EXCHANGE RATE VOLATILITY IN INDIAN MARKETS USING GARCH MODELS

Authors

  • Dr. Jagannayaki K
  • Dr. Sreekanth Yerramilli
  • Vara Lakshmi Thavva
  • Nunna Suresh

Keywords:

Exchange Rates, Aggressiveness, interdependency, linearity, leverage effect, volatility clustering.

Abstract

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.

References

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https://rpubs.com/CongWang141/929782

https://cran.r-project.org/web/packages/bayesforecast/vignettes/GARCH.html

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Published

2023-12-30

How to Cite

K, D. J. ., Yerramilli, D. S. ., Thavva, V. L. . ., & Suresh, N. . (2023). EXCHANGE RATE VOLATILITY IN INDIAN MARKETS USING GARCH MODELS. The Journal of Contemporary Issues in Business and Government, 29(4), 224–234. Retrieved from https://cibgp.com/au/index.php/1323-6903/article/view/2641

Issue

Vol. 29 No. 4 (2023): The journal of contemporary issues in business and government

Section

Articles

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