具有相关性和跳跃的金融模型的分位数敏感性估计

2019 Winter Simulation Conference (WSC) Pub Date : 2019-12-01 DOI:10.1109/WSC40007.2019.9004858

Yijie Peng, M. Fu, Jianqiang Hu, Lei Lei

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引用次数: 3

摘要

在以往的研究中，我们采用广义似然比(GLR)导数估计方法来估计具有相关性和跳跃的金融模型的分位数敏感性。通过提供其他技术难以应用的几个实际设置，实例说明了GLR方法的广泛适用性，数值结果证明了新估计器的有效性。

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Estimating Quantile Sensitivity for Financial Models with Correlations and Jumps

We apply a generalized likelihood ratio (GLR) derivative estimation method in previous works to estimate quantile sensitivity of financial models with correlations and jumps. Examples illustrate the wide applicability of the GLR method by providing several practical settings where other techniques are difficult to apply, and numerical results demonstrate the effectiveness of the new estimator.

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2019 Winter Simulation Conference (WSC)

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