Measuring Dependence Between the USA and the Asian Economies: A Time-varying Copula Approach

Abstract

During the past few years, many of the financial markets have gone through devastating effects due to the crisis in one or the other economy of the world. The recent global financial crisis has triggered dramatic movements in various stock markets which may arise from interdependence or contagion between the markets. This article attempts to measure the contagion between the equity markets of Asia and the US stock market. The countries considered in the Asian group are China, India, Indonesia, South Korea, Taiwan, Hong Kong, Malaysia and Japan. Most of the Asian economies have experienced drastic higher volatility and uncertainty in the financial markets. If the markets are contagious, then the investors will be unable to reap benefits through international diversification of the portfolio. In such a case, the policymakers will further frame policies so that they can insulate themselves from inflicting heavy damage from various crises. To achieve our goal, we make use of the time-varying copula approach which helps us to study the joint behaviour of the series based on their marginal distribution. Time-varying copula approach can also capture the non-linear dependence in the series and exhibits a rich pattern of tail behaviour. Our findings support the contagion between the Asian stock markets and the US stock market during the global financial crisis. This article also highlights that the increased tail dependence is an important factor for the contagion between the Asian stock markets and the US market.

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“…Copula modeling has found many successful applications, especially in actuarial science, survival analysis, and hydrology. In finance, copula modeling has also been applied in a great number of contexts, such as asset pricing, credit risk management, aggregation risks and the study of dependence between markets (e.g., Cherubini et al, 2004 ; McNeil et al, 2005 ; Rajwani and Kumar, 2019 ; Wang et al, 2011 ; Wen et al, 2012 ; Nguyen et al, 2017 ).…”

COVID-19 and stock returns: Evidence from the Markov switching dependence approach

“…Methodologically, we examine the Symmetrized Joe-Clayton (SJC) copula to measure lower and upper tail dependence ( Rajwani and Dilip, 2019 ). The uniqueness of using the copula function is that it offers information on both the degree and structure of dependence, something a simple linear correlation method is unable to provide ( Reboredo, 2011 ).…”

Assessing the structure dependence between the Spanish stock market and some international financial markets. A time-varying copula analysis.

“…Applications of copula analysis on dependence and contagion effects between international stocks markets can be found in Rajwani et al (2019), Wang et al (2011), Horta et al (2010), Hussain et al (2018), Wen et al (2012), Nguyen et al (2017), Das (2016), Changquing et al (2015), Kenourgios et al (2010) and Jondeau and Rockinger (2006) among others. Most of these papers analyze dependence between the US stock market and other international stocks markets; the dependence between Asian stock markets has been extensively studied as well.…”