In The Presence of Persistent Market Anomalies Part 1

In The Presence of Persistent Market Anomalies Part 1

Academics are split into two primary schools of thought on financial markets:  Efficient Markets Hypothesis prophytes and Behavioral Finance neophytes. The divisions between the two run deep, and the disagreements can be gravely bitter. At its core, the efficient markets hypothesis believes that rational beings operate within liquid markets with a low degree of information asymmetry. Behavioral finance, on the other hand, is rooted as much in psychology as it is in finance, and as such, views investors as mostly rational, but prone to inherent biases. These biases can then be exploited in order to generate alpha (excess return over the market). But before we can delve into the literature surrounding market anomalies, we need to understand what makes these phenomena anomalous from the general theory.

Efficient Markets Hypothesis has been the dominant theory in finance since the 1960’s, but was actually created by a French mathematician, Benoît Mandelbrot, in the 1900s. EMH states that the three forms of market efficiency are strong, semi-strong, and weak. Each form defines what sorts of information are reflected in a current stock price, and thus, what kinds of analysis cannot be used to predict future performance of that stock. The fundamental assumption is that financial markets are information efficient. It’s not that every investor knows everything about a stock. It’s that there are enough people who do know the information to price the stock correctly (a la The Wisdom of Crowds) or that arbitrageurs have taken a large enough contrary position to correct the stock price. Now, we need to understand the varying degrees/forms of information efficiency.

Weak-form efficiency describes current prices as reflecting all market data, meaning that past prices, trading volume, and stock price movements (technical analysis) cannot be used to predict future performance. We may, however, use corporate strategy, financial statements, and industry analysis to predict that a stock may perform better relative to its peers or the market (fundamental analysis). We could also achieve abnormal returns if we obtained inside information from a firm manager, supply chain executive, etc. It’s worth noting that this last “if” is illegal, and punishable by jail time and monetary fines from the SEC.  

Semi-strong form goes one step further than weak, and says that current stock prices reflect all public information about the stock, past and present. This means that fundamental analysis cannot be used to find excess returns, as all quantitative and qualitative information is incorporated. Stock price movements, trading volume, corporate strategy, financial statements; everything public is incorporated into the current stock price.

Finally, strong form believes all information, public and private, is incorporated in current stock prices, which means that no investor can consistently achieve excess returns over the market. This viewpoint would believe that even private information from firm managers could not be used to achieve abnormal returns over the market. It’s worth noting that these three forms all essentially recommend investing in passively managed index funds, like the S&P500 or the Russell 1000, which track overall market performance for better or worse.  

We can observe significant evidence that markets are efficient. Warren Buffett recently declared victory in his bet that the best hedge fund managers couldn’t “beat the market” in raw returns over a 10 year period. We could say that Warren Buffett beats the market consistently, but his performance has declined (slightly) in the past 6 years. This might indicate that on a long enough timeline the market will win; only time will tell. We’ve also seen numerous penalties and jail sentences handed out to investors for insider trading violations, or the use of private/non-public information to reap financial benefits (check out the SEC website listed below for examples). These cases point to financial markets being somewhere between semi-strong and strong form efficient.

However, in the late 1970s, Richard Thaler began documenting anomalies in financial markets, pricing occurrences that should not exist if markets are efficient. Combining psychology and finance, he became known as the father of behavioral finance, and from there, many researchers began to search for cases where investors en masse behaved irrationally. Some are well-known, like the “January effect”, discovered in 1977. This is the idea that investors, trying to minimize their tax bill, sell-off stocks in December, lowering prices. Then, many buy back the stocks in January, or use their year-end bonuses to immediately invest, raising prices. This led to a simple strategy of buying in December and selling in January, earning an abnormal return with no extra risk. Newer empirical research has mixed results on the continued existence of this behavioral tick, potentially because arbitrageurs are aware of it (and thus exploit it, driving alpha to zero). There are also anomalies that are less well-known to everyday investors, like the Momentum Effect, Stock-Split Signaling, and the Accruals Anomaly, among others. However, the simple fact that these anomalies can persist over decades indicates that markets do not always behave rationally and efficiently. So, in order to better understand financial markets, behavioral economists believe we need to better understand what motivates investors to make investing decisions in the first place.  

Now, we know that markets are supposed to be efficient, making it impossible to achieve abnormal or excess returns over the long run. We also know that there are persistent anomalies that go against this conventional wisdom, allowing investors to deploy simple strategies to generate alpha. These strategies not only exploit the market for excess returns, but also teach us how to be more discerning in our investing rationales. In the next article, we’re going to examine a few market anomalies that academics have identified, and that still persist in today’s markets.

 

Sources:

“Efficient Market Hypothesis.” Morningstar.com, www.morningstar.com/InvGlossary/efficient_market_hypothesis_definition_what_is.aspx.

Financial Times. “Lex Live: Inefficient Markets and Mandelbrot.” Financial Times, Financial Times, 18 Oct. 2010, www.ft.com/video/c4955fb1-810f-3070-b750-e8726e7566c2.

Malkiel, Burton Gordon. A Random Walk Down Wall Street. Norton, 1973.

Malkiel, Burton G., and Eugene F. Fama. “EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*.” Freshwater Biology, Wiley/Blackwell (10.1111), 30 Apr. 2012, onlinelibrary.wiley.com/doi/full/10.1111/j.1540-6261.1970.tb00518.x.

Neufeld, Dorothy. “Who Is Richard Thaler, Economics Nobel Prize Winner?” Investopedia, Investopedia, 9 Oct. 2017, www.investopedia.com/articles/investing/102715/richard-thaler-founding-father-behavioral-finance.asp.

Patel, Jayen B. “The January Effect Anomaly Reexamined In Stock Returns.” Journal of Applied Business Research (JABR), 31 Dec. 2015, search.proquest.com/openview/e4b81d8ee8b79abc98b35abcb227f24e/1?pq-origsite=gscholar&cbl=30135.

“SEC Enforcement Actions: Insider Trading Cases.” SEC.gov, 1 June 2011, www.sec.gov/spotlight/insidertrading/cases.shtml.

Sommer, Jeff. “Warren Buffett's Awesome Feat at Berkshire Hathaway, Revisited.” The New York Times, The New York Times, 7 Mar. 2015, www.nytimes.com/2015/03/08/your-money/warren-buffetts-awesome-feat-at-berkshire-hathaway-revisited.html.

Staff, Motley Fool. “Warren Buffett's Big Bet.” The Motley Fool, The Motley Fool, 15 Mar. 2017, www.fool.com/investing/2017/03/15/warren-buffetts-big-bet.aspx.

 

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