Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model

Qiyu Cheng, Sihan Wang

2022

Abstract

In the context of the reform of the registration system of China’s science and technology innovation board, this paper empirically investigates the impact of a company’s innovation output capability on the degree of its IPO depression, using 212 companies listed on the science and technology innovation board since 2019 as a research sample. In this paper, the company’s intellectual property book value and invention patent intensity are used as indicators of the company’s innovation output capability. This paper establishes a multiple linear regression model that affects the company’s IPO underpricing rate, and explore the impact of the company’s innovation output capacity on the degree of IPO underpricing. The results find that both the book value of intellectual property and the intensity of invention patents have a positive effect on the degree of IPO depression of the company, among which the former has a more significant effect. It is suggested to improve the assessment process of the actual innovation capacity of science and technology companies. Also, it can be urgent for relevant departments and organizations to guide secondary market investors to correctly understand the value of enterprises, as well as to participate in investment and pricing activities in an orderly manner.

Paper Citation

in Harvard Style

Cheng Q. and Wang S. (2022). Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model. In Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM, ISBN 978-989-758-593-7, pages 335-345. DOI: 10.5220/0011177700003440

in Bibtex Style

@conference{bdedm22,
author={Qiyu Cheng and Sihan Wang},
title={Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model},
booktitle={Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,},
year={2022},
pages={335-345},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011177700003440},
isbn={978-989-758-593-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,
TI - Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model
SN - 978-989-758-593-7
AU - Cheng Q.
AU - Wang S.
PY - 2022
SP - 335
EP - 345
DO - 10.5220/0011177700003440