Abstract:
As the economies are globalized, more rms, investors and workers nd their fortunes linked to the exchange rates. Therefore, management of exchange rate risk becomes more signi cant. As the measured risk can be managed better, the aim of this study is to quantify the foreign exchange risk. In this study, six di erent risk modeling methods - i.i.d Normal, i.i.d Student's t, Normal-GARCH, t-GARCH, unconditional EVT and GARCH ltered EVT - are used to quantify the daily risk of currency pairs. After the daily VaR of the currency pairs has been calculated, an extensive back testing study is performed using 4 di erent con dence levels to assess the performance of each risk model. The results of the back testing experiment show that the risk modeling methods that rely on the normality assumption, such as the i.i.d Normal and the Normal-GARCH model, result in signi cant underestimation of daily risk. The sophisticated methods, GARCH ltered EVT and t-GARCH models showed the best overall performance. Besides, it is observed that the performance of i.i.d Student's t is good especially for currency pairs that belong to the countries with strong economical base. The quality of the t-GARCH and GARCH ltered EVT models were observed in our study and it is recommended to use these models to quantify the FX risk. Also i.i.d Student's t model can be the method of choice if the simple implementation of the methods of choice is important.
