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Recent computational advances allow investment managers to methodically search through thousands or even millions of potential options for a profitable investment strategy. In many instances, the resulting strategy involves a pseudo-mathematical argument, which is spuriously validated through a simulation of its historical performance (also called(More)
Recent computational advances allow investment managers to search for profitable investment strategies. In many instances, that search involves a pseudo-mathematical argument, which is spuriously validated through a simulation of its historical performance (also called backtest). We prove that high performance is easily achievable after backtesting a(More)
Many investment firms and portfolio managers rely on backtests (i.e., simulations of performance based on historical market data) to select investment strategies and allocate capital. Standard statistical techniques designed to prevent regression overfitting, such as hold-out, tend to be unreliable and inaccurate in the context of investment backtests. We(More)
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