H基金公司股票投资市场风险管理研究

发布时间：2018-05-03 03:35

本文选题：金融风险 + 在险价值　；参考：《上海交通大学》2012年硕士论文

【摘要】：风险的确切定义是当资产价值、股票价格和盈利情况出现非预期结果时的不确定性。如何有效预测并度量风险,对于风险管理有决定性意义。对于目前股票二级市场重要的投资主体之一基金公司来说,也需要建立一套完善的风险预测和管理机制,投资者更为关注的是投资左半区间可能出现的最大亏损,即一定概率下可能的最大投资损失。通过调研文章发现目前H基金公司对于基金在股票市场风险管理和损失预测的量化方法主要是固定损失比例和近似VaR历史模拟法两种,并希望引入不同VaR方法进行方法比较,从而选取出更为有效的预测和管理方法。本篇论文由此选取H基金旗下的两种最典型基金类型作为研究对象,分别是：指数型股票基金和非指数型开放式股票基金。加入几种不同的VaR方法(Delta-正态VaR,历史模拟VaR, CVaR,方差-协方差VaR)和基金原有管理方法进行比较。通过运用Eviews和Excel工具并使用LR似然比后测检验验证各种方法的准确程度,从而得出其中比较有效的方法。通过实证研究,可以得到的结论是：一、对于指数型股票基金,分别进行了一年期,三年期VaR预测,并选取了不同的时间区间来屏蔽牛熊市带来的趋势影响,外加不同置信水平(99%、95%、90%)共12种情况。使用似然比后测检验表明,历史模拟VaR和Delta-正态VaR分别通过了的11次(91.7%)和10次(83.3%),优于其他模型。CVaR方法在置信水平比较低时误差较大,总共通过4次(33.3%)检验,而固定损失比例方法在大部分检验中都无法通过,仅通过3次(25%)。最后用Jarque-Bera检验验证了模型选取的指数是趋向于正态分布的,并用ARCH检验验证指数不存在条件异方差情况,说明以上VaR的计算都是有效的。二、对于非指数型开放式股票基金,方差-协方差VaR和历史模拟VaR预测优于其他模型,两种方法通过了所有似然比后测检验,但历史模拟方法的精确度更高,检验结果更接近于各个置信水平的理论推荐值。同时发现固定损失比例预测在大部分检验中无法通过。最后文章建议H基金管理公司在今后的投资工作中加入Delta-正态模型和方差-协方差模型两种VaR方法并保留历史模拟VaR方法来对旗下基金进行风险度量和管理。而固定损失比例的方法和CVaR由于不够精确和有效建议不再使用。
[Abstract]:The exact definition of risk is uncertainty when the value of assets, stock prices, and earnings are unexpected. How to effectively predict and measure risk is of decisive significance to risk management. For fund companies, one of the most important investors in the secondary stock market, it is also necessary to establish a set of sound risk forecasting and management mechanisms. Investors are more concerned about the maximum losses that may occur in the left half of the stock market. That is, the maximum possible investment loss under a certain probability. It is found that the quantitative methods for risk management and loss prediction of H fund companies in stock market are mainly fixed loss ratio and approximate VaR historical simulation, and it is hoped that different VaR methods will be introduced to compare them. In order to select a more effective prediction and management methods. In this paper, two typical types of H fund are selected as the research object: index stock fund and non exponential open equity fund. Several different VaR methods such as Delta-normal VaR, historical simulation VaR, Cvar, variance-covariance VaR) are added to compare with the original fund management methods. By using Eviews and Excel tools and using LR likelihood ratio test to verify the accuracy of various methods, the more effective methods are obtained. Through empirical research, we can draw the following conclusions: Firstly, for the index stock funds, the one-year and three-year VaR forecasts are carried out respectively, and different time intervals are selected to shield the trend effects of the bull bear market. There are 12 kinds of cases in addition to the different confidence levels 99% 95% and 90%. Using the likelihood ratio post-test, it is shown that the historical simulation VaR and Delta-normal VaR passed 11 times 91.7) and 10 times 83.3% respectively, which is better than other models. The Cvar method has a big error when the confidence level is low, and it has passed 4 times of 33. 3) test. However, the fixed loss ratio method can not be passed in most tests, only three times. Finally, the Jarque-Bera test is used to verify that the index selected by the model tends to normal distribution, and the ARCH test is used to verify that the index does not have conditional heteroscedasticity, which shows that the calculation of the above VaR is effective. Second, for non-exponential open-end stock funds, variance-covariance VaR and historical simulation VaR prediction are superior to other models. The two methods have passed all likelihood ratio post-test tests, but the historical simulation methods have higher accuracy. The test results are closer to the theoretical recommended values of each confidence level. At the same time, it is found that the prediction of fixed loss ratio can not be passed in most tests. Finally, the paper suggests that H fund management company should add Delta-normal model and variance-covariance model to the future investment work and retain the historical simulated VaR method to measure and manage the risk of its funds. The fixed loss ratio method and CVaR are no longer used due to their inaccuracy and effectiveness.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F224;F832.51

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