基于复杂网络的金融风险跨市场传导机制研究——以金融危机时期(2007~2009年)数据为例

doi:10.12005/orms.2018.0194

运筹与管理 ›› 2018, Vol. 27 ›› Issue (8): 155-161.DOI: 10.12005/orms.2018.0194

基于复杂网络的金融风险跨市场传导机制研究——以金融危机时期(2007~2009年)数据为例

刘超^1,2,郝丹辉¹,唐孝文^1,2,刘宸琦³

1.北京工业大学经济与管理学院,北京 100124;
2.北京现代制造业发展基地,北京 100124;
3.迪金森学院数学与计算机科学系,美国卡莱尔市 17013

收稿日期:2016-10-10 出版日期:2018-08-25
作者简介:刘超(1969-),男,山东枣庄人,博士生导师,教授,研究方向:社会经济系统分析与优化;郝丹辉(1994-),男,硕士研究生,研究方向:社会经济系统分析与优化;唐孝文(1980-),男,博士,讲师,研究方向:战略管理与组织创新。
基金资助:
国家自然科学基金项目(61773029,61273230);北京市属高校高水平教师队伍建设支持计划长城学者培养计划项目(CIT&TCD20170304);北京工业大学研究生科技基金(ykj-2016-00149)

A Study of Cross-market Financial Risks Contagion Mechanism Based on Complex Network Theory: For Data Around Financial Crisis(2007~2009)

LIU Chao^1,2, HAO Dan-hui¹ TANG Xiao-wen^1,2, LIU Chen-qi³

1.School of Economics and Management, Beijing University of Technology, Beijing 100124, China;
2.Research Base of Beijing Modern Manufacturing Development,Beijing 100124, China;
3.Department of Mathematics and Computer Science, Dickinson College, Carlile City 17013, America

Received:2016-10-10 Online:2018-08-25

摘要/Abstract

摘要： 金融系统具有典型的非线性复杂系统的特征,其多层次和多重反馈特性使得金融风险跨市场传导效应更加复杂多变。选取2007~2009年金融危机时期的相关数据,构建金融网络,并采用最小生成树(MST)的方法对金融风险跨市场传导机制进行实证分析。结果表明:我国金融市场具有明显的小世界特征;金融危机期间金融市场内部各子市场间的关联程度显著加强;股票、债券、房地产和外汇市场是系统重要性市场,需要重点监控;对金融风险跨市场传导的潜在路径进行了识别,为宏观审慎监管提供了理论基础。

关键词: 金融市场, 复杂网络, 最小生成树, 金融风险跨市场传导

Abstract: Financial system has a feature of typical nonlinear complex systems, whose multi-level and multi-feedback effects make cross-market financial risks contagion more complicated and changeable. Selecting relevant data of China’s economy around financial crisis(2007~2009), we divide the financial sub market, construct financial network and apply Minimum Spanning Tree (MST) for empirical research on cross-market financial risks contagion mechanism, including the contagion path and dynamic evolution of financial risk. The results reveal that China’s financial market has obvious characteristics of a small world; degree of relevance of sub markets of financial market significantly increases during the financial crisis; stocks market, bonds market, real estate market and foreign exchange market are importance markets of financial system which are at the core position in the China’s financial network and need focusing on monitoring and prevention. We identify the potential contagion path of cross-market financial risks and provide a theoretical basis for macro prudential regulation.

Key words: financial market, complex network, minimum spanning tree, cross-market financial risks contagion

中图分类号:

F832.5

刘超,郝丹辉,唐孝文,刘宸琦. 基于复杂网络的金融风险跨市场传导机制研究——以金融危机时期(2007~2009年)数据为例[J]. 运筹与管理, 2018, 27(8): 155-161.

LIU Chao, HAO Dan-hui TANG Xiao-wen, LIU Chen-qi. A Study of Cross-market Financial Risks Contagion Mechanism Based on Complex Network Theory: For Data Around Financial Crisis(2007~2009)[J]. Operations Research and Management Science, 2018, 27(8): 155-161.

参考文献

[1] 鲍勤,孙艳霞.网络视角下的金融结构与金融风险传染[J].系统工程理论与实践,2014,34(9):2202-2211.
[2] 史建平,高宇.宏观审慎监管理论研究综述[J].国际金融研究,2011,(8):66-74.
[3] 刘超.系统科学金融理论[M].北京:科学出版社,2013.
[4] 陈建青,王擎,许韶辉.金融行业间的系统性金融风险溢出效应研究[J].数量经济技术经济研究,2015,(9):89-100.
[5] 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[J].系统工程理论与实践,2010,30(10):1729-1740.
[6] Wen X, Wei Y, Huang D. Measuring contagion between energy market and stock market during financial crisis: a copula approach[J]. Energy Economics, 2012, 34(5): 1435-1446.
[7] Andreou E, Matsi M, Savvides A. Stock and foreign exchange market linkages in emerging economies[J]. Journal of International Financial Markets Institutions & Money, 2013, 27(27): 248-268.
[8] 闻岳春,王婕,程天笑.国内股市与国际股市、大宗商品市场的溢出效应研究[J].国际金融研究,2015,340(8):31-43.
[9] Alotaibi A R, Mishra A V. Global and regional volatility spillovers to GCC stock markets[J]. Economic Modelling, 2015, 45: 38-49.
[10] Zhao H. Dynamic relationship between exchange rate and stock price: evidence from china[J]. Research in International Business & Finance, 2010, 24(2): 103-112.
[11] Dean W G, Faff R W, Loudon G F. Asymmetry in return and volatility spillover between equity and bond markets in australia[J]. Pacific-Basin Finance Journal, 2010, 18(3): 272-289.
[12] Naylor M, Rose L C, Moyle B J. A network theory of financial cascades[J]. Social Science Electronic Publishing, 2008.
[13] Eom C, Kwon O, Jung W S, et al. The effect of a market factor on information flow between stocks using the minimal spanning tree[J]. Physica A Statistical Mechanics & Its Applications, 2009, 389(905.2043): 1643-1652.
[14] 邓超,陈学军.基于复杂网络的金融传染风险模型研究[J].中国管理科学,2014,22(11):11-18.
[15] Schwarcz S L. Systemic risk[J]. The Georgetown Law Journal, 2008, 97(466): 193-249.
[16] 何淑兰.热钱、房地产价格波动与金融体系稳定——基于SVAR模型的实证分析[J].经济与管理,2013,27(1):25-31.
[17] Kiyotaki N, Moore J. Balance-sheet contagion[J]. American Economic Review, 2002, 92(2): 46-50.
[18] Daníelsson J, Zigrand J P. Equilibrium asset pricing with systemic risk[J]. Economic Theory, 2008, 35(2): 293-319.
[19] Gibert C L. How to understand high food prices[J]. Journal of Agricultural Economics, 2010, 61(2): 398-425.

基于复杂网络的金融风险跨市场传导机制研究——以金融危机时期(2007~2009年)数据为例

A Study of Cross-market Financial Risks Contagion Mechanism Based on Complex Network Theory: For Data Around Financial Crisis(2007~2009)

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