Return and asymmetric volatility transmissions between main stock market and second-tier stock market: the case of Hong Kong

Nguyen, Trang, Chaiechi, Taha, Eagle, Lynne, and Low, David (2020) Return and asymmetric volatility transmissions between main stock market and second-tier stock market: the case of Hong Kong. In: Economics and Finance Readings: selected papers from Asia-Pacific Conference on Economics & Finance. From: 2019 Asia-Pacific Conference on Economics and Finance, 25-26 July 2019, Singapore. (In Press)

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Abstract

This study aims to investigate the dynamic return and asymmetric volatility transmissions between the main stock market and the Growth Enterprise Market in Hong Kong. Unlike previous studies, this study examines the cross-market transmissions under the joint impacts of volatility breaks, thin trading, and trading volume. A linear state-space AR model with Kalman filter estimation and an augmented bivariate VAR asymmetric BEKK-GARCH model are employed for empirical analysis. The results determine that under the joint impacts of volatility breaks, thin trading, and trading volume, a unidirectional return transmission from the GEM to the main market survives with the diminishing magnitude and significant level. However, the underlying volatility transmission from the GEM to the main market, in essence, is eliminated. This paper aims to be a proof-of-concept to provide sufficient evidence of methodological viability, which can then be used in larger scale research or replicated in new settings.

Item ID: 60503
Item Type: Conference Item (Research - E1)
ISBN: 978-981-10-8147-7
Keywords: Return and asymmetric volatility transmissions, Volatility break, Thin trading, Trading volume, Augmented bivariate VAR asymmetric BEKK-GARCH
Date Deposited: 09 Oct 2019 00:33
FoR Codes: 14 ECONOMICS > 1402 Applied Economics > 140207 Financial Economics @ 50%
14 ECONOMICS > 1403 Econometrics > 140305 Time-Series Analysis @ 50%
SEO Codes: 91 ECONOMIC FRAMEWORK > 9101 Macroeconomics > 910103 Economic Growth @ 100%
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