基于多元GARCH模型及VaR方法对上证行业板块指数的分析

发布时间：2018-05-12 18:42

本文选题：多元GARCH + 行业指数　；参考：《西南财经大学》2013年硕士论文

【摘要】：在一个经济体系之中,各个行业形成了一个相互影响的复杂系统。为了探讨行业指数收益率之间的波动溢出特点并进行风险性分析,本文将选择应用基于多元GARCH模型的VaR方法,在能很好地刻画出行业指数的波动性特征的基础上,同时也能有效地测度风险。本文以上海证券的行业板块指数为研究对象,选择农林牧渔、食品饮料、建筑建材、房地产、交运设备、交通运输、金融服务、商业贸易以及餐饮旅游九个行业指数进行行业间动态性分析。本文将按照产业链上下游关系把上海证券中的九个行业板块指数分成六组,研究具有产业链关系的行业间的动态关系,由此也可以对行业所代表的产业间的产业链关系和整个宏观经济结构的内在关系有一定的说明阐释意义,对人们在金融投资中行业的选择、金融风险管理有一定的借鉴意义。在实证的部分,分别对每组序列建立多元GARCH模型,通过对其波动率变化情况和时变相关图的综合比较,由此对六个序列组彼此之间的波动溢出情况做出详尽的分析,得出中国经济中不同行业间波动溢出效应不同的特征,从而为投资者在行业之间的投资选择提供了一定借鉴意义,比如给予了这样的借鉴意义：对于具有波动率增加导致时变相关系数也同样增加的波动溢出效益特征的行业组,可以在遇到市场波动率增加的时候选择这样的行业组合去追求风险收益,而为了规避风险则应避免这样的选择；对于具有波动率增加导致时变相关系数减小的波动溢出效益特征的行业组,则为在遇到市场波动率增加的时候提供了降低风险的选择；最后利用波动溢出分析过程在所建立的二元GARCH模型下结合风险度量制方法分别对六组行业指数序列进行了多头头寸VaR值的计算与比较,从本文的分析可以认为我国在二三产业中的行业可能相较而言有更大风险,同样对行业投资提供了一定的借鉴意义。
[Abstract]:In an economic system, industries form a complex system of interaction. In order to study the volatility spillover characteristics among the industry index returns and analyze the risk, this paper will choose to apply the VaR method based on the multivariate GARCH model, on the basis of which the volatility characteristics of the industry index can be well described. At the same time, it can measure the risk effectively. In this paper, the industry sector index of Shanghai Securities as the research object, select agriculture, forestry, animal husbandry, food and beverage, building materials, real estate, transportation equipment, transportation, financial services, Nine industry indices of commercial trade and catering tourism are analyzed in terms of inter-industry dynamics. In this paper, according to the upstream and downstream relationships of the industrial chain, the nine industry sector indices in Shanghai Securities are divided into six groups to study the dynamic relationship between industries with industrial chain relationship. It can also explain the industrial chain relationship between industries and the internal relationship of the whole macroeconomic structure. It can be used for reference to the choice of industry in financial investment and financial risk management. In the empirical part, the multivariate GARCH model is established for each sequence, and the volatility variation and time-varying correlation graph are compared synthetically to make a detailed analysis of the volatility spillover between the six sequence groups. The characteristics of volatility spillover effects among different industries in Chinese economy are obtained, which provide some reference for investors to choose their investment in different industries. For example, it can be used for reference: for industry groups with the characteristics of volatility increasing and time-varying correlation coefficient increasing as well as volatility spillover benefits, We can choose this kind of industry combination to pursue the risk return when the market volatility increases, but in order to avoid the risk, we should avoid this choice; For the industry groups with the characteristics of volatility increasing and time-varying correlation coefficient decreasing, the risk reduction options are provided when the market volatility increases. Finally, by using the volatility spillover analysis process under the established binary GARCH model and the risk measurement method, we calculate and compare the VaR value of the long positions in six groups of industry index series. From the analysis of this paper, it can be concluded that the industry of our country in the secondary and tertiary industries may have more risk than that of the industry, and it also provides a certain reference for the investment of the industry.
【学位授予单位】：西南财经大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F832.51;F224

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