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Momentum Crashes

Last Updated on 10 February, 2024 by Rejaul Karim

Delving into the intricate world of market dynamics, “Momentum Crashes” by Kent D. Daniel and Tobias J. Moskowitz, from Columbia and Yale Universities, unfolds the story of momentum strategies. Published on December 24, 2013, this research investigates the historical success of momentum strategies, characterized by high Sharpe ratios and positive alphas.

However, beneath this success lies a fascinating twist—momentum crashes, negatively skewed returns occurring in panic states amid market declines and increased volatility. The study exposes the partially forecastable nature of these crashes, unveiling the conditions that elevate expected returns in panic states, notably linked to past losers’ option-like payoffs.

Introducing a dynamic momentum strategy, the research doubles the unconditional Sharpe ratio, exploring the correlation between momentum returns in panic states and volatility risk across various markets and time periods.

Abstract Of Paper

Across numerous asset classes, momentum strategies have historically generated high Sharpe ratios and strong positive alphas relative to standard asset pricing models. However, the returns to momentum strategies are negatively skewed: they experience infrequent but strong and persistent strings of negative returns. These momentum crashes are partly forecastable. They occur in what we term “panic” states – following market declines and when market volatility is high, and are contemporaneous with market “rebounds.” We show that the low exante expected returns in panic states result from a conditionally high premium attached to the option-like payoffs of past losers. An implementable dynamic momentum strategy based on forecasts of each momentum strategy’s mean and variance generates an unconditional Sharpe ratio approximately double that of the static momentum strategy. Further, we show that momentum returns in panic states are correlated with, but not explained by, volatility risk. These results are robust across eight different markets and asset classes and multiple time periods.

Original paper – Download PDF

Here you can download the PDF and original paper of Momentum Crashes.

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Author

Kent D. Daniel
Columbia University – Columbia Business School, Finance; National Bureau of Economic Research (NBER)

Tobias J. Moskowitz
Yale University, Yale SOM; AQR Capital; National Bureau of Economic Research (NBER)

Conclusion

In conclusion, the extensive analysis of Momentum Crashes reveals a nuanced perspective on momentum strategies across diverse asset classes. While historically showcasing remarkable Sharpe ratios and positive alphas, these strategies exhibit a noteworthy characteristic – momentum crashes.

These crashes, characterized by sporadic but intense strings of negative returns, are not arbitrary; they demonstrate forecastability, particularly in what the authors term “panic” states. These states coincide with market declines and elevated volatility, aligning with market rebounds. The study introduces a dynamic momentum strategy, incorporating forecasts of mean and variance, yielding an unconditional Sharpe ratio nearly twice that of static momentum strategies.

Importantly, momentum returns in panic states exhibit a correlation with, though not explained by, volatility risk, underscoring the multifaceted nature of momentum phenomena across various markets and timeframes.

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FAQ

Q1: What distinguishes momentum crashes, as discussed in the research, from the overall success of momentum strategies?

The study identifies momentum crashes as negatively skewed returns within momentum strategies. These crashes are characterized by infrequent but intense strings of negative returns, occurring notably in “panic” states—periods following market declines and characterized by heightened market volatility. This feature contrasts with the historical success of momentum strategies, known for high Sharpe ratios and positive alphas.

Q2: How does the research explain the forecastability of momentum crashes, and what conditions contribute to their occurrence?

Momentum crashes are shown to be partly forecastable, occurring in panic states that follow market declines and coincide with market rebounds. The study reveals that the low expected returns in panic states result from a conditionally high premium attached to the option-like payoffs of past losers. This forecastability provides insights into the dynamics of momentum crashes and their link to specific market conditions.

Q3: What innovative approach does the research introduce to enhance momentum strategy performance, and what are the key findings regarding this dynamic strategy?

The research introduces a dynamic momentum strategy that incorporates forecasts of each momentum strategy’s mean and variance. This dynamic approach substantially improves the unconditional Sharpe ratio, nearly doubling that of static momentum strategies. The authors explore the correlation between momentum returns in panic states and volatility risk across various markets and time periods, offering a more nuanced and effective perspective on managing momentum strategies.

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