Two-step estimation of the volatility functions in diffusion models with empirical applications

Xu-Guo Ye, Jin-Guan Lin, Yan-Yong Zhao and Hong-Xia Hao

Journal of Empirical Finance, 2015, vol. 33, issue C, 135-159

Abstract: In this article, we develop a two-step estimation procedure for the volatility function in diffusion models. We firstly estimate the volatility series at sampling time points based on high-frequency data. Then, the volatility function estimator can be obtained by using the kernel smoothing method. The resulting estimators are presented based on high-frequency data, and are shown to be consistent and asymptotically normal. We also consider boundary issues and then propose two methods to handle them. The asymptotic normality of two boundary-corrected estimators is established under some suitable conditions. The proposed estimators are illustrated by Monte Carlo simulations and real data.

Keywords: Volatility function; Diffusion models; Nonparametric estimation; Two-step estimation; High-frequency data (search for similar items in EconPapers)
JEL-codes: C01 C14 C15 C22 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:33:y:2015:i:c:p:135-159

DOI: 10.1016/j.jempfin.2015.05.001

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