中美股市投资者风险偏好的联动性研究——基于风险-收益关系视角

贺志芳, 董天琪

系统工程理论与实践 ›› 2023, Vol. 43 ›› Issue (9) : 2556-2569.

PDF(1398 KB)
PDF(1398 KB)
系统工程理论与实践 ›› 2023, Vol. 43 ›› Issue (9) : 2556-2569. DOI: 10.12011/SETP2022-2637
论文

中美股市投资者风险偏好的联动性研究——基于风险-收益关系视角

    贺志芳, 董天琪
作者信息 +

Linkages of investor risk preferences in the Chinese and US stock markets: A perspective from risk-return relationship

    HE Zhifang, DONG Tianqi
Author information +
文章历史 +

摘要

股票市场上投资者的风险偏好可以通过市场上投资者承担风险所需要的收益补偿来体现, 也可以理解为股市风险与收益之间的关系. 本文以中美股票市场为研究对象, 基于时变参数广义自回归条件异方差(TVP-GARCH-M)模型分别得到中国股票市场和美国股票市场上的投资者风险偏好, 并采用Granger因果检验方法考察中美股市投资者风险偏好之间的因果关系, 研究发现美国股市投资者风险偏好的变动能够引起中国股市投资者风险偏好的变动, 而中国股市投资者风险偏好不能影响美国股市投资者风险偏好. 进一步运用时变参数向量自回归(TVP-VAR)模型探讨美国股市投资者风险偏好对中国股市投资者风险偏好的影响过程, 结果表明: 美国股市投资者风险偏好对中国股市投资者风险偏好具有显著的负向影响作用, 并且表现出明显的时变特征, 其短期的影响程度要大于中期和长期的影响程度. 同时, 该影响在不同时点上也存在差异, 在2018年中美贸易摩擦期间的影响程度最大, 说明中美贸易摩擦在中美股市投资者风险偏好的联动性中发挥重大作用.

Abstract

The risk preference of investors in stock markets can be reflected by the return compensation required by investors for risk-taking, which refers to the risk-return relationship in stock markets. This paper takes the Chinese and US stock markets as research objects, and captures the investors' risk preferences of the Chinese and US stock markets based on the time-varying parameter generalized autoregressive conditional heteroskedasticity in the mean (TVP-GARCH-M) model. Then, the causality relationship between investors' risk preferences of Chinese and American investors is investigated by Granger causality tests. It is found that changes in investors' risk preferences in the US stock market can cause changes in investors' risk preferences in the Chinese stock market, while investors' risk preferences in the Chinese stock market cannot affect those in the US stock market. Furthermore, the time-varying parameter vector auto regression (TVP-VAR) model is used to explore the impact of the investors' risk preference in the US stock market on that in the Chinese stock market. The results show that investors' risk preference in the US stock market has a significant negative impact on the investors' risk preference in the Chinese stock market, and the impact shows obvious time-varying characteristics. The short-term impact is greater than the medium-term and long-term impacts. Meanwhile, the impact also varies at different time points and is the largest during the US-China conflict in 2018, indicating that the 2018 US-China conflict plays a significant role in the co-movement of investor risk preferences in the Chinese and US stock markets.

关键词

中美股市 / 风险偏好 / GARCH-M / TVP-VAR

Key words

the Chinese and US stock markets / risk preference / GARCH-M / TVP-VAR

引用本文

导出引用
贺志芳 , 董天琪. 中美股市投资者风险偏好的联动性研究——基于风险-收益关系视角. 系统工程理论与实践, 2023, 43(9): 2556-2569 https://doi.org/10.12011/SETP2022-2637
HE Zhifang , DONG Tianqi. Linkages of investor risk preferences in the Chinese and US stock markets: A perspective from risk-return relationship. Systems Engineering - Theory & Practice, 2023, 43(9): 2556-2569 https://doi.org/10.12011/SETP2022-2637
中图分类号: F832.5   

参考文献

[1] Li Q, Yang J, Hsiao C, et al. The relationship between stock returns and volatility in international stock markets[J].?Journal of Empirical Finance, 2005,?12(5):650-665.
[2] Dewandaru G, Masih R, Masih A M M. Contagion and interdependence across Asia-Pacific equity markets:An analysis based on multi-horizon discrete and continuous wavelet transformations[J].?International Review of Economics&Finance,?2016, 43:363-377.
[3] Jiang Y, Nie H, Monginsidi J Y. Co-movement of ASEAN stock markets:New evidence from wavelet and VMD-based copula tests[J].?Economic Modelling,?2017, 64:384-398.
[4] Zhong Y, Liu J. Correlations and volatility spillovers between China and Southeast Asian stock markets[J].?The Quarterly Review of Economics and Finance,?2021, 81:57-69.
[5] 何德旭,苗文龙,闫娟娟,等.全球系统性金融风险跨市场传染效应分析[J].经济研究, 2021, 56(8):4-21. He D X, Miao W L, Yan J J, et al. Analysis on the global systemic financial risks cross-market contagion effect[J]. Economic Research Journal, 2021, 56(8):4-21.
[6] 朱小能,吴杰楠.股市联动中的"涟漪效应"[J].中国管理科学, 2021, 29(8):1-12. Zhu X N, Wu J N. The"ripple effect"in stock market co-movement[J]. Chinese Journal of Management Science, 2021, 29(8):1-12.
[7] 赵万里,范英,姬强,等."一带一路"国家金融风险溢出研究--基于TENET网络方法[J].系统工程理论与实践, 2022, 42(1):24-36. Zhao W L, Fan Y, Ji Q, et al. Research on financial risk spillover of the countries along the Belt and Road-Based on TENET method[J]. Systems Engineering-Theory&Practice, 2022, 42(1):24-36.
[8] Li X, Zhang B. Spillover and cojumps between the US and Chinese stock markets[J].?Emerging Markets Finance and Trade,?2013, 49:23-42.
[9] George L Y. The interactions between China and US stock markets:New perspectives[J].?Journal of International Financial Markets, Institutions and Money,?2014, 31:331-342.
[10] Zhang Y, Mao J. COVID-19's impact on the spillover effect across the Chinese and US stock markets[J].?Finance Research Letters, 2022, 47:102684.
[11] Liu Y, Ouyang H. Spillover and comovement:The contagion mechanism of systemic risks between the US and Chinese stock markets[J].?Emerging Markets Finance and Trade,?2014, 50:109-121.
[12] Moon G H, Yu W C. Volatility spillovers between the US and China stock markets:Structural break test with symmetric and asymmetric GARCH approaches[J].?Global Economic Review,?2010, 39(2):129-149.
[13] Hanif W, Mensi W, Vo X V. Impacts of COVID-19 outbreak on the spillovers between US and Chinese stock sectors[J].?Finance Research Letters,?2021, 40:101922.
[14] Vuong G T H, Nguyen M H, Huynh A N Q. Volatility spillovers from the Chinese stock market to the US stock market:The role of the COVID-19 pandemic[J].?The Journal of Economic Asymmetries,?2022, 26:e00276.
[15] 李红权,洪永淼,汪寿阳.我国A股市场与美股、港股的互动关系研究:基于信息溢出视角[J].经济研究, 2011, 46(8):15-25. Li H Q, Hong Y M, Wang S Y. Information spillover among China's A-shares market, US stock market and HK stock market[J]. Economic Research Journal, 2011, 46(8):15-25.
[16] 贺志芳,周方召.投资者风险偏好的动态特征--来自国际股票市场的实证证据[J].系统科学与数学, 2018, 38(3):348-363. He Z F, Zhou F Z. The dynamic characteristics of investors'risk preference:Empirical evidence from international stock markets[J]. Journal of Systems Science and Mathematical Sciences, 2018, 38(3):348-363.
[17] He Z, He L, Wen F. Risk compensation and market returns:The role of investor sentiment in the stock market[J].?Emerging Markets Finance and Trade,?2019, 55(3):704-718.
[18] 文凤华,杨鑫,龚旭,等.金融危机背景下中美投资者情绪的传染性分析[J].系统工程理论与实践, 2015, 35(3):623-629. Wen F H, Yang X, Gong X, et al. The research on investor sentiment contagion between China and U.S. based on the background of financial crisis[J]. Systems Engineering-Theory&Practice, 2015, 35(3):623-629.
[19] 尹海员,王盼盼.股票投资者情绪跨国传染与空间依赖性:基于中、美等七国空间面板数据的分析[J].管理工程学报, 2020, 34(1):223-232. Yin H Y, Wang P P. Transnational infection and spatial dependence of stock investor sentiment:Based on panel data from seven countries such as China and US[J]. Journal of Industrial Engineering and Engineering Management, 2020, 34(1):223-232.
[20] 贺志芳,文凤华,黄创霞,等.投资者情绪与时变风险补偿系数[J].管理科学学报, 2017, 20(12):29-38. He Z F, Wen F H, Huang C X, et al. Investor sentiment and time-varying coefficient of risk compensation[J]. Journal of Management Sciences in China, 2017, 20(12):29-38.
[21] He Z. Asymmetric impacts of individual investor sentiment on the time-varying risk-return relation in stock market[J].?International Review of Economics&Finance,?2022, 78:177-194.
[22] Wen F, Zhang M, Xiao J, et al. The impact of oil price shocks on the risk-return relation in the Chinese stock market[J].?Finance Research Letters, 2022, 47:102788.
[23] Zhao L, Wen F. Risk-return relationship and structural breaks:Evidence from China carbon market[J].International Review of Economics&Finance,2022, 77:481-492.
[24] 苑莹,王海英,庄新田.基于非线性相依的市场间金融传染度量--测度2015年中国股灾对重要经济体的传染效应[J].系统工程理论与实践, 2020, 40(3):545-558. Yuan Y, Wang H Y, Zhuang X T. Financial contagion measurement between nonlinear inter-dependent markets:Detecting the contagion effects of Chinese stock market crash in 2015 on the world's important economies[J]. Systems Engineering-Theory&Practice, 2020, 40(3):545-558.
[25] 闵峰,文凤华,吴楠.货币政策和财政政策对中国消费和投资的有效性评估[J].计量经济学报, 2021, 1(1):94-113. Min F, Wen F H, Wu N. Assessing the effectiveness of monetary and fiscal policies on Chinese investment and consumption[J]. China Journal of Econometrics, 2021, 1(1):94-113.
[26] 何枫,郝晶,谭德凯,等.中国金融市场联动特征与系统性风险识别[J].系统工程理论与实践, 2022, 42(2):289-305.He F, Hao J, Tan D K, et al. Chinese financial markets connectedness and systemic risk identification[J]. Systems Engineering-Theory&Practice, 2022, 42(2):289-305.
[27] 赵果庆,田存志.中美两国三地股指的同步性与传导机制--基于次贷危机以来道琼斯、恒生和上海综合指数日数据[J].系统工程理论与实践, 2011, 31(6):1029-1038. Zhao G Q, Tian C Z. The co-movements and transmission mechanism of stock indexes in three places of Sino-America:Based on Dow Jones, Hang Seng, Shanghai Composite Index daily data since the sub-prime mortgage crisis[J]. Systems Engineering-Theory&Practice, 2011, 31(6):1029-1038.
[28] 林娟,赵海龙.沪深股市和香港股市的风险溢出效应研究--基于时变ΔCoVaR模型的分析[J].系统工程理论与实践, 2020, 40(6):1533-1544.Lin J, Zhao H L. Research on the risk spillovers between Shanghai, Shenzhen and Hong Kong stock markets-Based on the time varying ΔCoVaR model[J]. Systems Engineering-Theory&Practice, 2020, 40(6):1533-1544.
[29] Chow G C, Liu C, Niu L. Co-movements of Shanghai and New York stock prices by time-varying regressions[J].?Journal of Comparative Economics,?2011, 39(4):577-583.
[30] 王璐,黄登仕,乔高秀,等.美国股市会影响金砖国家股市之间的相关性吗?--线性和非线性条件Granger因果检验[J].系统工程, 2018, 36(5):13-22. Wang L, Huang D S, Qiao G X, et al. Does the US stock market affect the dependence of Brick stock market?Linear and nonlinear conditional Granger causality analysis[J]. Systems Engineering, 2018, 36(5):13-22.
[31] Hiemstra C, Jones J D. Testing for linear and nonlinear Granger causality in the stock price-volume relation[J].?The Journal of Finance, 1994,?49(5):1639-1664.
[32] Diks C, Panchenko V. A new statistic and practical guidelines for nonparametric Granger causality testing[J].?Journal of Economic Dynamics and Control,?2006, 30(9-10):1647-1669.
[33] Wen F, Xiao J, Huang C, et al, Interaction between oil and US dollar exchange rate:Nonlinear causality, time-varying influence and structural breaks in volatility[J]. Applied Economics, 2018, 50(3):319-344.
[34] He Z. Dynamic impacts of crude oil price on Chinese investor sentiment:Nonlinear causality and time-varying effect[J].?International Review of Economics&Finance, 2020, 66:131-153.
[35] 龚朴,黄荣兵.次贷危机对中国股市影响的实证分析--基于中美股市的联动性分析[J].管理评论, 2009, 21(2):21-32. Gong P, Huang R B. Empirical analysis of sub-prime mortgage crisis's impacts on Chinese stock market-Based on the interaction between Chinese and American stock markets[J]. Management Review, 2009, 21(2):21-32.
[36] 杨子晖,陈雨恬,张平淼.重大突发公共事件下的宏观经济冲击、金融风险传导与治理应对[J].管理世界, 2020, 36(5):13-35. Yang Z H, Chen Y T, Zhang P M. Macroeconomic shock, financial risk transmission and governance response to major public emergencies[J]. Management World, 2020, 36(5):13-35.
[37] 周颖刚,肖潇.汇率波动、生产网络与股市风险--基于中美贸易摩擦背景的分析[J].金融研究, 2022(7):115-134. Zhou Y G, Xiao X. Exchange rate volatility, production network, and stock market risk during the Sino-US trade friction[J]. Journal of Financial Research, 2022(7):115-134.
[38] Shi Y, Wang L, Ke J. Does the US-China trade war affect co-movements between US and Chinese stock markets?[J].?Research in International Business and Finance,?2021, 58:101477.
[39] Primiceri G E. Time varying structural vector autoregressions and monetary policy[J].?The Review of Economic Studies,?2005, 72(3):821-852.
[40] Wen F, He Z, Dai Z, et al. Characteristics of investors'risk preference for stock markets[J].?Economic Computation&Economic Cybernetics Studies&Research,?2014, 48(3):235-254.
[41] Engle R F, Lilien D M, Robins R P. Estimating time varying risk premia in the term structure:The ARCH-M model[J].?Econometrica:Journal of the Econometric Society, 1987,?55(2):391-407.
[42] Granger C W J. Investigating causal relations by econometric models and cross-spectral methods[J]. Econometrica, 1969, 37(3):424-438.
[43] He Z, Zhou F. Time-varying and asymmetric effects of the oil-specific demand shock on investor sentiment[J].?PLoS One, 2018,?13(8):0200734.

基金

国家社会科学基金后期资助项目(21FJYB003)
PDF(1398 KB)

756

Accesses

0

Citation

Detail

段落导航
相关文章

/