The momentum anomaly in the stock market refers to the phenomenon where stocks that have performed well in the past continue to perform well in the near future, and those that have performed poorly continue to underperform. Momentum strategies exploit this anomaly by buying stocks with high past returns and selling those with low past returns, often leading to outperformance.
Despite its historical success, the momentum anomaly remains a subject of extensive research and debate regarding its persistence and underlying causes. Reference [1] challenges many claims made by pro-momentum researchers. The author pointed out,
This study tests whether RMVs are governed by power laws. In doing, various RMV data frequencies were analyzed. The general findings of this study indicate that regardless of the methodology used to estimate power-law exponents, the power-law null hypothesis cannot be rejected. Testing for invariance shows that power-law behavior is present across all time frequencies…
Surprisingly, the empirical outcome documented here suggests rather the opposite; that is, the lower the time frequency, the more extreme events can be expected in the variance processes, which is empirically manifested in a lower economic magnitude of the power-law exponent. Overall, the results of this study show that the risk for the momentum strategy is infinite, which is empirically manifested in power-law exponents of α < 2 which has, in turn, some serious consequences. First, in finite samples, we do not observe the time-honored, pervasive “momentum premium,” which is documented to correspond to 1% per month across various otherwise unrelated asset classes; second, the momentum premium does not have a defined t-statistic regardless of time frequency. The claim raised by many scholars in numerous momentum studies published in leading finance outlets that “the momentum premium exhibits a statistically significant t-statistic” is therefore invalid. Moreover, other metrics incorporating variances or functions of it, such as Sharpe ratios, are not defined either for this investment vehicle.
Basically, the author studied the scaling behaviour of realized momentum variances (RMV) of momentum portfolios. He concluded that momentum risk is infinite regardless of the data frequency, implying that (i) t-statistics for this strategy do not exist, (ii) correlation-based metrics such as Sharpe ratios do not exist either, and (iii) the momentum premium is not observable in reality.
This article refutes many research findings in momentum literature. It will have significant implications for the design of momentum strategies.
Let us know what you think in the comments below or in the discussion forum.
References
[1] Klaus Grobys, Science or scientism? On the momentum illusion, Annals of Finance, 2024
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