On Modeling and Forecasting the Volatility of the Market Risk of Nigerian Stock Exchange Index

• Activity Number: 246
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): Dallah Hamadu*+
• Companies: University of Lagos
• Keywords: NSI ; ARCH Models ; Asymmetric GARCH ; MLE ; Monte Carlo Simulation ; Robustness

Abstract

Forecasting market risk is an important statistical financial problem that is receiving increasing attention globally. This article investigates the volatility of the daily returns of Nigerian Stock Index (NSI). Empirical results findings indicate evidence of market regularities hypotheses and the adequacy the competing symmetric and asymmetric generalized conditional heteroskedastic (GARCH) volatility models considered in the present study. Maximum likelihood estimation (MLE) based on Normal, Student-t and Generalized Errors Distribution (GED)) are treated in the quest for a robust simulated preferred model. Contrary to expectation of complex symmetric and asymmetric GARCH volatility models behavior observed in most developed and emerging markets, the NSI returns exhibited an ARCH(2) pattern. Further analysis using Monte Carlo simulation supported the choice of the ARCH (2)-based Value at Risk (VAR). The present study findings have far reaching policy implication to market participants and particularly the investing community who need to be well informed after just passing through the tragedy of the global economic meltdown.