Research On CPPI Strategy Of Risk Multiplier Selection Based On Quantile Condition

The theory of portfolio insurance originated in the United States in 1980 s.By constructing the combination of stock and put option,we can ensure that the final value of portfolio does not fall below the value of the bottom line setted at the beginning of the period.Portfolio insurance strategy is mainly concerned with two types of assets.Part of the investment in risky assets is mainly to obtain the benefits from the rising of risk assets.The investment in the risk-free asset is used to lock the downside risk and guarantee the lowest value of portfolio when the market fell.Because the portfolio insurance strategy can lock the market risk,it is an important investment strategy to avoid the system risk.It is welcomed by the capital preservation fund,pension fund and other investment institutions.In a variety of portfolio insurance strategies,constant proportion portfolio insurance strategy(CPPI)is the most commonly strategy.It is easy to operate,doesn't have complicated formulas and is easy to understand.The most critical parameter in the strategy is Risk Multiplier.But the strategy assumes that the risk multiplier is fixed.The final value of the portfolio only depends on the maturity of the underlying market price and the execution price.But the market price is constantly changing,it will make the final value of the portfolio is very uncertain.Therefore,the setting of the parameters and the optimization of the model have gradually become the focus of the study.There are a lot of researches on the Risk Multiplier in the existing literatures,and there are many researches on the dynamic risk multiplier,but the introduction of quantile to select the risk multiplier is less.However,the current research in finance and economics,more and more quantile random variables are introduced in an arbitrary probability level.So in this case,whether we can consider at a given probability level(usually 99%)to ensure that the portfolio value is always above the insured amount,so we consider the introduction of quantile conditions to select the Risk Multiplier.So,in this paper,we introduce quantile conditions,assume that the logarithmic return of risk assets obeys the GARCH model and discuss the choice of Risk Multiplier in the CPPI strategy based on quantile conditions.First of all,this paper reviews the theoretical basis of portfolio insurance,such as the definition and classification of portfolio insurance strategies.Secondly,the analysis of risk multiplier selection of the traditional CPPI strategy,then it analyzes risk multiplier selection under quantile conditions and GARCH model.Then,it introduces the CPPI risk multiplier selection model based on conditional quantile.And it is the performance evaluation of the choice of CPPI risk multiplier based on quantile condition.Using different quantiles and different floor analyzes the risk multiplier selection and the market performance of the strategy at three kinds of market quotation and compared with the traditional CPPI strategy.The results show that,after the introduction of quantile conditions,compared with the general choice of risk multiplier is not more than 5,the choice of the risk multiplier has been improved.The lower the demand for capital preservation probability,the smaller the quantile,the higher the risk multiplier.And it has different impact of different market conditions under different quantile.The risk multiplier is the biggest in bull market,shock market next and is the lowest in the bear market.In the bull market,the effect of the CPPI strategy based on quantile conditions is best,it can take full advantage the benefit from the rising market.At the same time,in short and volatile market conditions,it also can achieve the purpose of capital preservation and achieve the most important goal of the CPPI strategy.In a word,the introduction of quantile conditions improves the choice of risk multiplier,it can both achieve the effect of capital preservation and improve the value of the overall portfolio.