Quantifying Backtest Overfitting in Alternative Beta Strategies

Antti Suhonen, Matthias Lennkh, Fabrice Perez

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)


We investigate the biases in the backtested performance of “alternative beta” strategies using a unique sample of 215 trading strategies developed and promoted by global investment banks. Our results lend support to the cautions in recent literature regarding backtest overfitting and lack of robustness in trading strategy performance during the ”live” period (out of sample). We report a median 73% deterioration in Sharpe ratios between backtested and live performance periods for the strategies, and establish a link between performance deterioration and strategy complexity, with the realized reduction in live vs. backtested Sharpe ratios of the most complex strategies exceeding those of the simplest ones by over 30 percentage points. The robustness of strategy exposure to risk factors varies between asset classes and strategies, and appears reasonable in equity volatility and FX carry strategies, but quite weak in the equity value strategy in particular.
Original languageEnglish
Pages (from-to)90-104
Issue number2
Publication statusPublished - 2017
MoE publication typeA1 Journal article-refereed


  • Alternative beta
  • Smart beta
  • Risk premia
  • Risk factor
  • Factor investing
  • Trading strategies
  • Index strategies
  • Investment strategies
  • Quantitative investment strategies
  • QIS
  • Sharpe ratio
  • Backtest
  • Overfitting
  • Data mining
  • Multiple test


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