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Series Expansion and Fourth-Order Global Padé Approximation for a Rough Heston Solution

机译:系列扩展和第四阶全球Padé近似粗糙的Heston解决方案

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The rough Heston model has recently been shown to be extremely consistent with the observed empirical data in the financial market. However, the shortcoming of the model is that the conventional numerical method to compute option prices under it requires great computational effort due to the presence of the fractional Riccati equation in its characteristic function. In this study, we contribute by providing an efficient method while still retaining the quality of the solution under varying Hurst parameter for the fractional Riccati equations in two ways. First, we show that under the Laplace–Adomian-decomposition method, the infinite series expansion of the fractional Riccati equation’s solution corresponds to the existing expansion method from previous work for at least up to the fifth order. Then, we show that the fourth-order Padé approximants can be used to construct an extremely accurate global approximation to the fractional Riccati equation in an unexpected way. The pointwise approximation error of the global Padé approximation to the fractional Riccati equation is also provided. Unlike the existing work of third-order global Padé approximation to the fractional Riccati equation, our work extends the availability of Hurst parameter range without incurring huge errors. Finally, numerical comparisons were conducted to verify that our methods are indeed accurate and better than the existing method for computing both the fractional Riccati equation’s solution and option prices under the rough Heston model.
机译:粗糙的Heston模型最近被证明与金融市场中观察到的经验数据非常一致。然而,模型的缺点是,由于其特征函数中的分数Riccati方程存在,因此在其特征函数中存在的情况下,以计算期权价格计算的传统数值方法需要很大的计算工作。在这项研究中,我们通过提供一种有效的方法来提供有效的方法,同时仍然以两种方式为分数Riccati方程的变化仓鼠参数仍然保持溶液的质量。首先,我们表明,在拉普拉斯 - adomian - 分解方法下,分数Riccati公式的解决方案的无限串联扩展对应于从先前工作的现有扩展方法至少到第五顺序。然后,我们表明,第四阶Padé近似剂可用于以意想不到的方式构建与分数Riccati方程的极其准确的全局近似。还提供了全局PADÉ近似到分数Riccati方程的点近似误差。与第三阶全局Padé近似的现有工作不同,我们的工作扩展了赫斯特参数范围的可用性而不会产生巨大的错误。最后,进行了数值比较,以验证我们的方法确实准确且比现有的方法更好地计算了粗糙的Heston模型下的分数Riccati公式的解决方案和期权价格。

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