Market Efficiency

Market Efficiency • Performance of portfolio managers • Anomalies • Behavioral Finance as a challenge to the EMH

2. Performance of Portfolio Managers • Implication of the semi-strong form EMH: managers cannot consistently beat the market • Information set of managers: (supposedly) public information • Collectively, U.S. evidence based on this type of tests support the semi-strong form EMH • Issue of survivorship bias

Canadian Evidence • Largest 76 Canadian equity funds from 1988 to 1997, none beat the category average in all ten years • Canadian Investment Review, Fall 2002, “Does Aggressive Portfolio Management Work?” • Market timing test: non-linear regression covered in class • Stock selection ability test: Jensen’s alpha

Performance of Portfolio Managers • Conclusion: no evidence of consistent market-timing or stock-picking abilities • And “past performance is not an indicator of future performance”

3. Anomalies • Exceptions that appear to be contrary to market efficiency • Earnings announcements affect stock prices • Adjustment occurs before announcement, but also significant amount after • Contrary to efficient market hypothesis because the lag should not exist

Anomalies: Examples • Low M/B ratio stocks tend to outperform high M/B ratio stocks • Low M/B portfolios typically have higher risk-adjusted returns (risk measured by  or constant ) • Value investing • Why is it an anomaly? • M/B is public information!

Canadian Evidence(Deaves 2005)

Anomalies: Examples • Size effect • Tendency for small firms to have higher risk-adjusted returns than large firms • January effect • Tendency for small firm stock returns to be higher in January • Half of the size premium can be accounted for in January (known as Small-firm-in-January effect)

Anomalies: Examples Time trend • Evidence of short-term momentum (3-12 month horizon) in stock prices • But evidence of long-term reversal (3-5 year horizon) in winner and loser portfolios

Explanations for Anomalies • Risk Premiums or market inefficiencies? • Data mining or anomalies?

The Value Premium • Risk-based explanation • Relax the assumption in the conventional CAPM that beta and the market risk premium are constant • HML has higher beta when market risk premium is high. Translation: value stocks do not do well in down markets, and hence are riskier to investors (Petkova and Zhang 2005) • Value firms tend to have greater amounts of tangible assets, and hence less flexibility to adjust capacity during downturns (operating risk)

The Value Premium • Behavioral finance explanation: Investors tend to overreact • Growth stocks are glamour stocks • Price bidded up beyond fundamental value • Correction in the long term • Opposite is true for value stocks

4. Behavioral Finance • Behavioral finance: provides an alternative view of financial markets • Challenges the EMH on both theoretical and empirical grounds • Theory: model investor behavior, using theories and observations from the psychology literature • Empirical: existence of anomalies (anomalous from the EMH perspective)

Three Theoretical Challenges • Investors can be irrational • Trade on irrelevant information (noise) • Trade on sentiment • Follow advice of financial gurus • Fail to diversify • Over-active trading

Theoretical Challenges • Irrational investors’ trades are not random • If random and uncorrelated, tend to cancel each other out, so that on average, stock price = fundamental price • Behavioral finance: irrational investors’ trades are positively correlated, and hence move in the same direction • Investor sentiment reflect common judgment errors made by a substantial number of investors • Listen to the same rumours, and imitate neighbours

Theoretical Challenges • There are limits to arbitrage • If there is a significant number of irrational investors, arbitrage is risky • If arbitrageurs are risk-averse, their activities will be limited (fundamental risk, implementation costs, model risk) • Mispricing can exist, particularly in the short term

Market Efficiency