Analysing time difference and volatility linkages between China and the United States during financial crises and stable period using VARX‐DCC‐MEGARCH model

• Published date: 01 January 2021
• Author: Aviral Tiwari,Abdul Rauf,Xiaoxing Liu,Muhammad Arif,Khurram Shehzad
• DOI: http://doi.org/10.1002/ijfe.1822
• Date: 01 January 2021

RESEARCH ARTICLE

Analysing time difference and volatility linkages between

China and the United States during financial crises and

stable period using VARX-DCC-MEGARCH model

Khurram Shehzad

1

| Xiaoxing Liu

1

| Aviral Tiwari

2

| Muhammad Arif

3

|

Abdul Rauf

4

1

School of Economics and Management,

Southeast University, Nanjing, China

2

Rajagiri Business School, Cochin, Kerala,

India

3

School of Economics, Xian Jiaotong

University, Xian, China

4

School of Management Science and

Engineering, Nanjing University of

Information Science and Technology,

China

Correspondence

Khurram Shehzad, School of Economics

and Management, Southeast University,

Nanjing, China.

Email: 233189917@seu.edu.cn

Funding information

National Natural Science Foundation of

China, Grant/Award Numbers: 18VSJ035,

71673043

Abstract

The study implies VARX-DCC-MEGARCH model to investigate the returns

transmission, volatility spillovers, asymmetry effect and the dynamic correla-

tion between China and U.S. stock markets, as well as their local stock mar-

kets. We found that daytime returns of U.S. stock markets affect the overnight

returns of Chinese stock markets. However, overnight returns transmission

from the United States to China (daytime) was insignificant. Returns transmis-

sions from Chinese stock markets to the United States are not significant. Day-

time volatility of U.S. stock markets significantly spillovers the overnight

volatility of Chinese stock markets and daytime volatility of Chinese stock

markets spillovers the overnight volatility of U.S. stock markets. Moreover,

during financial crises period, negative daily returns of Chinese stock markets

significantly transmit to U.S. stock markets. Additionally, returns and volatility

spillovers between local markets of the United States was also significant. Dur-

ing the financial crisis, the volatility spillovers between local stocks market of

China was significant on one hand and leverage effect for U.S. and Chinese

stock markets were also significant on the other hand.

KEYWORDS

leverage effect, returns transmission, symmetry/asymmetry effect, time difference, VARX-DCC-

MEGARCH, volatility spillovers

1|INTRODUCTION

Today, China and the United States are among the big-

gest economies of the world. According to the China

Securities Regulatory Commission (CSRC), Chinese stock

markets has become third biggest stock market around

the globe, and total market value of Shanghai and

Shenzhen stock markets has reached 3.07 trillion dollars.

Moreover, the NASDAQ stock exchange of the United

States is one of the top three stock markets based on their

market values (Akin Oyedele, 2015). Today the world

becomes a global village and it has activated the stock

market integration among the countries, as a result, such

stock markets not only captured the attention of domestic

investors but also of the foreign investors.

The increasing trend of global integration and liberal-

ization has reshaped the world economy as “one econ-

omy.”No one nation and its stock markets are

independent of the rest of the world (Bhuyan, Robbani,

Talukdar, & Jain, 2016). Hence, in this era of advanced

information and communication technology, industry-

specific news, political news or economic news (good or

Received: 19 July 2019 Revised: 12 October 2019 Accepted: 18 June 2020

DOI: 10.1002/ijfe.1822

814 © 2020 John Wiley & Sons, Ltd. Int J Fin Econ. 2021;26:814–833.wileyonlinelibrary.com/journal/ijfe

bad) generated anywhere in the world, would instantly

affect, with different degree, the value of a stock market

nationally and internationally (Bala & Takimoto, 2017;

Bhuyan et al., 2016). Moreover, high fluctuations and

crashes of financial markets such as Mexican crises

(1994), Asian Crises & Russian debt crises (1998), global

financial crises (GFC) (2007–2009), and significant

impact of Greek debt crises across the financial markets

gained substantial attention of academicians, and urged

to analyse how the financial markets interact within

and across the nations, and how shocks in a stock spill-

overs (see Hemche, Jawadi, Maliki, & Cheffou, 2016;

Kenourgios & Dimitriou, 2015; Miralles-Marcelo,

Miralles-Quirós, & Miralles-Quirós, 2013). On the other

hand, investors are also busy to find an enhanced

investment opportunity, both nationally and interna-

tionally (Dedi & Yavas, 2016). Conclusively, because of

this affiliation, study about integration of stock markets

has become more relevant and essential (Bala &

Takimoto, 2017).

Enormous research has been done on the returns

transmission and volatility spillovers between China and

U.S. stock markets such as (Abbas, Khan, & Shah, 2013;

BenSaïda, Litimi, & Abdallah, 2018; Bhar &

Nikolova, 2009; Brooks & Ragunathan, 2003; Dedi &

Yavas, 2016; Karolyi, 1995; Li, 2007; Moon & Yu, 2010;

Nishimura & Men, 2010; Theodossiou & Lee, 1993;

Wang & Wang, 2010; Yeh & Lee, 2002; Zhou, Zhang, &

Zhang, 2012). However, the time difference between

China and the U.S. stock markets was ignored in previ-

ous literature. Additionally, according to our best knowl-

edge, no study was found which consider the time

difference between China and the U.S. stock market to

analyse the return transmission and volatility spillovers

during the era of GFC and stable period.

China is 12 hr ahead from the United States and this

difference has significant impact on Chinese and the

U.S. markets. Because of time difference, U.S. markets

close before the opening of Chinese markets and vice

versa. Therefore, stockholders of the U.S. markets are

aware of the Chinese market returns, and on the next

day, at the opening of Chinese markets their participants

are aware of the U.S. market returns. This situation can

generate the abnormal returns and high volatility in

these markets. Conclusively, it becomes extremely imper-

ative to understand the time different returns transmis-

sion and volatility spillovers behaviour between China

and the U.S. stock markets, during and after the financial

crises period. If there are financial crises in the future,

effective policies can be prepared. Different univariate

models such as SGARCH, EGARCH, GJRGARCH,

BEKK-GARCH and CCC-GARCH can be used to analyse

the returns and volatility transmission. However, the

current study will apply dynamic conditional correla-

tion (DCC) multivariate exponential generalized auto-

regressive conditional heteroskedasticity (MEGARCH)

model with the combination of vector auto regressive

(VAR) model. DCC model considered the time varying

correlation among the parameters and can handle

large number of matrices (Ahmad, Sehgal, &

Bhanumurthy, 2013). Moreover, MEGARCH model

can compute the asymmetric effect (Sikhosana &

Aye, 2018). The key contribution of this study is to

explore the overnight, daytime and daily structure of

Chinese and U.S. stock markets by using advanced

econometric model named by VARX-DCC-MEGA-

RCH. Moreover, the study also analysed and compared

the behaviour of these markets during financial crises

and stable period.

The objectives of this study are to investigate the

dynamic linkages between China and the U.S. stock mar-

kets, and to analyse, which stocks are significant trans-

mitters of shocks and which stocks are perfect for

portfolio diversification, after considering the time differ-

ence between China and the U.S. stock markets. Also,

the study will examine the affiliation between domestic

stock markets of China, that is, Shanghai composite

index and Shenzhen composite index, as well as between

local stock markets of United States, that is, Standard &

Poor's (S&P) 500 stock index and NASDAQ stock index.

This paper is ordered as follow: Section 2 presents the lit-

erature review, Section 3 elaborate data and methodol-

ogy, results and discussion are given in Section 4, the

conclusion, policy implications and future recommenda-

tions are presented in Section 5, and at last, references

are given.

2|LITERATURE REVIEW

A vast literature exists on returns transmission and vola-

tility spillovers from developed nations to emerging coun-

tries and vice versa. Moon and Yu (2010) examined daily

returns of the Shanghai stock index of China and the

S&P 500 stock index of United States to analyse the

short-term volatility spillovers and returns transmission

effect. They used asymmetry GARCH models and found

that the U.S. stock market has significant symmetric and

asymmetric effect on the Chinese stock market. Also, the

Shanghai stock index showed symmetric spillovers effect

on the S&P 500 index.

Giovannetti and Velucchi (2013) used the multiplica-

tive error fully inter-dependent model (MEM) to evaluate

the financial markets of the United States, United King-

dom, China, South Saharan African economies like

Botswana, Kenya, Nigeria and South Africa. The

SHEHZAD ET AL.815