本文選題：保險(xiǎn)投資組合 + Copula-Garch模型　； 參考：《浙江工商大學(xué)》2013年碩士論文

【摘要】：當(dāng)前,我國保險(xiǎn)業(yè)競爭日趨激烈,保險(xiǎn)公司的承保利潤持續(xù)下降,保險(xiǎn)公司想要獲利必須依靠保險(xiǎn)投資業(yè)務(wù)。但是我國保險(xiǎn)投資的收益率仍然較低,嚴(yán)重影響了我國保險(xiǎn)業(yè)的健康發(fā)展,而導(dǎo)致保險(xiǎn)投資收益率偏低的一個(gè)重要原因就是投資比例的不合理。由此可見,如何優(yōu)化投資結(jié)構(gòu),提高投資收益已成為各保險(xiǎn)公司面臨的一個(gè)重大考驗(yàn)。 目前,保險(xiǎn)學(xué)術(shù)界研究的一個(gè)熱點(diǎn)問題即為如何求得保險(xiǎn)公司的最優(yōu)投資比例,為此,學(xué)者們構(gòu)建了各種不同的模型。本文創(chuàng)新性地將Copula-Garch模型和均值-CVaR模型進(jìn)行有機(jī)結(jié)合,引入到保險(xiǎn)投資比例的研究上來,為這一領(lǐng)域的研究打開了新的視角。我們知道,Copula函數(shù)是衡量相關(guān)性最有效的工具之一,因?yàn)閭鹘y(tǒng)的相關(guān)性分析建立在資產(chǎn)收益率符合正態(tài)分布的假設(shè)下,而現(xiàn)實(shí)的金融市場數(shù)據(jù)往往不符合這一特點(diǎn),但Copula函數(shù)可以準(zhǔn)確求得非正態(tài)、非線性條件下多項(xiàng)資產(chǎn)的聯(lián)合分布,從技術(shù)上解決了這一難題。與此同時(shí),CVaR方法已經(jīng)成為當(dāng)前金融風(fēng)險(xiǎn)管理中最熱門的風(fēng)險(xiǎn)度量方法之一,它能充分考慮到小概率極端事件的發(fā)生,使風(fēng)險(xiǎn)衡量更為安全、有效。 本文假設(shè)保險(xiǎn)投資組合中含有銀行存款、國債、企業(yè)債、基金、股票五項(xiàng)資產(chǎn),選取Shibor隔夜拆借利率、國債指數(shù)、企業(yè)債指數(shù)、基金指數(shù)和股票指數(shù)來分別模擬其收益率。首先,利用Garch (1,1)-t模型來擬合單個(gè)資產(chǎn)的收益率數(shù)據(jù),求得單個(gè)資產(chǎn)的邊緣分布特征；然后利用Copula-t函數(shù)來求解各資產(chǎn)之間的相關(guān)系數(shù)矩陣,從而得到多個(gè)資產(chǎn)收益率的聯(lián)合分布；接著用CVaR (?)代替方差作為風(fēng)險(xiǎn)度量標(biāo)準(zhǔn),建立均值-CVaR模型,以在一定收益率水平下令CVaR最小為目標(biāo),求得最優(yōu)投資組合中各資產(chǎn)的比重；最后簡要分析了實(shí)證結(jié)果,并提出改善建議。
[Abstract]:At present, the competition of insurance industry in our country is becoming more and more intense, the underwriting profit of insurance company is declining continuously, the insurance company must depend on the insurance investment business to make profit. However, the return rate of insurance investment in China is still low, which seriously affects the healthy development of the insurance industry in China, and an important reason leading to the low return rate of insurance investment is the unreasonable investment ratio. Thus, how to optimize the investment structure and improve investment returns has become a major test faced by insurance companies. At present, one of the hot issues in the research of insurance academia is how to get the optimal investment ratio of insurance companies. For this reason, scholars have constructed various models. This paper innovatively combines the Copula-Garch model with the mean Cvar model, and introduces it into the study of the proportion of insurance investment, which opens a new perspective for the research in this field. We know that the Copula function is one of the most effective tools to measure relevance, because the traditional correlation analysis is based on the assumption that the return on assets conforms to the normal distribution, and the real financial market data often do not conform to this characteristic. However, the Copula function can accurately obtain the joint distribution of multiple assets under the condition of non-normal and nonlinear conditions, which solves this problem technically. At the same time, CVaR method has become one of the most popular risk measurement methods in current financial risk management. It can fully consider the occurrence of small probability extreme events and make risk measurement safer and more effective. This paper assumes that the insurance portfolio contains five assets: bank deposits, treasury bonds, corporate bonds, funds and stocks, and selects Shibor overnight borrowing rate, treasury bond index, enterprise bond index, fund index and stock index to simulate the return rate respectively. Firstly, the Garch model is used to fit the yield data of a single asset, and the edge distribution characteristic of a single asset is obtained, and then the correlation coefficient matrix of each asset is solved by using the Copula-t function, and the joint distribution of multiple asset returns is obtained. CVaR) Instead of variance as a measure of risk, a mean value CVaR model is established, in order to order the minimum of CVaR at a certain rate of return, the proportion of each asset in the optimal portfolio is obtained. Finally, the empirical results are briefly analyzed, and suggestions for improvement are put forward.
【學(xué)位授予單位】：浙江工商大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F842.3;F224

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