Modeling and Forecasting the Volatility of Returns in the Infrastructure Sector in Emerging Markets
Keywords:infrastructure, volatility, modeling, forecasting, emerging markets
Understanding the volatility behaviour of specific sectors of the economy enables investors to formulate workable investment strategies, and policy-makers to formulate policies that dampen excess volatility. This study examined the volatility features of the infrastructure sector in emerging markets. The features assessed were the GARCH effects, volatility persistence, and leverage effects. EGARCH and GJRGARCH models of order one under normal and non-normal error distributions were employed to unpack the volatility behaviour of infrastructure returns in emerging markets. The results from both models under all distributions indicated the existence of GARCH effects, volatility clustering, volatility persistence, and leverage effects in the infrastructure sector in emerging nations. This implies that past conditional variance is significant in determining current conditional variance, thereby rendering forecasting a worthwhile task. The findings also suggest that investors interested in the infrastructure sector in emerging markets should incorporate leverage effects in their estimation of value-at-risk. Furthermore, they should focus on factors other than mean-variance portfolio optimization and consider leverage effects, excess kurtosis, and skewness when making investment decisions. Finally, investors in the infrastructure sector in emerging markets are encouraged to formulate hedging strategies as they are exposed to significant risk and uncertainty.