Tail Dependence Between US and Chinese Technology Stocks Under Policy and Technological Shocks

Shuchang Liu

doi:10.47297/wspceWSP2516-251911.20250903

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Tail Dependence Between US and Chinese Technology Stocks Under Policy and Technological Shocks

Volume 9, Issue 3

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Tail Dependence Between US and Chinese Technology Stocks Under Policy and Technological Shocks
Tail Dependence Between US and Chinese Technology Stocks Under Policy and Technological Shocks
Jinan University, Guangzhou, Guangdong, 511443, China
Vol. 9, Issue 3, Pages: 56-62(2025)
Published：30 June 2025
DOI：10.47297/wspceWSP2516-251911.20250903
Accepted：

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Liu Shuchang.Tail Dependence Between US and Chinese Technology Stocks Under Policy and Technological Shocks[J].Creative Economy,2025,09(03):56-62.
DOI：

Liu Shuchang.Tail Dependence Between US and Chinese Technology Stocks Under Policy and Technological Shocks[J].Creative Economy,2025,09(03):56-62. DOI： 10.47297/wspceWSP2516-251911.20250903.

摘要

Abstract

The financial market is a complex and interconnected system

and the correlation between the U.S. and Chinese stock markets has long been a focal point in financial research. However

limited attention has been paid specifically to the technology sector. This paper selects the Hang Seng TECH Index and the NASDAQ Composite Index as the representative benchmarks for the Chinese and U.S. technology markets. We first model the marginal distributions of return series using the t-GARCH(1

1) framework and compute constant upper and lower tail dependence coefficients. Then

we estimate the parameters of the SJC Copula using a two-step estimation procedure. Finally

we conduct independent and synergistic effect tests to examine how the two events influence the tail dependence structure between the two markets. The results reveal asymmetric and time-varying tail dependence dynamics

with the policy shock inducing a sustained increase and the technological shock triggering a short-lived spike in extreme market co-movements.

关键词

Keywords

references

Li D X . On default correlation: A copula function approach [J ] . Available at SSRN 187289 , 1999 .

Demarta S. , & McNeil A . J. The t copula and related copulas [J ] . International statistical review , 2005 , 73 ( 1 ), 111 - 129 .

Émile M. , & Gumbel J . Distributions des valeurs extrêmes en plusieurs dimensions [J ] . In Annales de l'ISUP (Vol . 9 , No. 2 , pp. 171 - 173 ).1960.

Clayton D . G. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence [J ] . Biometrika , 1978 , 65 ( 1 ), 141 - 151 .

Harry Joe . Multivariate models and multivariate dependence concepts . Book | Taylor and Francis ; CRC Press 2012 .

Patton A . J. Estimation of multivariate models for time series of possibly different lengths [J ] . Journal of Applied Econometrics , 2006 , 21 ( 2 ), 147 – 173 .

Bollerslev T . A conditionally heteroskedastic time series model for speculative prices and rates of return [J ] . The Review of Economics and Statistics , 1987 , 69 ( 3 ), 542 – 547 .

Connolly R . An examination of the robustness of the weekend effect [J ] . Journal of Financial and Quantitative Analysis , 1989 , 24 , 133 69 .

Gu G . -F., Chen W., & Zhou W.-X. Empirical distributions of Chinese stock returns at different microscopic timescales [J ] . Physica A , 2008 , 387 ( 2-3 ), 495 – 502 .

Yang L . Tail dependence among sectoral indices in the Shanghai and Shenzhen stock markets: Evidence from the M-Copula-t-GARCH model [J ] . Journal of Henan Institute of Technology , 2021 , 29 ( 5 ), 46 – 51 .

Wei Y. , & Zhang S . Correlation analysis in financial markets: The Copula-GARCH model and its applications . Systems Engineering , 2004 ,( 4 ), 7 – 12 .

Wen F. , Yang X. , & Zhou W . X. Tail dependence networks of global stock markets [J ] . International Journal of Finance & Economics , 2019 , 24 ( 1 ), 558 - 567 .

Song X . A study on the correlation between crude oil and stock markets based on the Copula-GARCH model [J ] . Science, Technology and Industry , 2021 , 21 ( 8 ), 77 – 84 .

Jia S. , Chen X. , & Jin J . Global climate change and stock market risk: Evidence from the GARCH-Copula-CoVaR model [J ] . Journal of Central University of Finance and Economics , 2025 ,( 2 ), 105 – 121,138 .

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