The Regime Examination of Nigeria Exchange Rate Volatility: Evidence from Markov Regime Switching Autoregressive Approach

Abstract

Inarguably, the escalation in dollar rates and the price instability in the Nigerian economy underwent significant structural and institutional changes. In assessing the importance of understanding exchange rates, it becomes imperative to build reliable models for predicting the volatility of exchange rates of home currency. Hence, this study aims to model the Nigerian exchange rate volatility using the Markov regime-switching model. The study analyses the Nigerian exchange rate returns in two and three distinct regimes by employing the Markov regime-switching autoregressive (MS-AR) model with data from 2nd January 2018 to 7th September 2020. Four MS-AR candidate models were estimated for the exchange rate series. Based on the least AIC value, MS(3)-AR(2) was returned as the most parsimonious model among the four candidate models. The MS(3)-AR(2) analysis established a high probability that the returns system remains in the liquidation and awareness states. It implied that only unconventional or severe events could switch the series from regime 2 (liquidation phase) and regime 3 (awareness). While there is a low probability that the system will stay in an imbalanced regime implies high switching of regime 1. Furthermore, an average duration period of 2 days, six days and five days were estimated for the imbalance, liquidation and awareness regimes, respectively. Thus, the findings, i.e. imbalance and liquidation regimes’ identification and their average durations, show that the Naira in the foreign exchange market is not favourable for investors to trade. The study recommends that the Nigerian government should direct more efforts towards improving the performance of the Naira in the foreign exchange market to make the market more favourable for investors. Specifically, the CBN should develop new strategies towards tackling the behaviour of the Nigerian exchange rate when in a liquidation state.