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Least-square-based control variate method for pricing options under general factor models

机译:一般因素模型下基于最小二乘的控制变量定价方法

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This paper proposes a class of simple but efficient control variate method for pricing derivatives under multiple factor models including stochastic volatility and stochastic interest rate model. The control variate can help us to obviously reduce the error of Monte Carlo simulation. Briefly speaking, we construct a virtual asset with deterministic volatility and deterministic interest rate which has high correlation with the original underlying asset based on the method of least square, and use derivative written on the virtual asset as control variate in pricing derivative written on the original underlying asset. Some theoretic results can help us to understand the mechanism of a control variate. Numerical examples show that simulation error is significantly reduced by our method. The advantage of our method is that it has no analytic form request for the underlying asset model, so the method is flexible to deal with and broadly applicable for derivative pricing.
机译:针对随机波动率和随机利率模型​​等多因素模型,提出了一种简单有效的衍生变量定价控制方法。控制变量可以帮助我们明显减少蒙特卡洛模拟的误差。简而言之,我们基于最小二乘方法构造一个具有确定性波动性和确定性利率的虚拟资产,该虚拟资产与原始基础资产具有高度相关性,并使用虚拟资产上写的衍生工具作为原始资产上写的定价衍生工具的控制变量。基础资产。一些理论结果可以帮助我们理解控制变量的机制。数值算例表明,利用我们的方法可以大大降低仿真误差。我们方法的优点是它不需要基础资产模型的分析形式请求,因此该方法处理起来很灵活,并且广泛适用于衍生产品定价。

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