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arXiv 1701.02129math.PRmath.STstat.TH
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振荡布朗运动的统计估计

Statistical estimation of the Oscillating Brownian Motion

Antoine Lejay, Paolo Pigato

摘要:

研究了一类称为振荡布朗运动的随机微分方程中二值不连续扩散系数估计的渐近性态。利用后一个过程与斜布朗运动的关系,我们提出了两个自然相容的估计,这是综合波动率估计的变种,并考虑到占用时间。我们证明了重正化误差估计对某些高斯混合的稳定收敛性,可能通过依赖于当地时间的项进行校正。这些限制源于遍历性的缺乏以及过程在零时的本地时间的行为。我们测试这两个估计的模拟过程中,找到一个完全符合理论预测。

英文摘要:

We study the asymptotic behavior of estimators of a two-valued, discontinuous diffusion coefficient in a Stochastic Differential Equation, called an Oscillating Brownian Motion. Using the relation of the latter process with the Skew Brownian Motion, we propose two natural consistent estimators, which are variants of the integrated volatility estimator and take the occupation times into account. We show the stable convergence of the renormalized errors' estimations toward some Gaussian mixture, possibly corrected by a term that depends on the local time. These limits stem from the lack of ergodicity as well as the behavior of the local time at zero of the process. We test both estimators on simulated processes, finding a complete agreement with the theoretical predictions.

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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