随机波动跳跃扩散模型的重加权纳达拉亚-沃森估计

IF 2.9 2区数学 Q1 MATHEMATICS, APPLIED

Computers & Mathematics with Applications Pub Date : 2024-10-04 DOI:10.1016/j.camwa.2024.09.029

Shaolin Ji, Linlin Zhu

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引用次数: 0

摘要

在本文中，我们构建了随机波动模型波动过程无穷小矩的重加权 Nadaraya-Watson 估计器，并应用了未观测波动过程的阈值估计器。我们的模型包括基础资产价格及其波动过程的跳跃。我们推导了在填充和长跨度假设下估计器的渐近特性。这些结果有助于识别过程。我们通过蒙特卡罗模拟研究了估计器的有限样本性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Reweighted Nadaraya–Watson estimation of stochastic volatility jump-diffusion models

In this paper, we construct the reweighted Nadaraya–Watson estimators of the infinitesimal moments for the volatility process of the stochastic volatility models, with the application of the threshold estimator of the unobserved volatility process. Our model includes jumps in both the underlying asset price and its volatility process. We derive the asymptotic properties of the estimators under the infill and long span assumptions. The results are useful for identification of the process. The finite-sample performance of the estimators is studied through Monte Carlo simulation.

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来源期刊

Computers & Mathematics with Applications 工程技术-计算机：跨学科应用

CiteScore

5.10

自引率

10.30%

发文量

396

审稿时长

9.9 weeks

期刊介绍： Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).