Abstract
The claimed performance of new trading strategies often looks too good to be true—and indeed, in many cases, the good performance is a result of data mining. When implementing the strategy in the real world, practitioners routinely make some corrections to the backtests by haircutting the Sharpe ratio by 50%. If a large number of strategies have been tested and a modest Sharpe ratio resulted, one should haircut the result to zero. But if a strategy is truly outstanding, why decrease the Sharpe ratio by a full 50%? “In that case, it seems more reasonable to take just a little off the top,” <b>Cam Harvey</b> says in an interview with <b>Institutional Investor Journals</b>. <b>TOPICS:</b>Statistical methods, portfolio management/multi-asset allocation
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