• Media type: E-Article
  • Title: Markov regime-switching autoregressive model of stock market returns in Nigeria
  • Contributor: Adejumo, Oluwasegun A. [VerfasserIn]; Albert, Seno [VerfasserIn]; Asemota, Omorogbe J. [VerfasserIn]
  • imprint: 2020
  • Published in: CBN journal of applied statistics ; 11(2020), 2 vom: Dez., Seite 65-83
  • Language: English
  • DOI: 10.33429/Cjas.11220.3/8
  • ISSN: 2476-8472
  • Identifier:
  • Keywords: All share index ; Markov process ; regime switching ; stock market ; volatility ; Aufsatz in Zeitschrift
  • Origination:
  • Footnote:
  • Description: 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.
  • Access State: Open Access