Sample Solution

Sandoval (2006) studied the daily exchange rate data, from year 2000 to 2004, of seven Asian and developing Latin American countries, by employing the ARMA, GARCH, EGARCH and GJR- GARCH models for modeling the exchange rates. He founded out that, in the developing countries the absence of statistical significance between asymmetric and symmetric models was conditional to the application of in-sample and out-of-sample tests jointly.

Also, in an attempt to adopt a parametric measure of exchange rate volatility in Nigeria, Isitua and Neville (2006) investigated the effect of exchange rate volatility on trade flows in Nigeria. Their study employed the generalized autoregressive conditional heteroskedasticity (GARCH) technique to measure exchange rate volatility.

Furthermore the GARCH model has also been applied in research done by Danson et al. (2012) that analyzed the impact of real exchange rate volatility on economic growth in Kenya. Results depicted that exchange rate was very volatile for the entire period under study .These results imply the presence of the volatility periods in the most macroeconomic variables of the East African countries and therefore gives confidence in the a applicability of the GARCH model in capturing the volatility of these variables in the regional economies, he never captured the asymmetric effect.

The idea of the exhibition of the volatility periods in economic variables is also stressed by Oz Turk (2006) who in his paper confirms the existence of the volatility in trade brought about by shifts in the volatility of exchange rates who further suggests some critics of GARCH model.

In conclusion, a critical look at the findings of these various authors reveals that the degree of exchange rate volatility differs from one study to the other. This, of course, might be the reason why the findings of these studies on the effect of exchange rate volatility on a particular macroeconomic phenomenon, such as trade are not uniform given the fact that several researchers have ignored the degree of volatility in exchange rate among world Currencies. This paper adopts a more rigorous parametric measures of exchange rate volatility in Kenya using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (E-GARCH) modelling technique which addresses the defects identified