Forecast Combinations for Structural Breaks in Volatility: Evidence from BRICS Countries

Abstract

The aim of this paper is to investigate the relevance of structural breaks for forecasting the volatility of daily returns on BRICS countries (Brazil, Russia, India, China and South Africa). The data set used in the analysis is the Morgan Stanley Capital International MSCI daily returns and covers the period from 19 July 1999 to 16 July 2015. To identify structural breaks in the unconditional variance, a binary segmentation algorithm with a test, which considers both the fourth order moment of the process and persistence in the variance, has been implemented. Some forecast combinations that account for the identified structural breaks have been introduced and their performance has been evaluated and compared by using the Model Confidence Set (MCS). The results give significant evidence of the relevance of the structural breaks. In particular, in the regimes identified by the structural breaks, a substantial change in the unconditional variance is quite evident. In forecasting volatility, the combination that averages forecasts obtained using different rolling estimation windows outperforms all the other combinations