Bootstrapping and bias: The economic costs of misjudging downside risk

The maximum drawdown (MDD), the maximum peak-to-trough loss associated with a series of returns, is a simple but highly important measure for investors with a downside risk budget. This paper compares the performance of three bootstrap simulation methods to estimate the entire distribution of MDDs from various global stock-bond allocations, quantifying the economic costs of biased estimates for three realistic decision-making scenarios. Compared to its benchmarks, the stationary bootstrap of Politis and Romano (1994) leads to the most precise estimates for the MDD which, in turn, helps avoid costly investment errors in portfolio construction and dynamic risk control strategies.