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Research Article | Open Access

Detecting jumps in stochastic volatility jump-diffusion models via the power variation approach

Zhongyu ChenJuliang Yin( )
School of Economics and Statistics, Guangzhou University, Guangzhou, Guangdong, China
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Abstract

It is well-known that pretesting the presence of the jump component in an underlying price process is crucial for modeling this process. In this paper, we propose a consistent test for jump intensity of the conditional Poisson process in a stochastic volatility jump diffusion model. Theoretically, we derive the infill and long-span asymptotic properties of realized power variation under some suitable conditions, and verify the asymptotic size and power of the proposed test. Furthermore, the finite-sample performance of our proposed test is illustrated through simulation analysis, and an application to real price series provides empirical evidence of significant jump intensities.

CLC number: 62M20, 62P05

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AIMS Mathematics
Pages 19189-19216

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Cite this article:
Chen Z, Yin J. Detecting jumps in stochastic volatility jump-diffusion models via the power variation approach. AIMS Mathematics, 2025, 10(8): 19189-19216. https://doi.org/10.3934/math.2025858

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Received: 06 May 2025
Revised: 16 July 2025
Accepted: 29 July 2025
Published: 15 August 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)