Clustering of Extremes in Financial Returns: A Study of Developed and Emerging Markets

Sara Ali Alokley,Mansour Saleh Albarrak

doi:10.3390/jrfm13070141

Sara Ali Alokley, Mansour Saleh Albarrak

Open Access

https://doi.org/10.3390/jrfm13070141

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Abstract

This paper investigates the clustering or dependency of extremes in financial returns by estimating the extremal index value, in which smaller values of the extremal index correspond to more clustering. We apply the interval estimator method to determine the extremal index for a range of threshold values in the developed and emerging markets from 2007–2017. The indices we used to represent developed markets are from France, Germany, Italy, Japan, USA, UK, Spain, and Sweden. For the emerging markets, we use indices from China, Brazil, India, Malaysia, Russia, Saudi Arabia, and Portugal. The results show that clustering occurs in the emerging and developed markets under several threshold values. This study will shed light on the dependency structure of financial returns data and the proprieties of the extremes returns. Moreover, understanding clustering of extremes in these markets can help investors reduce the exposure to extreme financial events, such as the financial crisis.

Highlights

The Black–Scholes model assume that financial returns are independent
The aim of this study is to investigates the dependency structure of extreme returns in a variety of stock market indices for developed and emerging markets
Using the interval estimator that was introduced by Ferro and Segers (2003) for a range of threshold values help us better understand the dependency structure of financial returns

Summary

Introduction

The Black–Scholes model assume that financial returns are independent. On the other hand, empirical evidence shows that returns exhibit dependency or long-range dependence (see, Cont 2001; Ding et al 1993). Extremes in financial markets are actively discussed because they can have a massive influence on both the economy and the society. The aim of this study is to investigates the dependency structure of extreme returns in a variety of stock market indices for developed and emerging markets. Using the interval estimator that was introduced by Ferro and Segers (2003) for a range of threshold values help us better understand the dependency structure of financial returns. Using the estimated extremal index and the dependency structure will shed light on behavior of the financial returns. A numerical investigation of the clustering extremes behaviour of the developed and emerging stock market indices has not been carried out in the literature; we are making preliminary progress in this direction

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