Statistical Modeling of Opening Price Gaps in the Shanghai Stock Exchange Composite Index Using Linear Methods

Yuancheng Si, Saralees Nadarajah and Zongxin Zhang ()
Additional contact information
Yuancheng Si: Anhui Academy of Social Sciences
Saralees Nadarajah: Fudan University
Zongxin Zhang: University of Manchester

Computational Economics, 2025, vol. 66, issue 4, No 24, 3437-3472

Abstract: Abstract This study explores the determinants of the opening price gap rate (diffrate) in the Chinese stock market using a range of statistical models, including linear models with regularization terms, generalized linear models (GLMs), generalized additive models (GAMs), and Long Short-Term Memory (LSTM) models. Emphasizing predictive accuracy, interpretability, and practical applicability, the findings reveal that GAMs with regularization terms outperform other approaches in forecasting opening price gap rate. The results identify several critical factors, including domestic market indices, global liquidity conditions, and market activity measures. By providing a comprehensive framework for understanding and modeling opening price dynamics, this work lays a robust foundation for future research and practical applications in market risk management and predictive analytics.

Keywords: Opening price gap; Generalized linear models; Generalized additive models; Regularization (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-024-10817-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:kap:compec:v:66:y:2025:i:4:d:10.1007_s10614-024-10817-9

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-024-10817-9

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().