Biases in Detecting Efficient Market Anomalies
A mispricing occurs when the price of a security predictably deviates from its normal or expected return. Persistent mispricings are called anomalies. However, the methods for determining expected return, and of finding anomalies, can introduce bias.
Expected Return
In order to constitute a mispricing, a security must predictably earn a higher or lower return than expected. However, the expected return itself is subjective. If it is improperly measured, an apparent anomaly may be nothing of the sort.
Data Mining
Studying hundreds or thousands of relationships is likely to result in a few that appear significant only due to random chance.
Survivorship Bias
When results are based on existing entities, they may ignore entities that have failed. While the existing fund managers, on average, have outperformed their benchmarks this is because if they had not investors would have withdrawn their funds. Only an examination of all managers, whether failures or successes, can give a true reading.
Small Sample Bias
Patterns observed over a short time period may not repeat in other time periods.
Selection Bias
Some anomalies are affected by a portion of the sample. For example, a certain anomaly may pertain only to small cap stocks. Attempts to exploit the anomaly could fail if not applied to the correct sample.
Nonsynchronous Trading
Stocks that trade less frequently will have price changes that reflect all information since the prior trade. Large swings in the overall market between trades will be masked. The stock may appear less volatile than it actually is.
Risk
Riskier investments should generate higher returns. If the risk estimate is incorrect, an apparent anomaly may simply reflect the correct risk.
For more information, see all articles on: Active Management, Investing in Stocks, Investment Returns, Portfolio Management See also:
The Intelligent Investor: The Classic Text on Value Investing
Financial Statement Analysis: A Practitioner's Guide, 3rd Edition
Managing Investment Portfolios: A Dynamic Process (CFA Institute Investment Series)
