Spillover Effects in Major Equity Markets: A GARCH BEKK Approach

Liu, Chengda

doi:10.4236/oalib.1102160

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…Apart from spillover index proposed by Diebold and Yilmaz (2009), multivariate GARCH model has been applied in many papers concerned about the estimates of volatility spillover in recent years. For example, Erten et al (2012) analyzed the presence and magnitude of the volatility transmissions in emerging markets, Liu (2016) examined volatility effects in major equity markets, Li and Giles (2015) modeled volatility spillover effects between developed stock market and Asian emerging stock markets. MacDonald et al (2018) explored volatility co-movements and spillover Effects within Eurozone Economies.…”

Section: Introductionmentioning

confidence: 99%

Return and volatility spillover across equity markets between China and Southeast Asian countries

Hung

2019

JEFAS

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Purpose This paper aims to study the daily returns and volatility spillover effects in common stock prices between China and four countries in Southeast Asia (Vietnam, Thailand, Singapore and Malaysia). Design/methodology/approach The analysis uses a vector autoregression with a bivariate GARCH-BEKK model to capture return linkage and volatility transmission spanning the period including the pre- and post-2008 Global Financial Crisis. Findings The main empirical result is that the volatility of the Chinese market has had a significant impact on the other markets in the data sample. For the stock return, linkage between China and other markets seems to be remarkable during and after the Global Financial Crisis. Notably, the findings also indicate that the stock markets are more substantially integrated into the crisis. Practical implications The results have considerable implications for portfolio managers and institutional investors in the evaluation of investment and asset allocation decisions. The market participants should pay more attention to assess the worth of across linkages among the markets and their volatility transmissions. Additionally, international portfolio managers and hedgers may be better able to understand how the volatility linkage between stock markets interrelated overtime; this situation might provide them benefit in forecasting the behavior of this market by capturing the other market information. Originality/value This paper would complement the emerging body of existing literature by examining how China stock market impacts on their neighboring countries including Vietnam, Thailand, Singapore and Malaysia. Furthermore, this is the first investigation capturing return linkage and volatility spill over between China market and the four Southeast Asian markets by using bivariate VAR-GARCH-BEKK model. The authors believe that the results of this research’s empirical analysis would amplify the systematic understanding of spillover activities between China stock market and other stock markets.

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Section: Introductionmentioning

confidence: 99%

Return and volatility spillover across equity markets between China and Southeast Asian countries

Hung

2019

JEFAS

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“…This study employs the GARCH model with emphasis on the Baba, Engle, Kraft, and Kroner (BEKK) framework suggested by Engle and Kroner (). The BEKK model has been used in previous studies to examine the transforming volatility across economic parameters (Fedorova & Saleem, ; Liu, ). Moreover, this model assures positive specification of the variance–covariance matrix.…”

Section: Methodsmentioning

confidence: 99%

Estimation of the spillover effect between patents and innovation using the GARCH–BEKK model

Mumtaz

Smith

2017

Pacific Economic Review

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This study examines the mean and variance spillovers between patents filed and total factor productivity in Pakistan during the period lasting from 1964 to 2015. Using the multivariate generalized autoregressive conditionally heteroskedastic-Baba, Engle, Kraft and Kroner (GARCH-BEKK) model, we find no evidence of mean spillover effects between patents filed and productivity growth. However, the results support the existence of the variance spillover effect, which illustrates that the innovations may affect productivity in the long-run. Moreover, bidirectional causality in the mean and variance between innovation and productivity growth is non-existent. We find that R&D/GDP, skilled labour force and economic freedom are the significant factors affecting technological advancements in the country. We also determine that R&D/GDP and economic freedom are the important factors affecting patent activities in Pakistan. Our findings suggest that the government needs to emphasize the regulations of the patent system to safeguard the interests of investors, which ultimately promotes economic growth.

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“…For example, Erten et al (2012) analyse the presence and magnitude of volatility transmissions among emerging markets using this approach. More recently, Liu (2016) tests for volatility effects in major equity markets, while Li and Giles (2015) investigate volatility spillovers between developed stock markets and Asian emerging stock markets using the multivariate GARCH model. Adopting a more regional approach, MacDonald et al ( 2018) examine volatility co-movements and spillover effects within Eurozone economies.…”

Section: Return and Volatility Spillover Analysismentioning

confidence: 99%

Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation

Khan

Fifield

Tantisantiwong³

et al. 2021

Financ Mark Portf Manag

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This paper documents evidence of changes in the co-movement of stock returns and risk transmission among four South Asian stock markets over periods of regional market reform and global market instability. The sample period (1993–2015) is disaggregated into three sub-periods: before and after the establishment of the South Asian Federation of Exchanges (SAFE) and after the 2008 Global Financial Crisis. The principal components investigation and cointegration analysis conclude that the co-movement among stock returns in this region altered amidst a change in the institutional context and global economic uncertainty. Using a tetra-variate GARCH-BEKK model, we find that, after the establishment of SAFE, the interactions among the markets increased through volatility spillovers, but decreased through shock spillovers. In addition, there were more shock and volatility spillovers in the last sub-period as compared to the first two sub-periods, indicating that risk transmission across countries increased during the period of uncertainty. In particular, the Indian stock market was a risk spreader in South Asia after the setup of SAFE and its influence on the regional stock markets increased even further after the 2008 Global Financial Crisis.

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Spillover Effects in Major Equity Markets: A GARCH BEKK Approach

Cited by 7 publications

References 17 publications

Return and volatility spillover across equity markets between China and Southeast Asian countries

Return and volatility spillover across equity markets between China and Southeast Asian countries

Estimation of the spillover effect between patents and innovation using the GARCH–BEKK model

Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation

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