Neural Network for Partially Linear Time Series Models

Xuchen Wei (), Min Chen and Shiqing Ling
Additional contact information
Xuchen Wei: Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong
Min Chen: ��School of Mathematics and Statistics, Shanxi University, Taiyuan, P. R. China‡Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, P. R. China
Shiqing Ling: Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong

Annals of Financial Economics (AFE), 2025, vol. 20, issue 02, 1-36

Abstract: This paper proposes an iterative neural network estimate (INNE) for the partially linear (PL) time series models. It is shown that the parametric coefficients of INNE are n consistent and asymptotically normal, and the convergence rate of nonparametric function is O(n−α), where α is a constant independent of the dimension of the nonparametric part. To obtain the INNE, an initial estimator of the parametric coefficients is proved to be asymptotically normal. Our estimation procedure circumvents “curse of dimensionality†incurred by the traditional nonparametric smoothing approach. A simulation study is carried out to assess the performance of the INNE in the finite samples. It is shown that our INNE outperforms the traditional nonparametric smoothing approach according to several criteria used in this paper. One real example is used to illustrate our approach.

Keywords: Neural network; partially linear model; time series (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S2010495225500149
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:afexxx:v:20:y:2025:i:02:n:s2010495225500149

Ordering information: This journal article can be ordered from

DOI: 10.1142/S2010495225500149

Access Statistics for this article

Annals of Financial Economics (AFE) is currently edited by Michael McAleer

More articles in Annals of Financial Economics (AFE) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().