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Author(s): Olumi Toba Timothy, Lawal Fatai Kolade, Ehimony James Babatunde, Umolo David, Ittah Joseph Babatunde.

Volume/Issue: Volume 8, Issue 2 (2025)

Page No: 31-44

Journal: African Journal of Mathematics and Statistics Studies (AJMSS)

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Abstract:

This study examines exchange rate volatility with Generalized Autoregressive Conditional heteroscedastic (GARCH) models using daily exchange rate data obtained from the central bank of Nigeria between 1st January 2017 and 31st December 2019. The ARCH LM test of the mean equation revealed the presence of conditional heteroscedasticity. The returns were modeled using ARCH (3), GARCH (2,2), Exponential Generalized Autoregressive Conditional Heteroscedastic EGARCH (3,2), Threshold Generalized Autoregressive Conditional Heteroscedastic TGARCH(1,1). The results revealed that EGARCH (3,2) was the best since it has the least AIC of -24.3197 and SIC of -24.2741. Diagnostic test of the EGARCH (3,2) model residuals with Ljung-Box and the ARCH LM tests revealed that the models were free from higher order autocorrelation and conditional heteroscedasticity respectively. The parameters of the EGARCH (3,2) model was significant and the positive value of the leverage parameter is an indication of absence of leverage effect in the returns of Naira-Dollar exchange rate. The absence of the leverage effect in the exchange rate indicates that positive shocks increases volatility than negative shocks of equal magnitude. Thus, the implication is that a strengthening Dollar (Weakening Naira) leads to higher period volatility than when the Naira is strengthens by the same amount. It is recommended that the Central bank should put in place long term measures to stabilize the Naira since a weakening Naira increases the uncertainty in the exchange market than a strengthening Naira.

Keywords:

Exchange Rate, Economic Growth, Garch, Heteroscedasticity, Volatility.

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