Vol. 6, Issue 2, Part B (2024)

The purpose of this study is to analyze the pattern of volatility in the exchange rate of India and to model this volatility using various models from the GARCH family, including GARCH, EGARCH, and TGARCH. To achieve this we selected India’s Nominal Effective Exchange Rate (NEER) of 23 years from January 2000 to April 2023 because it comprehensively represents the soundness of Rupee against India’s major trading countries. This study is basically an empirical research in which we used many statistical and econometric tools such as Average, Standard Deviation, Skewness, Kurtosis, Unit Root Tests, Correlogram, GARCH, EGARCH, TGATCH and various diagnostic tests in analysing exchange rate data. The study result indicates that 2008’s and 2013’s global financial crisis have impacted Rupee-NEER negatively causing highest volatility compare to less impacting global phenomenon like Covid Pandemic. The aforementioned analysis also shows that, on an average, the volatility of the Rupee-NEER is highest in May and lowest in April and June. The presence of a low degree anti-leverage effect was also discovered in the Rupee-NEER series which implies positives shocks have more influence than negative shocks on Rupee-NEER volatility, leading us to the ultimate conclusion that the best fit model for forecasting exchange rate volatility is GARCH (1, 3).

JEL Code: C1, C2, C22, G1, G12, E32, O14, O40.