Exchange Rate Volatility Forecasting: a Multivariate Realized-GARCH Approach

We propose a model of exchange rates that jointly models associated re-alized measures of volatility and covariances within the Realized GARCH framework. The proposed model exploits identities arising from no arbitrage conditions, that facilitates a relatively parsimonious modeling of a panel of exchange rates. The model shares the simplicity of GARCH models while taking advantage of realized volatility measures that are computed from high-frequency (intraday) data. The latter leads to a better modeling of the vari-ances and covariances, by providing a flexible modeling of their dynamic properties. The model easily produce forecasts at any horizon. The model is illustrated with an empirical application for exchange rates between the currencies: EUR, USD and JPY. An out-of-sample comparison shows that the proposed model dominates conventional benchmark models, in particular at shorter horizons