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Volatility Weighting Applied to Momentum Strategies

Last Updated on 10 February, 2024 by Rejaul Karim

Delve into the intricate world of financial strategies with “Volatility Weighting Applied to Momentum Strategies.” This upcoming study, penned by Johannes Paulus Du Plessis and Winfried G. Hallerbach, investigates the dynamic use of two forms of volatility weighting – own volatility and underlying asset volatility – applied to momentum strategies across both different assets and over time.

The research combines theoretical insights with empirical data, focusing on the Sharpe ratios of these weighted strategies. Using empirical data from US industry portfolios, it highlights the crucial role of timing and the stabilizing effect of volatility weighting in boosting Sharpe ratios.

The study also introduces a new dispersion weighting scheme, comparing its effectiveness to volatility weighting. Journey into the complex relationship between momentum, trend following, and volatility that shape financial investment strategies.

Abstract Of Paper

We consider two forms of volatility weighting (own volatility and underlying asset volatility) applied to cross-sectional and time-series momentum strategies. We present some simple theoretical results for the Sharpe ratios of weighted strategies and show empirical results for momentum strategies applied to US industry portfolios. We find that both the timing effect and the stabilizing effect of volatility weighting are relevant for the improvement in Sharpe ratios. We also introduce a dispersion weighting scheme which treats cross-sectional dispersion as (partially) forecastable volatility. Although dispersion weighting improves the Sharpe ratio, it seems to be less effective than volatility weighting.

Original paper – Download PDF

Here you can download the PDF and original paper of Volatility Weighting Applied to Momentum Strategies.

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Author

Johannes Paulus Du Plessis
Independent

Winfried G. Hallerbach
Fintelligence CCT; EDHEC Business School – Department of Economics & Finance

Conclusion

In summary, “Volatility Weighting Applied to Momentum Strategies” explores the application of two types of volatility weighting to momentum strategies both across different assets and over time. The research highlights the significant role of timing and the stabilizing effect contributed by volatility weighting in augmenting Sharpe ratios.

Besides, the study introduces a new dispersion weighting scheme treating cross-sectional dispersion as partially predictable volatility. Although this dispersion weighting enhances the Sharpe ratio, it appears less effective than volatility weighting. The findings demystify the complex interplay between momentum, trend following, and volatility that ultimately shape the landscape of financial investment strategies.

The study is a compelling revelation of how these factors mutually influence each other and underscore the necessity to consider them when formulating effective financial strategies. Their work is a significant contribution to the financial field, opening new discussions and potential research directions.

Related Reading:

Risk-Managed Industry Momentum and Momentum Crashes

The Conservative Formula: Quantitative Investing Made Easy

FAQ

FAQ on “Volatility Weighting Applied to Momentum Strategies”

Q1: What is the main focus of the study “Volatility Weighting Applied to Momentum Strategies” by Johannes Paulus Du Plessis and Winfried G. Hallerbach?

A1: The study explores the application of two forms of volatility weighting, namely own volatility and underlying asset volatility, to momentum strategies across different assets and over time. The main focus is on understanding the impact of volatility weighting on the Sharpe ratios of these strategies.

Q2: What are the key empirical findings regarding the application of volatility weighting to momentum strategies?

A2: The study finds that both the timing effect and the stabilizing effect of volatility weighting play a significant role in improving Sharpe ratios for momentum strategies. Empirical results from US industry portfolios indicate that the timing and stabilizing effects contribute to the enhancement of Sharpe ratios.

Q3: Is there a comparison with a dispersion weighting scheme in the study, and what are the findings in this regard?

A3: Yes, the study introduces a dispersion weighting scheme that treats cross-sectional dispersion as partially forecastable volatility. While dispersion weighting improves the Sharpe ratio, the study suggests that it appears to be less effective than volatility weighting in the context of momentum strategies.

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