金融资产收益非对称性的多标度分形测度及其在VaR计算中的应用

doi:10.16381/j.cnki.issn1003-207x.2015.03.002

中国管理科学 ›› 2015, Vol. 23 ›› Issue (3): 13-23.doi: 10.16381/j.cnki.issn1003-207x.2015.03.002

金融资产收益非对称性的多标度分形测度及其在VaR计算中的应用

王鹏^1,2, 袁小丽³

1. 西南财经大学中国金融研究中心, 四川成都 610074;
2. 金融安全协同创新中心, 四川成都 610074;
3. 西南财经大学金融学院, 四川成都 611130

收稿日期:2013-01-26 修回日期:2013-08-07 出版日期:2015-03-20 发布日期:2015-03-18
作者简介:王鹏(1981-),男(汉族),山东宁阳人,西南财经大学中国金融研究中心,博士,副教授,研究方向:金融工程与风险管理.
基金资助:
国家自然科学基金资助项目(71101119);西南财经大学和四川省教育厅创新团队建设项目(JBK130401)

A VaR Moldel Based on Multifractal Asymmetry Measurement

WANG Peng^1,2, YUAN Xiao-li³

1. Institute of Chinese Financial Studies, Southwest University of Finance and Economics, Chengdu 610074, China;
2. Collaborative Innovation Center of Financial Security, Chengdu 610074, China;
3. School of Finance, Southwest University of Finance and Economics, Chengdu 611130, China

Received:2013-01-26 Revised:2013-08-07 Online:2015-03-20 Published:2015-03-18

摘要/Abstract

摘要： 通过提炼多标度分形分析过程中所产生的对描述金融资产收益非对称特征有益的统计信息,提出了一种新的资产收益非对称测度——多标度分形非对称测度(Multifractal asymmetry measurement)Δf,并以沪深300指数长达7年左右的5分钟高频数据为实证样本,通过两种不同的VaR后验分析(Backtesting analysis)方法,实证对比了Δf测度和传统的偏度系数(Coefficient of skewness)测度在市场风险计算准确性方面的差异。实证结果表明:基于Δf测度的市场风险计算模型的VaR计算精度优于基于偏度系数测度的对应模型,Δf测度具有较偏度系数测度更为优异的对金融资产收益非对称特征的刻画能力。

关键词: 多标度分形理论, 非对称测度, 风险价值, 后验分析

Abstract: For describing asymmetry of financial returns, the validity of traditional measurement, i.e., skewness coefficient, is heavily dependent on the assumption that the data is independently and normally distributed. However, actual data in financial markets often has non-independent and non-normal distribution. So a new measurement should be explored to fit stylized facts of actual financial data. After a preliminary exploration for a long time, fractal analysis are found to provide highly targeted solutions for many problems in traditional research about asymmetry of financial returns. By refining useful statistical information to describe the asymmetric features of financial assets' yields during the process of multifractal analysis, a new asymmetry measurement (Δf) is constructed in this paper,whose theoretical properties is more excellent and are more suitable for typical statistical characteristics of actual financial data. Unconditional coverage test and conditional coverage test are used to compare the VaR computation accuracy differences for CSI 300 index between risk models augmented by the skewness coefficients and the Δf measurement. Empirical results show that the latter has higher VaR estimation accuracy. The new measurement which we present in this paper provides a more suitable tool for asymmetry testing to financial returns. Furthermore, this is a typical result of making use of statistical information embedded in the process of fractal analysis.

Key words: multifractal theory, asymmetry measurement, value at risk, backtesting analysis

中图分类号:

F224
F830

王鹏, 袁小丽. 金融资产收益非对称性的多标度分形测度及其在VaR计算中的应用[J]. 中国管理科学, 2015, 23(3): 13-23.

WANG Peng, YUAN Xiao-li. A VaR Moldel Based on Multifractal Asymmetry Measurement[J]. Chinese Journal of Management Science, 2015, 23(3): 13-23.

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金融资产收益非对称性的多标度分形测度及其在VaR计算中的应用

A VaR Moldel Based on Multifractal Asymmetry Measurement

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