Are Financial Markets Efficient ?

Outline Efficient Market Hypothesis The Theoretical Foundations of Efficient Market Hypothesis The Theoretical Challenges to Efficient Market Hypothesis The Empirical Challenges to Efficient Market Hypothesis

Efficient market hypothesis (EMH) Fama (1970)：An efficient market is the one in which security prices always fully reflect the available information. It rules out the possibility of trading system based only on currently available information that have expected returns in excess of equilibrium expected returns. This hypothesis received an enormous theoretical and empirical success in the first decades after its conception in the 1960s.

Efficient market hypothesis (EMH) In efficient markets, prices reflect fundamental value, namely “prices are right”. There is “no free lunch” in an efficient market. In other words, no investment strategy can earn excess risk-adjusted average returns, or average returns greater than are warranted for its risk.

Efficient market hypothesis (EMH) Fama distinguishes between three types of information. Past prices (returns): Weak-form efficiency. Under the assumption of risk neutrality, this version of EMH reduces to random walk hypothesis, a statement that stock returns are entirely unpredictable based on past returns. Public available information: Semi-strong efficiency. Event study (Fama et al., 1969), Keown and Pinkerton (1981). Inside information: Strong-form efficiency.

The theoretical foundations of EMH F1: Investors are assumed to be rational and hence to value securities rationally. F2: To the extent that some investors are not rational, their trades are random and therefore cancel each other out without affecting prices. F3: To the extent that investors are irrational in similar ways, they are met in the market by rational arbitrageurs who eliminate their influences on prices.

The theoretical foundations of EMH Investor rationality implies the impossibility of earning superior risk-adjusted returns. Milton Friedman (1953) and Fama (1965): Arbitrage The process of arbitrage brings security prices in line with their fundamental values even when some investors are not fully rational and their demands are correlated, as long as securities have close substitutes.

The theoretical challenges to EMH C1: It is difficult to sustain the case that people in general, and investors in particular, are fully rational. C2: The psychological evidence shows precisely that people does not deviate from rationality randomly, but rather most deviate in the same way. C3: In contrast to EMH, behavior finance states that real-world arbitrage is risky and therefore limited.

The theoretical challenges to EMH The building block of behavior finance : Psychology (irrationality) Many experiments find that people deviate from fully rationality, including the biases in forming belief and in making decisions (preference especially).

The theoretical challenges to EMH The building block of behavior finance : Limits to arbitrage When an asset price deviates from its fundamental value, it’s not necessarily true that an attractive investment opportunity is created. Strategies designed to correct the mispricing can be both risky and costly, rendering them unattractive.

The theoretical challenges to EMH Fundamental risk : The effectiveness of arbitrage relies crucially on the availability of close substitutes for securities whose price is potentially affected by noise trading. Since substitute securities are rarely perfect, and often highly imperfect, fundamental risk remains a significant deterrent to arbitrage.

The theoretical challenges to EMH Noise Trader Risk : De Long et al. (1990a), Shleifer and Vishny(1997) Noise trader risk is the risk that the mispricing being exploited by the arbitrageur worsens in the short run. This risk can force arbitrageurs to liquidate their positions early, bringing them potentially steep losses. Implementation Costs : The transaction costs in implementing the arbitrage can make it less attractive to exploit a mispricing (short-selling constraints, the cost of finding and learning about a mispricing, as well as the cost needed to exploit it).

The empirical challenges to EMH Weak-form EMH Even Fama (1991) admits that stock returns are predictable from past returns. Long-term Reversals : De Bondt and Thaler (1985) They group stocks by their prior three-year cumulated returns and form two portfolios: “winner” and “loser” portfolio. They find that over the three years subsequent to their formation, the average return of the loser portfolio is higher than the average return of the winner portfolio by almost 8 percent per year.

The empirical challenges to EMH Momentum : Jegadeesh and Titman (1993) They group stocks into deciles based on their prior six-month return and compare average return of each decile over the six months after portfolio formation. They find that the biggest prior winner outperforms the biggest prior losers by 10 percent on an annual basis.

The empirical challenges to EMH Semi-Strong form EMH The size premium: Banz(1981), Fama & French(1992) They group stocks into deciles based on their market capitalization, and find that the average return of the smallest stock decile is 0.74 percent per month higher than the average return of the largest stock decile.

The empirical challenges to EMH The value premium: They group stocks into deciles based on their B/M ratio or E/P ratio. They find that the average return of the highest ratio decile (“value” stocks) is higher than the average return of the lowest ratio decile (“growth” stocks). The difference is higher than can be explained through difference in beta. Sometimes these phenomena are called “ the predictive power of scaled-price ratios”.

The empirical challenges to EMH Other related challenges 1. The three puzzles found in U.S aggregate stock market The equity premium puzzle The volatility puzzle The predictability puzzle

The empirical challenges to EMH 2. The evidence supporting that arbitrage is limited. There are only a few cases that the presence of a mispricing can be established beyond any reasonable doubt. Fama (1970) “joint hypothesis problem”. Twin Shares. The prices of twin shares deviate from their fundamental values. Ex: Royal Dutch and Shell. Index Inclusion. Harris and Gurel (1986) and Shleifer (1986) document that when a stock is added to the S&P 500 index, it jumps in price by an average of 3.5 percent, and much of this jump is permanent.

The empirical challenges to EMH Internet Carve-outs Ex: 3Com sold 5 percent of its initially wholly owned subsidiary Palm Inc. in an IPO. After IPO, Palm shares stood at $95 while 3Com’s price was $81.