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Study On The Optimal Investment Proportion Of China’s Insurance Companies Based On Copula-Garch Model

Posted on:2014-01-09Degree:MasterType:Thesis
Country:ChinaCandidate:F ZhangFull Text:PDF
GTID:2249330395492422Subject:Finance
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At present, China’s insurance industry competition is becoming increasingly fierce, insurance companies underwriting profit drops continuously, the insurance company wanted to make a profit must rely on insurance investment business. But China insurance investment return rate is still relatively low, severely affecting the healthy development of the insurance industry,and the unreasonable ratio of investment is one of the key reasons for the low return rate. Therefore, how to optimize investment structure, improve investment income has become the a major challenge for insurance companies.At present, a hot academic research focus on how to obtain the optimal investment proportion of insurance companies, therefore, scholars have constructed a CVaRiety of different models. This paper innovatively combines Copula-Garch model and the mean-CVaR model together, then introduces them into the field of insurance investment proportion,and opens up a new perspective of the study in this field. As we know, the Copula function is one of the most effective tools to measure correlation, because the traditional correlation analysis base on the return rate of assets obeys the normal distribution assumption, while the real financial market data are often not in consistant with this assumption.While Copula function can accurately calculate the joint distribution of several assets in non-normal, nonlinear condition,to solve this problem technically. At the same time, the CVaR method has become the most popular financial risk management methods, it can fully take into account the probability of extreme events, make the risk measure more safe and effective.This paper assumes that the insurance portfolio contains five assets:bank deposits, bonds, corporate bonds, funds, stocks, select Shibor overnight rates, bonds index, corporate bonds index, fund index and stock index to simulate their rates of return. First of all, using GARCH(1,1)-t model to fit the individual asset yield characteristics, obtain single asset’s the marginal distribution; and then use the Copula-t function to describe the correlation structure between these assets and then obtian the joint distribution of investment porfolio’s yield; and then use CVaR instead of CVaRiance as risk measure to establish the mean-CVaR model, with a target of minimal CVaR at a certain level of yield rate, obtainning the proportion of all assets in the optimal portfolio; finally a brief analysis of the empirical results, and proposes the some suggestions.
Keywords/Search Tags:insurance investment portfolio, Copula-Garch model, mean-conditional value-at-risk model, monte carlo simulation
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