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

【摘要】：當(dāng)前,我國保險業(yè)競爭日趨激烈,保險公司的承保利潤持續(xù)下降,保險公司想要獲利必須依靠保險投資業(yè)務(wù)。但是我國保險投資的收益率仍然較低,嚴(yán)重影響了我國保險業(yè)的健康發(fā)展,而導(dǎo)致保險投資收益率偏低的一個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公司面臨的一個重大考驗(yàn)。 目前,保險學(xué)術(shù)界研究的一個熱點(diǎn)問題即為如何求得保險公司的最優(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,CVaR方法已經(jīng)成為當(dāng)前金融風(fēng)險管理中最熱門的風(fēng)險度量方法之一,它能充分考慮到小概率極端事件的發(fā)生,使風(fēng)險衡量更為安全、有效。 本文假設(shè)保險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模型來擬合單個資產(chǎn)的收益率數(shù)據(jù),求得單個資產(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

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李婷;張衛(wèi)國;;風(fēng)險資產(chǎn)組合均值-CVaR模型的算法分析[J];安徽大學(xué)學(xué)報(自然科學(xué)版);2006年06期

2 蔣洪浪;保險投資的資金配置策略[J];保險研究;2002年08期

3 王燕;;基于我國數(shù)據(jù)的壽險資產(chǎn)最優(yōu)配置模型[J];保險研究;2007年11期

4 吳鈺;;我國保險資金運(yùn)用芻議[J];保險研究;2008年01期

5 曲揚(yáng);;保險資金運(yùn)用的國際比較與啟示[J];保險研究;2008年06期

6 秦振球,俞自由;保險公司投資比例問題研究[J];財(cái)經(jīng)研究;2003年02期

7 劉小茂,李楚霖,王建華;風(fēng)險資產(chǎn)組合的均值—CVaR有效前沿(Ⅰ)[J];管理工程學(xué)報;2003年01期

8 何琳潔,文鳳華,馬超群;基于一致性風(fēng)險價值的投資組合優(yōu)化模型研究[J];湖南大學(xué)學(xué)報(自然科學(xué)版);2005年02期

9 林旭東,鞏前錦;正態(tài)條件下均值-CVaR有效前沿的研究[J];管理科學(xué);2004年03期

10 丁立剛;唐俊;;CVaR約束下最優(yōu)投資組合[J];內(nèi)蒙古大學(xué)學(xué)報(自然科學(xué)版);2007年05期

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本文編號：1916744