inefficiencies [12,17], or even worse may lead to financial bubbles and crashes when the "wisdom of crowds" gets temporarily replaced by the "madness of mobs" [9].

- Human decision-making is not purely rational, as it is often swayed by emotions and cognitive biases [8]. Indeed, characterizing individuals as entirely rational actors solely driven by wealth accumulation, with their preferences perfectly encapsulated in simple formulas called "utility functions", sharply contrasts with the findings of behavioral empirical research [8]. For example short-term loss aversion is known to be an important source of inefficiency [8,12], and stress may exacerbate this characteristic as stress encourages short-term focus. Another well-known bias relates to the so-called affect heuristic, known to determine the "goodness" or "badness" we feel based on a stimulus, which may also result in irrational decision making [8,12]. In addition, and contrary to the "Homo Economicus" model, Professor H.A. Simon (recipient of the 1978 Nobel Prize in Economics) argued that people do not make decisions based on optimal outcomes; people make choices based on what is just good enough. Hence investors do not optimize or maximize, rather they merely just "satisfy" [16].

- Markets may take a long time to absorb and fully price information [11]. Indeed, due to liquidity constraints and market impact considerations, large institutional trades may take several days or even several weeks to be completed. Since institutional trades are staggered over time, the market will absorb the information related to these trades gradually. This slow absorption process means that prices may not fully reflect new information right away.

- Prices have been observed to be statistically efficient without necessarily being fundamentally efficient [4]. As pointed out by the late Professor F. Black [1] "the action of traders who seek to exploit statistical arbitrage lead to martingale prices (i.e. unpredictable prices) that do indeed err away from their fundamental values by large amounts, and for long times". Essentially, on short time scales, the fundamental value is not driving prices, rather the main driver of price changes is the order flow itself [4].

- Price changes are not statistically independent, as price series exhibit long-range and short-term memory. It has been empirically shown that today's action can, at least slightly, affect tomorrow's action [11].

- The non-stationarity of price changes has also been observed, i.e. statistical properties of price changes are not consistently stable over time [11].

- Price changes are very far from following the Bell curve, indeed the distribution tails of price return do not become imperceptible but follow a "power law" [11].

- Price changes are in reality discontinuous and not continuous. Indeed, price changes in financial markets do not occur in a smooth, continuous manner but rather in abrupt, discrete jumps. This discontinuity is far from being an anomaly best ignored, it is a fundamental characteristic of financial markets. This specificity helps set finance apart from the natural sciences where changes are often modeled as continuous processes [11].

- Finally, even the most liquid markets aren't as liquid as they appear, making them more like strategic games of hide and seek between unseen buyers and sellers who must navigate a narrow channel of available liquidity [4]. Hence financial markets have no reason to be efficient [2].

In essence, there is accumulating empirical evidence that brings the EMH picture further and further into question. Moreover, all of the aforementioned findings have the potential to propel financial markets towards periods of bubbles or busts.

The Adaptive Market Hypothesis (AMH):
MIT Professor A. Lo is a prominent pioneer of the Adaptive Market Hypothesis (AMH). From the AMH perspective, the Efficient Market Hypothesis (EMH) is not wrong, it is just incomplete [9]. Financial markets do indeed look efficient under specific circumstances [9,12] when:

1) The investors community is made of a diverse and heterogeneous group of investors, i.e. not being subject to herding behavior.
2) The investors community is made of competing, rational, and profit-maximizing participants.
3) Current information is almost freely and timely available to all.
4) Business conditions remain relatively stable over a long enough period of time, allowing for investors to adapt to these existing conditions.

Under these circumstances financial markets do crystallize the so-called wisdom of the crowds, resulting in efficient markets.

However as observed by Professor A. Lo "An efficient market is simply the steady-state limit of a market in an unchanging financial environment. Such an idealized market is unlikely to ever exist in practice, but it is still a useful abstraction whose performance can be approximated under certain conditions (...). The AMH includes the EMH as a special case, as a theoretical and frictionless limit. In practice, however, this limit is rarely attained, and if it is, it usually does not last very long".

Tales of Outperformance by a few Investment Wizards:
If financial market were constantly efficient, and if asset prices did continuously and fully incorporate all relevant information, then trying to beat the market would be a hopeless task. However, a select group of investors has consistently outperformed the market over extended periods of time, hence challenging the foundations of the EMH.
For example as cited by Professor B. Mandelbrot in [11] "By 1989 Peter Lynch, one of the most successful investment managers, had guided Fidelity's Magellan Fund to beat the market index in eleven out of thirteen years. For its first seven years, when it was still a small fund, Magellan beat the market by an average 25% a year. The odds of that occurring by dumb luck are less than one in 10,000, far beyond the bounds of luck in an efficient market".
Another notable instance is given by the Medallion Fund, the flagship of Jim Simons' hedge fund (Renaissance Technologies), which boasted an impressive average annual return of 66.1% gross (39.1% after fees) during the period from 1988 to 2018 [19].

Conclusion:
The EMH has had a huge impact on the financial industry. The EMH was responsible for the emergence of the index mutual fund business, now a multi-trillion dollar sector of the financial industry, and still growing robustly. As emphasized in [5], the Efficient Market Hypothesis (EMH) is a very useful concept that provides an excellent starting point for developing financial market theories.
While the wisdom of crowds does exist, and financial markets are likely to often be near informationally efficient, it is also important to acknowledge that market inefficiencies do exist during specific conditions as Homo Sapiens is not Homo Economicus. Humans are neither entirely rational nor entirely irrational. In essence, and as pointed out by Professor A. Lo, a fully efficient market is an idealized market, unlikely to ever exist in practice [9]. A fully efficient market may be seen as simply the steady-state limit of a market in an unchanging financial environment [9]. Another way to look at this topic is by observing that financial markets, on aggregate, are likely efficient but one may still discover pockets of inefficiencies from time to time, as indicated by various studies [5].
While the EMH remains a fundamental concept in financial theory, it is no more than a hypothesis! As pointed out by Professor B. Mandelbrot "Many a grand theory has died under the onslaught of real data" [11]. There are two elements that play a particular role around the long-standing EMH debate. First as pointed out by Professor B. Mandelbrot "Compared to other disciplines, economics tends to let its theory gallop well ahead of its evidence" [11]. In other words, economists may develop and rely on theories before there is sufficient real-world data to validate or challenge these ideas, leading to a potential disconnect between economic theory and actual market behavior. This is also similar in spirit to Profesor D. Kahneman famous quote "Economists think about what people ought to do. Psychologists watch what they actually do". Second, and unfortunately, the EMH has "become an article of faith for many economists, it has hardened into a tenet of dogma (...), and departing from this paradigm was deemed heresy." as pointed out by Professor A. Lo [9].
Summarizing, although the EMH does provide a useful framework for understanding market dynamics, it is also essential to recognize its limitations and, where applicable, consider alternative theories that may better capture the intricacies of financial markets.


Explore Linear Metrics on the Best Fin Investment Dashboard:


Explore Also Non-Linear Metrics on the Best Fin Investment Dashboard:


References:

[1] Black F., "Noise", The Journal of Finance, vol. 41, issue 3, pp. 528-543, 1986.
[2] Bouchaud J.P., "The endogenous dynamics of markets: price impact, feedback loops and instabilities", Lessons from the credit crisis, pp.345-74, 2011.
[3] Bouchaud J.P., "Viewpoints on emergent phenomena in non-equilibrium systems", Talk at Higgs Centre for Theoretical Physics, 2014.
[4] Bouchaud J.P., Bonart J., Donier J., Gould M., "Trades, Quotes and Prices: Financial Markets Under the Microscope", Cambridge University Press, 2018.
[5] Bouchaud J.P., Doyne Farmer J., Lillo F., "How markets slowly digest changes in supply and demand", In Handbook of Financial Markets: Dynamics and Evolution, Chapter 2, 2009.
[6] Cont R., "Empirical properties of asset returns: stylized facts and statistical issues", Quantitative Finance, vol. 1, issue 2, pp. 223-236, 2001.
[7] Fama E.F., "Efficient capital markets: a review of theory and empirical work", vol. 25, issue 2, pp.383-417, Journal of Finance, 1970.
[8] Kahneman D., "Thinking, Fast and Slow", Farrar, Straus and Giroux, 2013.
[9] Lo A.W., "Adaptive Markets: Financial Evolution at the Speed of Thought", Princeton University Press, 2019.
[10] Malkiel B.G., "A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing", W.W. Norton & Company, 2020.
[11] Mandelbrot B., Hudson R.L., "The (Mis)Behaviour of Markets: A Fractal View of Risk, Ruin and Reward", Profile Books Ltd , 2008.
[12] Mauboussin M.J., "More Than You Know: Finding Financial Wisdom In Unconventional Places", Columbia University Press, 2013.
[13] Shiller R.J., "Do stock prices move too much to be justified by subsequent changes in dividends?", The American Economic Review, vol. 71, issue 3, pp. 421-436, 1981.
[14] Shleifer A., "Inefficient Markets: An Introduction to Behavioral Finance", Oxford University Press, 2000.
[15] Shleifer A., Summers L.H., "The noise trader approach to finance", The Journal of Economic Perspectives, vol. 4, issue 2, pp. 19-33, 1990.
[16] Simon H.A., "Rational choice and the structure of the environment", Psychological Review, vol. 63, issue 2, pp. 129-138, 1956.
[17] Smith V.L., "An Experimental Study of Competitive Market Behavior", J. of Political Economy, vol. 70., issue 3, pp. 111-137, 1962.
[18] Thaler R.H., "Misbehaving: The Making of Behavioral Economics", W.W. Norton, 2015.
[19] Zuckerman G., "The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution", Penguin, 2019.



Books from the References Section:

Explore the books that inspired the insights in this blog. These carefully selected readings delve deeper into the topics we have referenced, offering valuable knowledge and perspectives.


Additional Reads on Human Behavior and Behavioral Finance:

Dive deeper into the fascinating world of behavioral science and behavioral finance. The following books provide a comprehensive look at how human behavior influences financial and investment decisions, offering valuable insights for investors and decision-makers alike.