EXCHANGE RATE VOLATILITY IN INDIAN MARKETS USING GARCH MODELS - K, Dr. Jagannayaki; Yerramilli, Dr. Sreekanth; Thavva, Vara Lakshmi; Suresh, Nunna (The journal of contemporary issues in business and government, 2023)
The present study focuses on the time series behaviour of select currencies using GARCH Models. Monthly returns of currency prices exhibit aggressiveness and high degree of interdependence. In particular, generalized autoregressive conditional heteroscedastic GARCH (1, 1) processes fit to data very satisfactorily. Various out-of-sample forecasts of monthly return variances are generated and compared statistically. Forecasts based on the GARCH model are found to be superior. The common assumptions of this model is interdependence and linearity. This paper aims to model the volatility of INR exchange rates against USD for the period from January 2000 to 5 January 2023 using the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. Both symmetric and asymmetric models have been applied to measure factors that are related to the exchange rate returns such as leverage effect and volatility clustering. Based on the results, the static forecast of GJR-GARCH (1, 1) is the best model in predicting the future pattern for both INR and USD.