Markov regime-switching autoregressive model of stock market returns in Nigeria

This study is designed to model and forecast Nigeria's stock market using the AllShare Index (ASI) as a proxy. By employing the Markov regime-switching autore-gressive (MS-AR) model with data from April 2005 to September 2019, the studyanalyzes the stock market volatility in three distinct regimes (accumulation or distri-bution - regime 1; big-move - regime 2; and excess or panic phases - regime 3) ofthe bull and bear periods. Six MS-AR candidate models are estimated and based onthe minimum AIC value, MS(3)-AR(2) is returned as the optimal model among the sixcandidate models. The MS(3)-AR(2) analysis provides evidence of regime-switchingbehaviour in the stock market. The study also shows that only extreme events canswitch the ASI returns from regime 1 to regime 2 and to regime 3, or vice versa. Itfurther specifies an average duration period of 9, 3 and 4 weeks for the accumu-lation/distribution, big-move and excess/panic regimes respectively which is an evi-dence of favorable market for investors to trade. Based on Root Mean Square Errorand Mean Absolute Error, the fitted MS-AR model is adjudged the most appropriateASI returns forecasting model. The study recommends investments in stock across theregimes that are switching between accumulation/distribution and big-move phasesfor promising returns.