Timing Luck in Factor Investing
How robust are your backtests, really?
SUMMARY
- The starting date matters for a backtest
- Annual returns can vary more than 10%, challenging robustness
- Averaging into portfolios can reduce the timing luck
INTRODUCTION
The objective of quantitative investing is to separate skill from luck by applying a rigorous, evidence-based approach to strategy evaluation. In practice, this means conducting backtests over long horizons that span multiple market regimes, using a realistic universe of tradable instruments, incorporating transaction and market impact costs, and validating results through out-of-sample tests or across different markets.
All strategies are sensitive to modeling assumptions, though some are more consequential than others. For example, high-turnover approaches such as statistical arbitrage are particularly exposed to transaction costs, whereas lower-turnover equity strategies like quality investing are less affected, as their underlying fundamentals evolve more slowly.
One assumption that is often overlooked – but still materially important – is deceptively simple: the choice of starting date. In this article, we examine the impact of timing luck, using the momentum factor as a case study.
TIMING LUCK & THE MOMENTUM FACTOR
We construct a long–short momentum index for the U.S. equity market by ranking stocks based on their past 12-month returns, excluding the most recent month. The top 20% form the long portfolio, while the bottom 20% form the short portfolio. The strategy is rebalanced monthly.
The first portfolio is initiated on Monday, February 25, 2002, and additional portfolios are launched on each subsequent trading day. Comparing the performance of the five portfolios formed during the first week reveals remarkably similar trajectories over the roughly 25-year period from 2002 to 2026. Nevertheless, small differences persist: the portfolio initiated on Monday delivers the weakest performance, while the one initiated on Friday performs the best.

