A multivariate generalized ARCH approach to modeling risk premia in forward foreign exchange rate markets
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Assuming that daily spot exchange rates follow a martingale process, we derive the implied time series process for the vector of 30-day forward rate forecast errors from using weekly data. The conditional second moment matrix of this vector is modelled as a multivariate generalized ARCH process. The estimated model is used to test the hypothesis that the risk premium is a linear function of the conditional variances and covariances as suggested by the standard asset pricing theory literature. Little supportt is found for this theory; instead lagged changes in the forward rate appear to be correlated with the 'risk premium.'. © 1990.
Published Version (Please cite this version)10.1016/0261-5606(90)90012-O
Publication InfoBaillie, RT; & Bollerslev, T (1990). A multivariate generalized ARCH approach to modeling risk premia in forward foreign exchange rate markets. Journal of International Money and Finance, 9(3). pp. 309-324. 10.1016/0261-5606(90)90012-O. Retrieved from https://hdl.handle.net/10161/1970.
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Juanita and Clifton Kreps Distinguished Professor of Economics, in Trinity College of Arts and Sciences
Professor Bollerslev conducts research in the areas of time-series econometrics, financial econometrics, and empirical asset pricing finance. He is particularly well known for his developments of econometric models and procedures for analyzing and forecasting financial market volatility. Much of Bollerslev’s recent research has focused on the analysis of newly available high-frequency intraday, or tick-by-tick, financial data and so-called realized volatility measures, macroeconomic news annou