金融危机前后亚太地区主要股指间的联动效应分析
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摘要
2007年美国爆发了次贷危机,进而引起了金融市场的剧烈动荡,并迅速波及到亚太地区的金融市场,亚太各国股市受到剧烈震荡,均出现了大幅的下滑。本文从2005年7月22日至2011年3月18日亚太地区最具代表性的21个股指的日交易数据入手,采用具有准确拓扑序列的亚超度量空间方法和最小生成树算法,以2008年9月15日为金融危机前后分界点对亚太地区主要股票市场之间的联动程度加以研究,继而运用VAR模型、Granger因果检验和脉冲响应函数对我国沪深300指数和亚太地区中心节点指数之间的联动性进行检验和实证分析。研究结果表明,自从金融危机大规模爆发后,亚太地区主要股指间的地理区域聚集效应变得更加明显,各股指间的相关程度得到显著提高；亚太地区股指整体上的动态稳定性是相对稳定的；金融危机进一步增强了香港作为亚太地区金融中心的地位。我国沪深300指数与香港恒生指数之间存在着长期的协整关系,金融危机发生以后,香港恒生指数对我国沪深300有较强的引导作用。为了避免亚太各国股指过度剧烈波动,应该在整个亚太地区协调金融监管措施,保持各国股票市场的多元化投资。
Subprime mortgage crisis broke out in the United States in2007,and triggered a fierce fluctuation in financial markets, then quickly spread to other financial markets of the Asia-Pacific region, and there was a substantial decline among those turbulent national stock markets. The data used in this article comes from the daily data of the most representative21Asia-Pacific region stocks which started from Jul.22,2005to Mar.18,2011.This article used a subdominant ultrametric space method of precise topology sequence and the minimum spanning tree algorithm to study the degree of co-movements in the major stock markets of the Asia-Pacific region by taking Sep.15,2008as a cut-off point of the financial crisis. Then I test and analysis the co-movements between China's HS300Index and the central node index of the Asia-Pacific region by using VAR models, Granger causality test and impulse response function. Empirical results shows that, after the financial crisis, the major indexes of the Asia-Pacific region showed more pronounced aggregation effect of the geographic area, the degree of correlation between the stock indexes increased significantly. The overall dynamic stability of the Asia-Pacific region index is relatively stable. The financial crisis enhances Hong Kong as a regional financial center further. China's HS300Index has a long-term integrated relationship with Hang Seng Index in Hong Kong. After the financial crisis, Hang Seng Index in Hong Kong has a strong guiding role on China's HS300Index. In order to avoid excessive volatility of stock index among the Asia-Pacific countries we should coordinate the financial regulatory measures throughout the Asia-Pacific region and maintain the diversity of national stock market investment.
Subprime mortgage crisis broke out in the United States in2007,and triggered a fierce fluctuation in financial markets, then quickly spread to other financial markets of the Asia-Pacific region, and there was a substantial decline among those turbulent national stock markets. The data used in this article comes from the daily data of the most representative21Asia-Pacific region stocks which started from Jul.22,2005to Mar.18,2011.This article used a subdominant ultrametric space method of precise topology sequence and the minimum spanning tree algorithm to study the degree of co-movements in the major stock markets of the Asia-Pacific region by taking Sep.15,2008as a cut-off point of the financial crisis. Then I test and analysis the co-movements between China's HS300Index and the central node index of the Asia-Pacific region by using VAR models, Granger causality test and impulse response function. Empirical results shows that, after the financial crisis, the major indexes of the Asia-Pacific region showed more pronounced aggregation effect of the geographic area, the degree of correlation between the stock indexes increased significantly. The overall dynamic stability of the Asia-Pacific region index is relatively stable. The financial crisis enhances Hong Kong as a regional financial center further. China's HS300Index has a long-term integrated relationship with Hang Seng Index in Hong Kong. After the financial crisis, Hang Seng Index in Hong Kong has a strong guiding role on China's HS300Index. In order to avoid excessive volatility of stock index among the Asia-Pacific countries we should coordinate the financial regulatory measures throughout the Asia-Pacific region and maintain the diversity of national stock market investment.
引文
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[21]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.
[22]方毅,桂鹏,亚太地区股票市场的联动程度-基于次级贷冲击的研究,世界经济研究,2010.8
[23]黄飞雪,谷静,李延喜,苏敬勤.金融危机前后的全球主要股指联动与动态稳定性比较.2010.11
[24]母宇,后金融危机时代关于中国股市与世界重要股市联动性的思考,金融经济,2009,100-102
[2]Forbes, K. J., Rigobon, R. NoContagion, Only Interdependence:Measuring Stock Market Comovements [J]. Journal of Finance,2002,57:2223-2261
[3]Arshanapalli B., and J. Doukas. International Stock Market Linkages:Evidence from the Pre-and Post-Octobe1987 Period [J]. Journal of Bankings Finance,1993, (17):193-208.
[4]Lin W, Engle R. F. and I to T. Do bul Is and bears move across borders? Internal ional transmission of stock returns and volatility [J]. Review of Financial Studies, 1994, (7):507-538
[5]Jang, H., and W. Sul. The Asian Financial Crisis and the Co-Movement of Asian Stock Markets [J]. Journal of Asian Economics,2002, (13):94-104.
[6]Fan, W.. An Empirical Study of Cointegrat ion and Causal ity in the Asia-Pacific Stock Markets [R]. Yale University Working Paper, Available at http://ssm. com /abstract=360160 or do:i 10.2139/ssrn.360160,2003.
[7]Albuquerque, P. H., A.E. Rivas, and A. J. Rodriguez. Are European Stock Markets Influencing Latin American Stock Markets? [J]. An a lisis Economico,2006, (21): 51-67.
[8]Masih, A. M. M. and R. Masih. Are Asian Stock Market Fluctuations Due Mainly to Intra-Regional Contagion Effects? Evidence Based on Asian Emerging Stock Markets[J]. Pacific Basin Financial Journal,1999, (7):251-282
[9]Koutmos, G. and Booth, G. G. Asymmetric volatility t ransmiss ion in international stock markets [J]. Journal of International Money and Finance,1995,14(6):747-762
[10]Mantegna R N. Hierarchical Structure in Financial Markets [J]. The European Physical Journal B,1999,11 (1):193-197.
[11]Kim H J, Lee Y, Kahng B, Kim I M. Weighted Scale 2Free Network in Financial Correlations [J]. Journal of Physical Society of Japan,2002,71 (9):2133- 2136.
[12]Onnela J P, Kaski K, Kertesz J. Clustering and Information in Correlation Based Financial Networks [J]. The European Physical Journal B,2004,38 (2) 353-362.
[13]Lee K E, Lee J W, Hong B H. Comp lex Networks in a Stock Market [J]. Computer Physics Communications,2007,177 (1-2):186.
[14]V. Tola, F. Lillo, M. Gallegati, R. N. Mantegna, Cluster analysis for portfolio optimization, Journal of Economic Dynamics and Control 32 (2008) 235-258.
[15]Gilmore C G, Lucey B M, BosciaM. An ever-closer union? Examining the evolut ion of linkages of European equity markets via minimum spanning trees[J]. Physica A: Statistical Mechanics and Its Applications,2008,387(25):6319-6329.
[16]Tabak B M, Serra T R, Cajueiro D 0. Topological properties of stock market networks:The case of Brazi 1 [J]. Physica A:Statistical Mechanics and Its Applications,2010,389(16):3240-3249.
[17]俞世典,陈守东,黄立华.主要股票指数的联动分析[J].统计研究,2001,(08).
[18]陈守东,韩广哲,荆伟.主要股票市场指数与我国股票市场指数间的协整分析[J].数量经济技术经济研究,2003,(05).
[19]高莹,靳莉莉.沪深300指数与世界主要股票指数的关联性分析[J].金融管理,2008,(02).
[20]李晓广,张岩贵.我国股票市场与国际市场的联动性研究——对次货危机时期样本的分析[J].国际金融研究.2008(11)：75-80.
[21]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.
[22]方毅,桂鹏,亚太地区股票市场的联动程度-基于次级贷冲击的研究,世界经济研究,2010.8
[23]黄飞雪,谷静,李延喜,苏敬勤.金融危机前后的全球主要股指联动与动态稳定性比较.2010.11
[24]母宇,后金融危机时代关于中国股市与世界重要股市联动性的思考,金融经济,2009,100-102