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Momentum Crash Management

Last Updated on 10 February, 2024 by Rejaul Karim

Exploring the captivating landscape of market anomalies, “Momentum Crash Management” by Mahdi Heidari, emanating from the Stockholm School of Economics, investigates the intricate phenomenon of momentum crashes.

Unveiling on March 15, 2015, with revisions up to November 11, 2015, the study delves into the pervasive anomaly of momentum, renowned for its substantial mean and Sharpe ratio, yet plagued by pronounced negative skewness arising from momentum crash periods. These crashes, occurring during both market stress and rebound, become pivotal in predicting momentum. The research introduces two novel momentum predictors, demonstrating their predictability in regression models alongside established predictors.

Beyond prediction, the study pioneers an innovative momentum risk management method, boasting lower transaction costs in terms of both turnover and price impact compared to existing strategies. This investigation not only adds depth to understanding momentum dynamics but also charts a path for more effective risk management strategies in the face of momentum crashes.

Abstract Of Paper

Momentum is one of the largest and most pervasive market anomalies. However, despite a high mean and Sharpe ratio, momentum suffers from large negative skewness that comes from momentum crash periods. These crashes occur in times of both market stress and market rebound and thus variables that capture these episodes, can be used as momentum predictors. Once momentum prediction has been proved, the predictors can be applied to momentum risk management. I introduce two new momentum predictors and show their predictability in single and multiple regression models in the presence of other predictors that have been used before. I then introduce a new method of momentum risk management that has a lower transaction cost than existing methods, both in terms of turnover and price impact.

Original paper – Download PDF

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Author

Mahdi Heidari
Stockholm School of Economics

Conclusion

In conclusion, the study on Momentum Crash Management sheds light on effective strategies for handling the inherent challenges associated with momentum investing, notably the substantial negative skewness caused by momentum crashes.

Acknowledging momentum as a prominent market anomaly, the research introduces novel momentum predictors that prove effective, particularly during market stress and rebound periods. These predictors, integrated into single and multiple regression models alongside existing variables, demonstrate notable predictability.

Importantly, the findings pave the way for a pioneering momentum risk management approach, surpassing existing methods in terms of lower transaction costs, encompassing both turnover and price impact considerations. This innovative framework offers a pragmatic solution to navigate the complexities of momentum investing, enhancing its resilience and performance across various market conditions.

Related Reading:

Momentum Trading, Return Chasing and Predictable Crashes

Momentum Crashes

FAQ

Q1: What is the primary focus of the research paper “Momentum Crash Management”?

The paper explores the phenomenon of momentum crashes, a challenge associated with momentum investing. Despite momentum’s high mean and Sharpe ratio, it suffers from large negative skewness during momentum crash periods. The study investigates these crashes and introduces novel momentum predictors.

Q2: When were the findings of “Momentum Crash Management” first unveiled, and what is the significance of the introduced momentum predictors?

The research was unveiled on March 15, 2015, with revisions up to November 11, 2015. The introduced momentum predictors play a crucial role in predicting momentum, especially during market stress and rebound periods. These predictors contribute to a better understanding of momentum dynamics.

Q3: How does the research contribute to momentum risk management, and what distinguishes the introduced risk management method from existing strategies?

The study pioneers an innovative momentum risk management method. This method is characterized by lower transaction costs, encompassing both turnover and price impact considerations, compared to existing strategies. It offers a pragmatic solution to enhance the resilience and performance of momentum investing across various market conditions.

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