Daily Exchange Rate Behaviour and Hedging of Currency Risk

Exchange rates typically exhibit time-varying patterns in both means andvariances. The histograms of such series indicate heavy tails. In thispaper we construct models which enable a decision-maker to analyze theimplications of such time series patterns for currency risk management.Our approach is Bayesian where extensive use is made of Markov chainMonte Carlo methods. The effects of several model characteristics(unit roots, GARCH, stochastic volatility, heavy tailed disturbancedensities) are investigated in relation to the hedging decision strategies.Consequently, we can make a distinction between statistical relevanceof model specifications, and the economic consequences from a riskmanagement point of view. The empirical results suggest thateconometric modelling of heavy tails and time-varying means and variances paysoff compared to a efficient markets model. The different ways to measurepersistence and changing volatilities appear to strongly influence thehedging decision the investor faces.