Daily exchange rate behaviour and hedging of currency risk

We construct models which enable a decision-maker to analyze the implications of typical time series patterns of daily exchange rates for currency risk management. Our approach is Bayesian where extensive use is made of Markov chain Monte Carlo methods. The effects of several model characteristics (unit roots, GARCH, stochastic volatility, heavy tailed disturbance densities) are investigated in relation to the hedging strategies. Consequently, we can make a distinction between statistical relevance of model specifications, and the economic consequences from a risk management point of view. We compute payoffs from several alternative hedge strategies. These payoffs indicate that modelling time-varying features of exchange rate returns may lead to improved hedge behaviour within currency overlay management.