Modelling Volatility Dynamics of Monthly Changes in Nigeria’s Savings Deposit Rate: A GARCH Approach

Abstract

This study modelled the volatility dynamics of monthly changes in Nigeria's Savings Deposit Rate using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) framework. Monthly Savings Deposit Rate data covering January 2013 to April 2026 were obtained from the Central Bank of Nigeria Statistical Bulletin and analysed using EViews 10. Descriptive statistics, the Augmented Dickey-Fuller (ADF) test and the ARCH-LM test were employed as preliminary procedures, while ARCH and GARCH models were estimated using Maximum Likelihood. The ADF test showed that the Savings Deposit Rate was non-stationary at level but became stationary after first differencing. The ARCH-LM test provided significant evidence of conditional heteroskedasticity, with an F-statistic of 21.47946 and a probability value of 0.0000, thereby justifying the use of conditional volatility models. The estimated model produced a positive and statistically significant ARCH coefficient of 0.241450 (p = 0.0210), indicating that recent shocks significantly affect current volatility. The GARCH coefficient was positive at 0.284001 but was statistically insignificant at the 5% level (p = 0.0943). The estimated volatility persistence measure, α+β=0.525451, was below unity, indicating a stationary conditional variance process. The estimated half-life of a volatility shock was approximately 1.08 months, suggesting relatively rapid dissipation of volatility shocks. Post-estimation diagnostics showed no significant remaining ARCH effects or residual serial correlation, while the standardised residuals did not significantly depart from normality. The study concludes that monthly changes in Nigeria's Savings Deposit Rate exhibit time-varying conditional volatility and that the model provides an adequate and parsimonious representation of its conditional variance dynamics.