基于熵理论的金融市场风险测度及实证研究

发布时间：2018-01-20 06:37

本文关键词： 证券市场熵最大熵分布金融风险　出处：《金融理论与实践》2016年05期 　论文类型：期刊论文

【摘要】：目前主流的金融风险测度方法如Va R、CVa R和ES都是基于均值-方差分析框架,刻画金融风险都通过分析收益率分布,且大多将收益率分布描述成正态分布;然而,这种传统方法不能很好地拟合证券市场诸如尖峰厚尾形态的真实分布。物理学中的熵可以用来度量不确定性程度,选取熵值最大的概率分布可以更好地描述证券市场价格随机过程。将熵理论引入金融风险测度研究中,利用最大熵分布对道琼斯指数、纳斯达克指数、德国DAX指数、法国CAC指数、日经225指数、上证指数等欧、美、亚典型并具有代表性的6个证券指数近20年的日数据进行实证分析得出,这种度量方法可以更加准确刻画证券市场收益率分布以及描述金融风险特征。
[Abstract]:At present, the mainstream financial risk measurement methods, such as Va RN CVR and es, are based on the mean-variance analysis framework, characterizing financial risk by analyzing the return distribution. And most of them describe the return distribution as normal distribution. However, this traditional method can not well fit the true distribution of the stock market such as peak and thick tail shape. Entropy in physics can be used to measure the degree of uncertainty. Selecting the probability distribution with the largest entropy value can better describe the stochastic process of the stock market price. The entropy theory is introduced into the study of financial risk measurement, and the maximum entropy distribution is used for Dow Jones Index and Nasdaq Index. Germany's DAX index, France's CAC index, Nikkei 225 index, Shanghai Stock Exchange index and other European, American, sub-typical and representative of the six securities index in the past 20 years of empirical analysis. This method can more accurately depict the yield distribution of the securities market and describe the characteristics of financial risk.
【作者单位】：广东财经大学金融学院;
【基金】：国家自然科学基金项目(71273067) 教育部人文社会科学规划基金项目(11YJA790089)
【分类号】：F831.5
【正文快照】： 一、引言金融风险测度一直是风险管理的核心内容,而金融风险的特性描述是金融风险测度的基础。现如今,在传统的均值-方差金融理论框架下,描述金融风险的特性一般是对金融市场收益率的随机分布进行刻画,用收益的一、二阶信息(即均值和方差)反映其随机性和变化方式,金融市场的收

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