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Market Anomaly occurs when returns are systematically predictable

Market anomalies represent price

Market anomalies suggest technical
trading strategies.
A market anomaly is something that deviates from the efficient market hypothesis. Most evidence suggests anomalies are not violations of market efficiency but are due to the methodologies used in anomaly research, such as data mining or failing to adjust adequately for risk.


Time Series Anomalies (Calendar, Momentum overreaction)

Calendar anomalies
– Predictable returns based on dates or
times. Ex January Effect - The January Anomaly is most likely the result of tax induced trading at year end. An investor can profit by buying stocks in December and selling them during the first week in January.
• Momentum and overreaction anomalies
– Predictable returns based on past returns.
Momentum- Price changes tend to persist
Overreaction - Price reacts too much to certain types of information
Underreaction - Price reacts too little to certain types of information
Which of the following statements best describes the overreaction effect?Low returns over a three-year period are followed by high returns over the following three years. If the momentum effect persists over time, it would provide evidence against which of the following forms of market efficiency?: Both weak form and semistrong form. - The momentum effect suggests it is possible to earn abnormal returns using market data. All three forms of market efficiency (weak form, semistrong form, and strong form) assume that market prices fully reflect market data.

The overreaction effect refers to stocks with poor returns over three to five-year periods that had higher subsequent performance than stocks with high returns in the prior period. The result is attributed to overreaction in stock prices that reverses over longer periods of time. Stocks with high previous short-term returns that have high subsequent returns show a momentum effect.


Cross-sectional Anomalies
• Size effect—Small firms outperform
large firms.
• Value effect—Value firms outperform
growth firms.

Anomalies that have been identified in cross-sectional data include a size effect (small-cap stocks outperform large-cap stocks) and a value effect (value stocks outperform growth stocks).


Other Anomaly Examples
• Closed end fund discount—Closed end
funds trade at a discount to their net
asset values.
– Generally explained by high management
fees relative to performance.
• Earnings surprise—slow adjustment to
• Initial Public Offerings—Newly issued
firms tend to underperform.

Other identified anomalies involve closed-end investment funds selling at a discount to NAV, slow adjustments to earnings surprises, investor overreaction to and long-term underperformance of IPOs, and a relationship between stock returns and prior economic fundamentals.


Anomalies in General

Anomalies that have been identified in time-series data include calendar anomalies such as the January effect (small firm stock returns are higher at the beginning of January), overreaction anomalies (stock returns subsequently reverse), and momentum anomalies (high short-term returns are followed by continued high returns).

• Anomalies represent violations of market
efficiency because they are predictable.
• Once identified, most anomalies go away,
as would be expected in efficient markets.
• Persistent anomalies must be associated
with limits to trade and with persistent
behavior biases.
• Some anomalies may be returns to
bearing risk.