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arXiv 1705.04780q-fin.PR
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指数Lévy期权定价模型的校正与滤波

Calibration and Filtering of Exponential Lévy Option Pricing Models

Stavros J. Sioutis

摘要:

最小二乘校准使用期权溢价和粒子过滤的价格数据,以找到模型参数的准确性是确定的。使用指数Lévy过程的导数模型使用正则化加权最小二乘关于最小熵鞅测度进行校准。将序贯重要性回归用于时间序列参数估计的贝叶斯推断问题,建议分布由扩展卡尔曼滤波器确定。该算法收敛到各自的全局最优值,使用高度并行化的统计优化方法,使用网格的初始位置。这些方法中的每一个都应该产生相同的参数。我们调查这个断言。

英文摘要:

The accuracy of least squares calibration using option premiums and particle filtering of price data to find model parameters is determined. Derivative models using exponential Lévy processes are calibrated using regularized weighted least squares with respect to the minimal entropy martingale measure. Sequential importance resampling is used for the Bayesian inference problem of time series parameter estimation with proposal distribution determined using extended Kalman filter. The algorithms converge to their respective global optima using a highly parallelizable statistical optimization approach using a grid of initial positions. Each of these methods should produce the same parameters. We investigate this assertion.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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