Risk quantification for foreign currency investments

As the economies are globalized, more firms, investors and workers find their fortunes linked to the exchange rates. Therefore, management of exchange rate risk becomes more significant. As the measured risk can be managed better, the aim of this study is to quantify the foreign exchange risk. In this study, six different risk modeling methods - i.i.d Normal, i.i.d Student's t, Normal-GARCH, t-GARCH, unconditional EVT and GARCH filtered 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 different confidence 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 significant underestimation of daily risk. The sophisticated methods, GARCH filtered 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 filtered 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.