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本文基于pair_Copula_CVaR模型对保险投资组合进行优化。选用977个交易日的上证指数、上证国债指数、上证基金指数和SHIBOR为样本数据,采用GARCH模型对单个资产建模,运用pair_Copula模型估计投资组合的联合分布,并通过Monte Carlo方法得到投资组合未来收益的多个可能情景,求得组合VaR和CVaR,得到使CVaR最小时的投资比例。实证研究表明,为了使风险值最小,保险资金可以将大部分的资金投资到风险较小的银行存款和国债中,适当地投资到风险较大的股票和基金中。通过理论最优比例结合实际情况可动态调整保险投资的结构,有利于保险资产的合理配置和保险资金的高效利用。
This article optimizes the insurance portfolio based on the pair_Copula_CVaR model. Using the 977 trading days of the Shanghai Composite Index, Shanghai Bond Index, the Shanghai Composite Fund Index and SHIBOR as the sample data, using GARCH model to model a single asset, the use of pair_Copula model to estimate the joint portfolio distribution and portfolio by Monte Carlo method to get the future Multiple possible scenarios of returns yield the combined VaR and CVaR, yielding the investment ratio that minimizes CVaR. Empirical studies show that in order to minimize the risk value, insurance funds can invest most of the funds in bank deposits and bonds with less risk, and properly invest in riskier stocks and funds. Through the optimal proportion of the theory and the actual situation, the structure of the insurance investment can be dynamically adjusted, which is conducive to the rational allocation of insurance assets and the efficient use of insurance funds.