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Momentum and the cross-section of stock volatility

Journal: Journal of Economic Dynamics and Control

Date: 2022

Author: Minyou Fan, Fearghal Kearney, Youwei Li, Jiadong Liu

Abstract:
Recent literature shows that momentum strategies exhibit significant downside risks over certain periods, called momentum crashes. We find that high uncertainty of momentum strategy returns is sourced from the cross-sectional volatility of individual stocks. Stocks with high realised volatility over the formation period tend to lose momentum effect. We propose a new approach, generalised risk-adjusted momentum (GRJMOM), to mitigate the negative impact of high momentum-specific risks. GRJMOM is proven to be more profitable and less risky than existing momentum ranking approaches across multiple asset classes, including the UK stock, commodity, global equity index, and fixed income markets.

Link: Google Scholar

Background and Context

Research Motivation

Momentum strategies experience increased volatility and crash risks during specific periods, particularly when markets rebound from panic states.

Study Coverage

Analysis covers multiple markets including UK stocks (1965-2018), commodities, global equity indices, and fixed income securities.

Methodology

Develops a generalized risk-adjusted momentum (GRJMOM) approach that adjusts returns by volatility to reduce momentum-specific risks.

High Volatility Stocks Show Weaker Momentum Effect

  • Shows momentum returns across different volatility deciles in UK stocks
  • High volatility stocks (D9-D10) show weak or negative momentum returns
  • Lower volatility deciles (D1-D8) demonstrate consistent positive momentum returns

GRJMOM Outperforms Traditional Momentum Strategies

  • GRJMOM achieves higher returns and Sharpe ratios than traditional strategies
  • Shows significant improvement in risk-adjusted performance
  • Demonstrates effectiveness of volatility adjustment in momentum strategies

Reduced Maximum Drawdown Risk Using GRJMOM

  • GRJMOM significantly reduces maximum drawdown compared to traditional strategies
  • Shows improved risk management during market stress periods
  • Demonstrates better downside protection for investors

Superior Performance During Crash Periods

  • Shows performance during major market crash periods
  • GRJMOM significantly outperforms during market stress
  • Demonstrates effective crash risk mitigation

Excess Volatility Reduction Across Markets

  • Shows reduction in excess volatility across different asset classes
  • GRJMOM successfully reduces momentum-specific risks
  • Demonstrates consistency across different markets

Contribution and Implications

  • Introduces a new risk-adjusted momentum strategy that significantly improves performance and reduces crash risks
  • Demonstrates that momentum risks originate from cross-sectional volatility of individual stocks
  • Provides a flexible framework for investors to adjust momentum strategies based on market conditions

Data Sources

  • Momentum Decile Chart: Based on Table 2 showing performance of momentum strategies by volatility decile
  • Performance Comparison: Based on Table 6 showing performance metrics across different strategies
  • Maximum Drawdown: Based on Table 6 MaxDD statistics
  • Crash Period Performance: Based on Table 8 showing performance during worst periods
  • Excess Volatility: Based on Tables 1 and 4 comparing excess volatility across strategies