Asymptotic dependence modelling of the BRICS stock markets

TL;DR

This paper analyzes the extremal dependence between BRICS stock markets using advanced statistical models, revealing varying dependence levels that can inform investment strategies.

Contribution

It introduces the use of bivariate point process and conditional multivariate extreme value models to better understand extremal dependence in stock markets.

Findings

Point process models capture more extreme events than traditional methods.

Varying extremal dependence levels observed across BRICS pairs.

Results are beneficial for investment decision-making.

Abstract

With the use of empirical data, this paper focuses on solving financial and investment issues involving extremal dependence of ten pairwise combinations of the five BRICS (Brazil, Russia, India, China, and South Africa) stock markets. Daily closing equity indices from 5 January 2010 to 6 August 2018 are used in the study. Unlike previous literature, we use bivariate point process and conditional multivariate extreme value models to investigate the extremal dependence of the stock market returns. However, it is observed that the point process was able to model many more extreme observations or exceedances that contribute to the likelihood estimation. It gives more information than the threshold excess method of the CMEV model. This study shows varying levels of low extremal dependence structure whose outcomes are highly beneficial to investors, portfolio managers and other market participants interested in maximising investment returns and financial gains.