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Risk metrics method and computer algorithms designed to achieve VaR

机译:旨在实现VaR的风险度量方法和计算机算法

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The article firstly analyzes the Markowitz''s Mean-Variance Model, with The Monte Carlo method achieving the computer simulation of efficient frontier. Against the shortage of the model, this test allows short selling, using the Zero-Utility to optimize the objective, and improving the model with chance constraints, then using the Risk Metrics way to design the VaR algorithm, realized by computer. Finally, the paper provides a practical example, implementing the practical application of the algorithm. What''s more, this study proves that “the high risk, the high payoff” is a character of risk investment. It shows the result is more practical which is optimized by Utility Function. By comparing, we find that the risk aversion coefficient has big influence on the economic benefits of the investors. We can say, VaR provides a powerful basis for the effective selection of investment combination and the assessment of risk and value.
机译:本文首先分析了Markowitz的均值-方差模型,利用蒙特卡洛方法实现了有效边界的计算机仿真。针对模型的不足,该测试允许卖空,使用零效用来优化目标,并在机会约束下改进模型,然后使用风险度量方法来设计由计算机实现的VaR算法。最后,本文提供了一个实例,实现了该算法的实际应用。而且,这项研究证明“高风险,高回报”是风险投资的特征。它表明结果更加实用,并且通过效用函数进行了优化。通过比较,我们发现风险规避系数对投资者的经济利益影响很大。可以说,VaR为有效选择投资组合以及评估风险和价值提供了强大的基础。

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