Market anomalies are exceptions to the notion of market efficiency and may be present if a change in the price of an asset or security cannot directly be linked to current relevant information known in the market. Market anomalies are only valid if they are consistent over long periods of time and not the result of data mining, or examining data with the intent of developing a hypothesis. There is much debate if market anomalies truly exist after making appropriate adjustments for risk, transaction costs, sampling errors, and other factors. Market anomalies can be categorized as time-series anomalies, cross-sectional anomalies, or other anomalies.
Time Series Anomalies
- Calendar anomalies: significant differences in returns on different days, months, or years. The most commonly known calendar anomaly is the January effect, in which stocks tend to outperform in the month of January. Part of this effect may be explainable by individual investors or fund managers selling off during the previous December either for tax reasons or to show off impressive end-of-year results.
- Momentum/overreaction: The momentum anomaly refers to the empirically observed tendency for rising asset prices to rise further, and falling prices to keep falling. Stocks with strong past performance continue to outperform stocks with poor past performance in the next period. It is termed an anomaly because in finance theory, an increase in asset price, in and of itself, should not warrant a further increase in asset price unless it is backed up by new information or changes in demand and supply. The momentum anomaly suggests investors should buy past “winners” while selling past “losers.” Students of financial economics have largely attributed the appearance of momentum to cognitive biases, which belong in the realm of behavioral economics.
The overreaction anomaly goes contrary to the momentum anomaly. It refers to the empirically observed tendency of stocks to exhibit long-term reversals in returns. Stocks which have performed poorly in the past three to five years demonstrate superior performance over the next three to five years compared to stocks that have performed well in the past. The overreaction anomaly suggests buying past losers while selling past winners.
Two of the most researched of these anomalies in financial markets are the size effect and value effect. The Fama and French three-factor model (seen in the Portfolio Management section) attempts to adjust for these anomalies.
- Size effect: small companies tend to outperform larger companies. This argument has indeed been validated through historical analysis, at least until the 1980s. Some empirical studies have declared the size effect to be “dead” after the early 1980s.
- Value effect: value stocks, which generally are stocks with below-average price-to-earnings and market-to-book ratios, and above average dividend yields, have consistently outperformed growth stocks. This effect seems to have weakened or disappeared after the papers that highlighted it was originally published.
- Closed-end fund discounts: closed-end funds sometimes sell at a discount to their net asset value, or the price that the fund’s holdings could theoretically be sold for if fully liquidated. Tax inefficiency and expectations of manager underperformance may partially explain this anomaly.
- Earnings surprise: stock prices have a tendency to underreact to new information, allowing for a momentum strategy (buying stocks with recent positive developments and selling stocks with recent negative developments) to be potentially profitable.
- Initial public offerings (IPOs): investors able to purchase a stock at its initial offering price earn excess returns. This is somewhat understandable as investment banks arranging the IPOs are often incentivized to set a low price.
- Prior information: some researchers have found that equity returns relate to prior information like interest rates, inflation rates stock volatility, and dividend yields. However, this is not evidence of a market anomaly as abnormal returns cannot be earned using such information.
What characteristic used for stock screening is the least likely to result in any abnormal profits due to market anomalies?
A. Market capitalization
B. Earnings per share
C. P/E ratio
The correct answer is B.
Screening for stocks with larger market capitalizations and P/E ratios may arguably allow the investor to take advantage of abnormal returns based on cross-sectional anomalies. However, stocks with low/high earnings per share alone (without considering price per share) have not been shown to generate abnormal returns.
Reading 38 LOS 38f:
Describe market anomalies