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

Davide Gaetano

doi:10.3390/jrfm11040064

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

Highlights

Measuring and forecasting volatility in financial markets has attracted growing interest by academics, policy makers and practitioners during the last few decades
The structural breaks in the unconditional variance of the five time series have been identified by using a binary segmentation algorithm with a test proposed by Sansó et al (2004)
It takes into account both the fourth order moment of the process and persistence in the variance and so it is suitable for financial time series

Summary

Introduction

Measuring and forecasting volatility in financial markets has attracted growing interest by academics, policy makers and practitioners during the last few decades. Volatility in the stock, bond and foreign exchange market can be used as a measurement of risk and its impact on the economy and on the stability of financial markets is an important public policy issue; it plays a central role in the pricing of derivative securities. The financial markets are buffeted by suddenly important events that can lead to sharp breaks in the markets and breaks in parameters governing the volatility models can occur. In such cases, the inference on the parameters may be misleading as well as any policy implications drawn from the model. Strong evidence of the existence of multiple break points has been highlighted for BRICS countries (Morales and Gassie-Falzone 2011) which have experienced severe crises in the last 20 years

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Results

Conclusion