Price and volatility spillovers across North American, European and Asian stock markets

Singh, Priyanka; Kumar, B. Rajesh; Pandey, Ajay

doi:10.1016/j.irfa.2009.11.001

Cited by 135 publications

(71 citation statements)

References 25 publications

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“…To examine the same-day spillover effect of returns of ten Chinese cross-listed stocks, we employ the vector autoregressive (VAR) which was used by Singh, Kumar and Pandey (2009). The VAR model thus estimates a dynamic simultaneous equation system; free of a priori restrictions on the structure of relationships; and the VAR is a good model to examine the spillover effect (Eun and Shim, 1989;Alaganar and Bhar, 2002;Hansda and Ray, 2003).…”

Section: Methodsmentioning

confidence: 99%

“…In the next section, we focus on the methodology incorporating the same day effect presented by Singh, Kumar and Pandey (2009) to test the spillover effect of returns of Chinese cross-listed firms.…”

Section: Research Datamentioning

confidence: 99%

“…The early opened market may have a strong influence for forthcoming opening markets. We examine the same-day price spillover of Chinese cross-listed equities with Vector Autoregressive (VAR) models developed by Singh, Kumar and Pandey (2009).…”

mentioning

confidence: 99%

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Spillover Effect of Chinese Cross-Listed Companies across Shanghai, Hong Kong and US Markets

Li¹,

Yi²,

Su³

2011

IJEF

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This paper assesses the spillover effect of returns of ten Chinese cross-listed equities which are traded in Shanghai, Hong Kong and US markets simultaneously. We find a strong unidirectional spillover effect from US market to Shanghai market, however, a significant two-way influence exists between Hong Kong and US markets. When we use VAR modeling to exam the same-day effect, we find evidence that the effect of same-day return occurs from the Shanghai to Hong Kong market and from the Hong Kong to US market; however, there is no such effect from the Shanghai to US market.

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Section: Methodsmentioning

confidence: 99%

Section: Research Datamentioning

confidence: 99%

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Spillover Effect of Chinese Cross-Listed Companies across Shanghai, Hong Kong and US Markets

Li¹,

Yi²,

Su³

2011

IJEF

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“…Thus, studies denote that the differences in holding periods in investment appear to be as one of the essential factors for investment strategy (Rigobon, 2003;Zhou, Wu, & Yang, 2011;Singh et al, 2010).…”

Section: Research Problemmentioning

confidence: 99%

“…Since 1970s, Research ISSN 2162-4860 2013 these countries started to exhibit a notable economic growth, and shortly were named as the tiger economies in the world. The upcoming body of this study focuses more on the stock markets of mentioned countries, and their performances (Pontines & Siregar, 2009;Singh, Kumar, & Pandey, 2010).…”

Section: Introductionmentioning

confidence: 99%

Investment Strategies of Different Holding Periods: Evidence from Stock Markets of Hong Kong, Korea, Shanghai, and Taiwan

Moslehpour

Batmunkh

2013

Business and Economic Research

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Although there is abundant research focusing on estimating the level of returns on stock market, there is a lack of studies examining the comparison of stock return movements for short-term and long-term investment in the Asian stock market. The present study examines return on investment of different holding periods among selected stock markets in Asia. Based on the trading performance of key indices and market capitalization value, Korean Stock Exchange (KRE), Shanghai Stock Exchange (SSE), Hong Kong Stock Exchange (HKSE), and Taiwan Stock Exchange (TWSE) were selected for this study. In assessing the comparative output of the case stock markets, this study used ANOVA and post-hoc analysis to process time series data of daily, monthly, quarterly, semiannually and annually return of investments of indices of the case stock markets. The results of this study showed that there are significant differences in return on investment among the case stock markets in the given holding periods. While a country might have a higher return in short-term investment, it may not necessarily be suitable for long-term investment as evidenced by their performance from 2001 to 2012.

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Is there a systemic risk between Sharia, Sukuk, and GCC stock markets? A ΔCoVaR risk metric‐based copula approach

et al. 2020

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This study examines the dependence structure and systemic risk concerning Sukuk, Sharia, and the Gulf Cooperation Council (GCC) stock markets. We first use copula functions to investigate the dependence structure between these markets, and subsequently, apply the conditional value‐at‐risk (CoVaR) and delta CoVaR (∆CoVaR) to assess the systemic risk. Results show evidence of time‐varying symmetric tail dependence between Islamic stock markets and GCC stock markets, except for Saudi Arabia in which an average tail dependence is observed. Sukuk has symmetric tail dependence with Bahrain, Oman, and Abu Dhabi; average dependence with Qatar and Saudi Arabia; and asymmetric tail dependence with Dubai and Kuwait. Importantly, no evidence of systemic risk for Islamic (DJIM and Sukuk) and Gulf stock markets was found.

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Price and volatility spillovers across North American, European and Asian stock markets

Cited by 135 publications

References 25 publications

Spillover Effect of Chinese Cross-Listed Companies across Shanghai, Hong Kong and US Markets

Spillover Effect of Chinese Cross-Listed Companies across Shanghai, Hong Kong and US Markets

Investment Strategies of Different Holding Periods: Evidence from Stock Markets of Hong Kong, Korea, Shanghai, and Taiwan

Is there a systemic risk between Sharia, Sukuk, and GCC stock markets? A ΔCoVaR risk metric‐based copula approach

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