Maximum Drawdown and Recovery as Momentum and Reversal Signals

Summary

The document tests stock-selection rules based on maximum drawdown and the recovery that follows it. Across various equity markets, portfolios formed from these measures are reported to predict price direction and capture differences in returns across stocks. At monthly horizons, strategies ranked by maximum drawdown outperform other alternative momentum portfolios, including traditional strategies based on cumulative returns. At weekly horizons, recovery-based rules rank stocks most effectively for detecting mean reversion, giving the approach both momentum and contrarian applications at different time scales.

The strategies are also reported to have improved reward-risk profiles, and a Carhart four-factor analysis finds higher factor-neutral intercepts. These results support the authors’ claim of predictive value, but the document does not name the markets, report performance figures, or describe trading costs and implementation. The evidence is empirical and does not establish that the signals will persist outside the tested settings.

Key ideas

• The study tests stock-selection rules using maximum drawdown and subsequent recovery.
• Maximum-drawdown rankings are reported to outperform other alternative momentum portfolios at monthly horizons.
• Recovery-based rankings are reported to detect mean reversion most effectively at weekly horizons.
• The alternative strategies show improved reward-risk measures and higher factor-neutral intercepts in a Carhart four-factor analysis.
• The document does not provide market names, performance figures, or transaction-cost details.

Tags

# Maximum drawdown, recovery, and momentum


# Maximum drawdown, recovery, and momentum









We empirically test predictability on asset price by using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from these alternative selection criteria are superior not only in forecasting directions of asset prices but also in capturing cross-sectional return differentials. In monthly periods, the alternative portfolios ranked by maximum drawdown measures exhibit outperformance over other alternative momentum portfolios including traditional cumulative return-based momentum portfolios. In weekly time scales, recovery-related stock selection rules are the best ranking criteria for detecting mean-reversion. For the alternative portfolios and their ranking baskets, improved risk profiles in various reward-risk measures also imply more consistent prediction on the direction of assets in future. In the Carhart four-factor analysis, higher factor-neutral intercepts for the alternative strategies are another evidence for the robust prediction by the alternative stock selection rules.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.