We have attempted to test the existence of time-varying risk premia in foreign exchange markets under two models that we have developed in this dissertation. This first one is an extension to Lucas's general equilibrium model of international finance. By assumption of the Cobb- Douglas utility function of the consumers we are able to derive a closed form for the risk premia in the foreign exchange markets on the setting of a two-country economy model. We used White's test and Engle's test for homoscedasticity and used White's heteroscedasticity-consistent variance-covariance matrix to derive the correct standard errors. The time varying risk premium is tested jointly with the efficiency of the foreign exchange market, i.e., whether the forward exchange rates are unbiased predictors of the future spot exchange rates. The empirical findings indicate that the notion of market efficiency is rejected and there is no risk premium for any of the three cases we studied. In the monetary approach, however, we test the existence of time- varying risk premia alone. By PPP and an extension to the uncovered interest parity we introduced the risk premia into our monetary approach to foreign exchange rate determination. The forward premium is used as a driving force of the risk premium. A rational expectation hypothesis is made and the forward solution derived. Since it is a non-linear single equation model and there is evidence of heteroscedasticity we used GMM estimators and the corresponding variance-covariance matrix and found that there is constant risk premia in the case of Germany and Japan but not in the case of Canada. We also did an empirical study of monetary model with the formation of risk premium derived before. The findings we have is that there is time-varying risk premium in the case of Germany but not in the cases of Japan and Canada. Since our monetary model relaxes the restriction imposed on the semi-elasticity of interest rate the empirical results are based on a more general setting than most of the monetary models of foreign exchange rates. The conflicting empirical results from the two attempts are attributed to the different setting of the models. Extensions to the current data will test whether the conclusion we have drawn is valid.

Large fundamental imbalances persist in the global economy, with potential exchange rate implications. This paper assesses whether exchange rate risk is priced across G-7 stock markets. Given the multitude of hedging instruments available, theory suggests that stock market investors should not be compensated for currency risk. However, data covering 33 industry portfolios across seven major stock markets suggest that not only is exchange rate risk priced in many markets, but that it is time-varying and sensitive to currency-specific shocks. With stock market investors typically exhibiting "home bias," this suggests that investors are using equity asset proxies to hedge the exchange rate risks to consumption.

We consider a world capital market in which the investor population is heterogenous. Investors of different countries differ in the prices of goods at which they consume the income from their investments. In such a setting, the international CAPM incorporates rewards for exchange rate risk, in addition to the traditional reward for market-covariance risk. The aim of the paper is to determine whether these additional risk premia empirically playa significant role in the pricing of securities. The test being conducted is a test of a conditional version of the CAPM. It builds on the recent empirical literature which points out that stock market returns may, to some extent, be predicted on the basis of a number of instrumental variables, such as interest rates and dividend yields. All previous tests of the international CAPM with exchange risk premia have been tests of the unconditional version and have been inconclusive.

We investigate time varying risk premia in forward dollar/pound monthly exchange rates over the last two decades. We study this issue using a signal plus noise model and separately using regression techniques. Our models account for time varying volatility and non-normalities in the observed series. Our signal plus noise model fails to isolate a statistically significant risk premium component whereas our regression model does. We attribute the discrepancy in the results from the two methods to the low power of the signal plus noise model in discriminating between a time varying risk premium component and a serially uncorrelated spot exchange rate expectational error. An important reason for the low power of the signal plus noise model is its failure to use information on current period forward rates in extracting the risk premium.