Application of Multivariate Logistic Model in Prospective Identification of Initial Public Offering Risk from the Perspective of Investment Banking

DOI

10.2991/978-2-38476-585-0_57How to use a DOI?

Keywords

IPO risk; Multivariate logistic model; Prospective identification; Investment banking; Science and technology innovation board

Abstract

This paper explores Initial Public Offering (IPO) risk identification from the perspective of investment banking, focusing on the misreporting of R&D expenses among companies listed on the Science and Technology Innovation Board between 2019 and 2024. Firms penalized or rejected due to false Research and Development (R&D) disclosures were selected as the experimental group, while companies successfully listed without disputes served as the control group. A logistic regression model incorporating six core variables—such as project anomaly index and R&D personnel salary dispersion—was constructed. Parameters were estimated using the maximum likelihood method, with Lasso regression applied to refine variable selection and improve model clarity. The analysis shows that project anomaly index and R&D salary dispersion significantly raise the likelihood of misreporting, whereas auditor industry expertise reduces this risk. The model achieves strong predictive performance, with an AUC of 0.89 and an overall accuracy of 85%. The findings support a forward-looking framework for investment banks to assess IPO risks and strengthen audit quality.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xingcheng Kong
PY  - 2026
DA  - 2026/06/18
TI  - Application of Multivariate Logistic Model in Prospective Identification of Initial Public Offering Risk from the Perspective of Investment Banking
BT  - Proceedings of the 2025 International Conference on Hybrid Commerce, Human Capital, and Economic Dynamics (ICHCH 2025)
PB  - Atlantis Press
SP  - 513
EP  - 523
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-2-38476-585-0_57
DO  - 10.2991/978-2-38476-585-0_57
ID  - Kong2026
ER  -