基于分位数条件的CPPI策略风险乘数选择的研究
发布时间：2018-08-08 19:47
【摘要】：投资组合保险理论兴起于20世纪80年代的美国,通过构造股票和看跌期权的组合,保证投资组合最终价值不跌破期初设置的价值底线。投资组合保险策略主要涉及两类资产,投资于风险资产的部分主要是为了获得风险资产上升的收益,无风险资产的部分则主要是保证投资组合在市场行情下跌时,期末总资产不至于跌破要保额度,主要是为了锁定下行风险。由于投资组合保险策略能够锁定市场风险,是规避系统风险的一种重要投资策略,因而广受保本基金、养老基金等投资机构的欢迎和青睐。在各种不同的投资组合保险策略中,固定比例投资组合保险策略(CPPI策略)因操作简单灵活,没有复杂的计算公式,容易理解,成为了目前最常用的一种策略。其中策略中最关键的参数是风险乘数m,但该策略假定风险乘数是固定不变的,投资组合期末价值仅取决于到期日时标的风险资产的市场价格和执行价格(保险额度),但是市场价格是不断波动变化的,它会使投资组合的期末价值具有很大的不确定性。因此,策略中各参数的设置、模型的不断优化等逐渐成为了研究的重点。现有的文献对风险乘数的研究有很多,关于动态风险乘数的研究也不少,引入分位数来选择风险乘数的却较少。但是,目前关于金融学和经济学的研究中,引入随机变量在任意概率水平下的分位点的越来越多。所以在这种情况下,我们是否可以考虑在一个给定的概率水平(通常为99%)下,保证投资组合价值总是在要保额度之上,这样考虑引入分位数条件来选择风险乘数。因此本文的研究重点在于引入分位数条件、假设风险资产的对数收益服从GARCH模型,讨论基于分位数条件的CPPI策略中的风险乘数的选择问题。首先,对投资组合保险策略的定义、分类等组合保险方面的理论基础进行了梳理回顾。其次,分析传统CPPI策略下风险乘数的选择,接着分析引入分位数条件和GARCH模型后,基于分位数条件的CPPI策略中风险乘数的选择。然后,概括基于分位数条件的CPPI策略风险乘数选择的模型,对基于分位数条件的CPPI策略风险乘数的选择进行绩效评估,采用不同的分位数和不同的要保额度,分别分析在多头、空头和震荡三种市场行情下风险乘数的选择以及该策略的表现,并与传统的CPPI策略进行对比。研究结果显示,引入分位数条件后,与风险乘数一般选择不超过5相比,风险乘数的选择水平得到了提高。投资者对保本概率要求越低,即分位数越小,风险乘数就会越高;并且不同市场行情下分位数影响不同,多头市场风险乘数最大,震荡市场次之,空头市场风险乘数最低。并且,多头时期基于分位数条件的CPPI策略效果最好,能充分抓住市场行情不断上涨带来的收益,同时在空头和震荡市场条件下也能达到保本的目的,实现CPPI策略最首要的目标。即从整体来看,引入分位数条件后,提高了风险乘数的选择,既能达到保本的效果,也能提高整体组合的价值。
[Abstract]:The theory of portfolio insurance rose in the United States in 1980s. By constructing the combination of stock and put options, the value bottom line is guaranteed at the beginning of the final value of the portfolio. The portfolio insurance strategy mainly involves two types of assets, and the part of the investment in the risk asset is mainly to gain the income of the riskier assets. Part of the riskless assets is mainly to ensure that the total assets of the portfolios are not to be covered by the end of the term when the market prices fall, mainly in order to lock down the downside risk. Because the portfolio insurance strategy can lock the market risk, it is an important investment strategy to avoid the system risk, so it is widely protected by the fund and the pension fund. In a variety of different portfolio insurance policies, the fixed proportional Portfolio Insurance Strategy (CPPI strategy) is easy to understand because of its simple and flexible operation and no complex calculation formula. It has become one of the most commonly used strategies at present. The most critical parameter in the strategy is the Risk Multiplier m, but the strategy assumes that the policy is the most important. The risk multiplier is fixed and fixed, and the final value of the portfolio depends only on the market price and the executive price (insurance quota) of the risk asset of the maturity date, but the market price is constantly fluctuating, and it will make the final value of the portfolio very uncertain. Optimization and so on gradually become the focus of research. There are a lot of research on Risk Multiplier in the existing literature. There are many studies on the dynamic risk multiplier, but few of the risk multipliers are introduced by introducing quantiles. However, in the current research on finance and economics, the increasing of random variables at arbitrary probability level is becoming more and more important. The more we can consider, in this case, whether we can consider a given probability level (usually 99%) to ensure that the portfolio value is always above the degree of guarantee, so that the quantile condition is introduced to select the risk multiplier. Therefore, the emphasis of this paper is to introduce the quantile condition, assuming the logarithmic returns of the risk assets. According to the GARCH model, we discuss the choice of Risk Multiplier in the CPPI strategy based on Quantile condition. First, it reviews the theoretical basis of portfolio insurance policy definition, classification and other combination insurance. Secondly, it analyzes the choice of Risk Multiplier under the traditional CPPI strategy, and then analyzes the quantile condition and GARCH module. After type, the choice of Risk Multiplier in CPPI strategy based on Quantile condition. Then, the model of CPPI policy risk multiplier selection based on Quantile condition is summarized, and performance evaluation is made for the selection of CPPI Policy Risk Multiplier Based on Quantile condition. The selection of the Risk Multiplier and the performance of the strategy are compared with the traditional CPPI strategy. The results show that the selection level of the risk multiplier is improved after introducing the quantile condition and the Risk Multiplier generally chooses not more than 5, and the lower the demand for the investment holders, the smaller the number of quantiles, the smaller the quantile, the smaller the number, the smaller the number of quantiles. The risk multiplier will be higher, and the number of quantiles in different market prices is different, the multihead market risk multiplier is the largest, the market is concussion and the market risk multiplier is the lowest. And the CPPI strategy based on the quantile condition is the best. In the market condition, it can achieve the goal of saving the book and realize the most important goal of the CPPI strategy. In the whole, the selection of the risk multiplier is improved after the introduction of the quantile condition, which can not only achieve the effect of saving the book, but also improve the value of the overall combination.
【学位授予单位】：河南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F224;F832.51
本文编号：2172868
[Abstract]:The theory of portfolio insurance rose in the United States in 1980s. By constructing the combination of stock and put options, the value bottom line is guaranteed at the beginning of the final value of the portfolio. The portfolio insurance strategy mainly involves two types of assets, and the part of the investment in the risk asset is mainly to gain the income of the riskier assets. Part of the riskless assets is mainly to ensure that the total assets of the portfolios are not to be covered by the end of the term when the market prices fall, mainly in order to lock down the downside risk. Because the portfolio insurance strategy can lock the market risk, it is an important investment strategy to avoid the system risk, so it is widely protected by the fund and the pension fund. In a variety of different portfolio insurance policies, the fixed proportional Portfolio Insurance Strategy (CPPI strategy) is easy to understand because of its simple and flexible operation and no complex calculation formula. It has become one of the most commonly used strategies at present. The most critical parameter in the strategy is the Risk Multiplier m, but the strategy assumes that the policy is the most important. The risk multiplier is fixed and fixed, and the final value of the portfolio depends only on the market price and the executive price (insurance quota) of the risk asset of the maturity date, but the market price is constantly fluctuating, and it will make the final value of the portfolio very uncertain. Optimization and so on gradually become the focus of research. There are a lot of research on Risk Multiplier in the existing literature. There are many studies on the dynamic risk multiplier, but few of the risk multipliers are introduced by introducing quantiles. However, in the current research on finance and economics, the increasing of random variables at arbitrary probability level is becoming more and more important. The more we can consider, in this case, whether we can consider a given probability level (usually 99%) to ensure that the portfolio value is always above the degree of guarantee, so that the quantile condition is introduced to select the risk multiplier. Therefore, the emphasis of this paper is to introduce the quantile condition, assuming the logarithmic returns of the risk assets. According to the GARCH model, we discuss the choice of Risk Multiplier in the CPPI strategy based on Quantile condition. First, it reviews the theoretical basis of portfolio insurance policy definition, classification and other combination insurance. Secondly, it analyzes the choice of Risk Multiplier under the traditional CPPI strategy, and then analyzes the quantile condition and GARCH module. After type, the choice of Risk Multiplier in CPPI strategy based on Quantile condition. Then, the model of CPPI policy risk multiplier selection based on Quantile condition is summarized, and performance evaluation is made for the selection of CPPI Policy Risk Multiplier Based on Quantile condition. The selection of the Risk Multiplier and the performance of the strategy are compared with the traditional CPPI strategy. The results show that the selection level of the risk multiplier is improved after introducing the quantile condition and the Risk Multiplier generally chooses not more than 5, and the lower the demand for the investment holders, the smaller the number of quantiles, the smaller the quantile, the smaller the number, the smaller the number of quantiles. The risk multiplier will be higher, and the number of quantiles in different market prices is different, the multihead market risk multiplier is the largest, the market is concussion and the market risk multiplier is the lowest. And the CPPI strategy based on the quantile condition is the best. In the market condition, it can achieve the goal of saving the book and realize the most important goal of the CPPI strategy. In the whole, the selection of the risk multiplier is improved after the introduction of the quantile condition, which can not only achieve the effect of saving the book, but also improve the value of the overall combination.
【学位授予单位】：河南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F224;F832.51
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