This paper provides a robust statistical approach to testing the unbiasedness hypothesis in forward exchange market eﬀiciency studies. The methods we use allow us to work explicitly with levels rather than diﬀerenced data. They are statistically robust to data distributions with heavy tails, and they can be applied to data sets where the frequency of observation and the futures maturity do not coincide. In addition, our methods allow for stochastic trend nonstationarity and general forms of serial dependence. The methods are applied to daily data of spot exchange rates and forward exchange rates during the 1920’s, which marked the ﬁrst episode of a broadly general floating exchange rate system. The tail behavior of the data is analyzed using an adaptive data-based method for estimating the tail slope of the density. The results conﬁrm the need for the use of robust regression methods. We ﬁnd cointegration between the forward rate and spot rate for the four currencies we consider (the Belgian and French francs, the Italian lira and the US dollar, all measured against the British pound), we ﬁnd support for a stationary risk premium in the case of the Belgian franc, the Italian lira and the US dollar, and we ﬁnd support for the simple market eﬀiciency hypothesis (where the forward rate is an unbiased predictor of the future spot rate and there is a zero mean risk premium) in the case of the US dollar.
Phillips, Peter C.B.; McFarland, James W.; and McMahon, Patrick C., "Robust Tests of Forward Exchange Market Efficiency with Empirical Evidence from the 1920’s" (1994). Cowles Foundation Discussion Papers. 1323.