Profitability of Momentum Strategies: An Evaluation of Alternative Explanations

Motivation(s)

Momentum strategies earn profits of about one percent per month for the following year through buying stocks with high returns over the previous three to twelve months and selling stocks with poor returns over the same time period. Due to a lack of data, several theories have emerged in an attempt to explain the source of the profits; they can categorized under

  • Behavior Model: Market Inefficiency

    • Representative Heuristic

      • The tendency of individuals to identify an uncertain event, or a sample, by the degree to which it is similar to the parent population.

      • In the context of stocks, investors mistakenly conclude that firms realizing extraordinary earnings growths will continue to experience similar extraordinary growth in the future.

      • When coupled with conservatism bias, the idea that individuals underweight new information in updating their priors, this behavioral tendency can lead to long horizon negative returns despite previously high returns.

    • Self-attribution Bias

      • Overconfident investors push up the prices of the winners above their fundamental values.

      • The delayed overreaction in this model leads to momentum profits that are eventually reversed as prices revert to their fundamentals.

    • Partial Information

      • Informed investors (i.e. news watchers) obtain signals about future cash flows but ignore information in the past history of prices.

      • Technical traders extrapolate based on past prices without observing fundamental information and tend to push prices of past winners above their fundamental values.

      • The partial incorporation of information contributes to market underreaction resulting in momentum profits; return reversals occur when prices eventually revert to their fundamentals.

  • Rational Model: Compensation for Risk / Product of Data Mining

    • Stock prices follow random walks with drifts, and the unconditional drifts vary across stocks.

    • The differences in unconditional drifts across stocks explain momentum profits.

    • Predicts that the stocks on the long side of the momentum portfolio should continue to outperform stocks on the short side by the same magnitude in any postranking period.

Proposed Solution(s)

The authors propose evaluating the various explanations using out-of-sample tests on the additional data collected over the past nine years. The advantage of an out-of-sample test is that it significantly reduces the number of strategies that researchers can potentially search over, thus increasing the informativeness of the tests.

Evaluation(s)

The dataset consisted of all stocks traded on the NYSE, AMEX, and Nasdaq. Stocks priced below $5 were excluded to ensure the results are not driven primarily by small and illiquid stocks or by bid-ask bounce.

Following Jegadeesh and Titman (1993), the stocks are ranked at the end of each based on their past six-month returns and then grouped into 10 equally weighted portfolios based on these ranks. Each portfolio was held for six months following the ranking month.

The monthly positive returns in the first twelve months following the formation period over the 1965 to 1989 sample period confirms the results in Jegadeesh and Titman (1993). However, the January momentum profits are significantly smaller than the momentum profits in other calendar months in all sample periods. Both winners and losers tend to be smaller firms than the average stock in the sample because smaller firms have more volatile returns and are thus more likely to be in the extreme return sorted portfolios. The average size rank for the winner portfolio is larger than that for the loser portfolio, and the market betas for winners and losers are virtually equal.

More evidence in favor of behavioral theories can be found in the negative cumulative return in the post-holding period (months thirteen to sixty). The evidence here indicates that the losers as well as winners experience negative abnormal returns in years two through five; this contradicts the idea that the momentum in loser returns is generated as a result of positive feedback trading that is later reversed. One can also rest assured that the momentum profits are not entirely due to data snooping biases.

The analysis presented in this paper should be treated with caution because the evidence of negative postholding period returns tends to depend on the composition of the sample, the sample period, and whether the postholding period returns are risk adjusted. At best, the behavioral models provide a partial explanation for the momentum profits.

Future Direction(s)

  • What are some good indicators to estimate the duration of a stock’s momentum?

  • How come index funds fail to achieve the proposed returns?

  • Would including foreign stocks affect the returns?

Question(s)

  • This approach sounds like index funds?

Analysis

Momentum strategies have been shown to yield on average monthly returns of one percent for the following year. The source of the profits can be partially explained through behavioral theories. The analysis should have included graphics alongside the tables since the focus is the trend. Overall, it is good to know that stocks are more consistent with behavior models than rational models.

References

JT01

Narasimhan Jegadeesh and Sheridan Titman. Profitability of momentum strategies: an evaluation of alternative explanations. The Journal of Finance, 56(2):699–720, 2001.