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Nonparametric estimation of jump diffusion models

机译:跳转扩散模型的非参数估计

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摘要

This paper develops the asymptotics for nonparametric kernel estimators of local time, drift and volatilities, and Levy measure in jump diffusion models. Our asymptotics are developed in a very general set-up, allowing the sample span to increase as the sampling interval decreases, and without assuming stationarity. For drift and volatilities, we analyze both local constant and local linear estimators. We consider not only estimators for instantaneous conditional second moment, but also threshold estimators to disentangle diffusive and jump volatilities. The optimal bandwidths are provided for all these estimators. (C) 2020 Elsevier B.V. All rights reserved.
机译:本文发展了跳扩散模型中局部时间、漂移和波动性以及Levy测度的非参数核估计的渐近性。我们的渐近性是在一个非常普遍的设置中发展起来的,允许样本跨度随着采样间隔的减小而增加,并且不假设平稳性。对于漂移和波动,我们分析了局部常数和局部线性估计。我们不仅考虑了瞬时条件二阶矩的估计量,还考虑了估计扩散和跳跃波动的阈值估计。为所有这些估计器提供了最佳带宽。(C) 2020爱思唯尔B.V.版权所有。

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