In this paper, three different versions of bivariate GARCH in mean models were considered to explain the relationship between uncertainty and average outcomes of the stock index and exchange rate. From the empirical results, the bivariate EGARCH-M is ...
In this paper, three different versions of bivariate GARCH in mean models were considered to explain the relationship between uncertainty and average outcomes of the stock index and exchange rate. From the empirical results, the bivariate EGARCH-M is the best model to explain the volatility in the two markets. This paper revealed four important conclusions. First, there is a negative relationship between the exchange rates return and stock prices return, but the current exchange rates return is positively affected by the lagged stock prices return at 5% significance level. Second, the results provide strong empirical confirmation of the first hypothesis (that uncertainty in foreign exchange market has an effect on average stock prices) and third hypothesis (that uncertainty in stock market has an effect on average stock prices), implying a negative effect of stock index uncertainty and a positive effect of exchange rates uncertainty on average stock index. On the other hand, for the exchange rates equation, the GARCH-in-mean variables in AR modeling are significant. This shows that there is a positive effect of exchange rates uncertainty and a negative effect of stock index uncertainty on average exchange rates. Third, the coefficient on the lagged residual variance is greater for stock index than for exchange rates, implying that stock index shocks have longer lived effects on uncertainty in the stock market than exchange rates shock have on uncertainty in the foreign exchange market. Finally, from the magnitude of coefficient that shows the effect of the last period’s shock, volatility is more sensitive to its own lagged values than it is to new surprises in the foreign exchange market.