Dynamic Currency Hedging with Ambiguity

This paper establishes a general relation between investor's ambiguity and non-Gaussianity of financial asset returns. Based on that relation and utilizing a flexible non-Gaussian returns model for the joint distribution of portfolio and currency returns, we develop an ambiguity-adjusted dynamic currency hedging strategy for international investors. We propose an extended filtered historical simulation that combines Monte Carlo simulation based on volatility clustering patterns with the semi-parametric non-normal return distribution from historical data. This simulation allows us to incorporate investor's ambiguity into the dynamic currency hedging strategy algorithm that can numerically optimize an arbitrary risk measure, such as volatility, value-at-risk, or expected shortfall. The out-of-sample back-test results show that, for globally diversified investors, the derived dynamic currency hedging strategy with ambiguity is stable, robust, and highly risk reductive. It outperforms the benchmarks of constant hedging as well as dynamic approaches without ambiguity in terms of lower maximum drawdown and higher Sharpe and Sortino ratios in gross terms and net of transaction costs.