【作者】 蒋翠侠；

【导师】 张世英；

【作者基本信息】 天津大学 ， 技术经济及管理， 2007， 博士

【摘要】 金融风险始终伴随着金融市场的发展,如何度量金融风险的变化及其特性并实施有效的规避及防范措施,一直是理论界与实务界共同研究的课题。本文重点讨论广义自回归条件密度建模及其在金融风险动态测度与管理方面的应用,论文主要工作和创新如下:1.在高阶矩的波动性建模研究方面,全面开展了GARCD模型研究工作,初步建立了一元GARCD模型体系;提出了多元GARCD模型;基于Copula技术,给出多元GARCHSK模型和多元GARCD模型的参数估计方法,完善了波动性建模理论体系。2.在高阶矩风险的含义、形成机理及特征研究方面,对高阶矩风险的含义进行了界定;从金融市场信息到达的非线性性质引起投资者交易的非线性行为出发解释了峰度风险产生的原因,从金融资产价格对金融市场信息反应的非对称性角度出发解释了偏度风险产生的原因;最后,在时域和频域中分别讨论了高阶矩风险与低阶矩风险之间关系。3.在动态金融风险溢出性研究方面,构建了一元因子GARCD-JSU模型,给出了高阶矩(前四阶矩)风险在世界范围、地区范围内的溢出效应的判别方法;利用多元条件Copula-GARCHSK模型和Copula-GARCD模型进行了实证研究。4.在动态金融风险管理研究方面,全面系统地研究了基于VaR的金融风险管理方法,在二阶矩VaR测度的基础上,给出动态VaR与CVaR的测度方法,进一步给出其组合投资决策模型;提出了高阶矩VaR的概念,基于JSU分布给出其静态与动态测度方法;建立了收益-风险分析的一般框架。5.在动态组合投资选择研究方面,分别基于多目标优化技术与效用理论,构建了两类高阶矩组合投资决策模型,对两类模型的有效性从理论与实证两个层面进行了对比;并提出利用MATLAB软件中带有约束条件的非线性优化工具“fmincon”对两类模型进行求解。6.在高频数据的波动性建模方面,利用高频金融时间序列的特点将“已实现”波动的研究扩展到“已实现”高阶矩,进而构建了基于“已实现”高阶矩的组合投资决策模型,用以讨论高阶矩风险分散问题,取得了较好的实证效果。本论文是国家自然科学基金资助项目《多变量矩序列长期均衡关系及动态金融风险规避策略研究》(No:70471050)的组成部分。更多还原

【Abstract】 Accompanied by financial risk all time, financial market has made great progress. It is common problem on how to measure the change and character of financial risk and how to avoid the risk in terms of theory and practice. In this dissertation, the technique of generalized autoregressive conditional density modeling is discussed in detail. After that, its applications in measure and management of financial risk are also studied primarily. The main work and innovations of the dissertation include:1. In the area of volatility modeling about higher moments, GARCD model is discussed comprehensively and deeply. In the dissertation, the system of univariate GARCD has been established preliminarily. To simulate the character of multi-asset, multivariate GARCD model is proposed. Based on Copula technique, the estimation methods for parameters of multivariate GARCHSK model and multivariate GARCD model is analyzed in detail.2. In aspects of definition, formation and character of higher moments risk, the sense of higher moments risk has been demonstrated. The cause of kurtosis is explained by the information flows reach the market in a non-linear fashion. Moreover, the skewness risk is cased by the asymmetry of financial information response. In the end, the relation between higher moments and the first two moments are analyzed in time domain and frequency domain respectively.3. As far as dynamic financial risk spillover is concerned, univariate factor GARCD-JSU model is proposed to describe higher moments risk spillover in worldwide and regional wide. The empirical research is made through multivariate conditional Copula-GARCHSK model and Copula-GARCD model.4. Based on VaR, methodologies to financial management has been studied in detail. Under the framework of the first two moments, dynamic VaR and CVaR are defined, and the model for dynamic portfolio selection is proposed. Under the framework of higher moments, the definition of higher moments VaR is suggested, and the measure of HVaR is demonstrated through JSU distribution.5. Based on PGP technique and utility theory, two kinds of models for dynamic portfolio selection under higher moments are established respectively. In the dissertation, these models are compared with each other from theoretical and empirical view. We find that these models can be solved by the function“fmincon”, a tool for nonlinear optimization, in MATLAB software. 6. To our knowledge, high frequency data contains more information than low frequency data. Realized volatility has been extended to realized higher moments. And then, the dynamic portfolio selection model is proposed to disperse the higher moments risk. In the end, the empirical results show that realized higher moments is a good method for risk measure.The research is sponsored by National Natural Science Foundation of China: Research on Long Run Eqilibrium in Multivariate Moments Series and Avoiding Tactics of Dynamic Financial Risk (No. 70471050).更多还原