Volatility-Adjusted ETF Momentum

[WITH CODE] Investigating the performance of traditional momentum and volatility-adjusted momentum

Hello!

Today’s post is a deep dive into an underappreciated yet highly practical refinement in systematic investing: volatility-adjusted momentum. While traditional momentum strategies rank assets based on raw returns over a past period, volatility-adjusted momentum modifies this signal by dividing returns by the volatility over the same lookback window.

In other words, it favors high-return assets that achieved those returns with lower volatility. In this post, I explore how this adjustment performs in practice across various lookback and holding periods, using a ETF universe. Backtested Sharpe ratios rise above 1 in multiple scenarios.

Importantly, this is not a pure replication of an academic paper. Instead, it builds on the ideas presented in the November 2024 paper "Shades of Momentum: Alternative Momentum Metrics and their Dissipation in Indian Equities" by Rajan Raju (highlighted in this Recent Academic Research post). The author finds that volatility-adjusted momentum delivers the highest Sharpe ratio. These findings influenced how I tested and interpreted the strategies presented here.

This post is for paid subscribers only, and it includes:

• A clear explanation of both momentum types

• Backtested results across multiple lookback and holding periods

• Strategy comparisons, with insights on when each works best

• Excel data download

Let’s get into it.