Research on the Impact of Innovation Output on IPO Underpricing
Rate based on Multiple Linear Regression Model
Qiyu Cheng and Sihan Wang
Zhejiang University, International Campus, Wenzhou, China
Keywords: Innovation Capacity Output, Science And Innovation Board, Degree Of IPO Price Suppression, Multiple
Linear Regression Model, Book Value Of Intellectual Property, Invention Patent Intensity.
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.
1 INTRODUCTION
1.1 Background of the Study of the
Problem
Due to the late establishment of the Chinese stock
market, the short development time of the capital
market and the imperfection of the relevant system,
the IPO price suppression in the Chinese A-share
market has been at a high level for a long time, with
the average price suppression rate even exceeding
140%. The severe price suppression makes IPOs
rarely break in the primary market, weakening the
efficiency of market resource allocation. New shares
are generally undervalued in the primary market, a
phenomenon that is particularly evident in the KSE,
increasing the cost of financing for KSEs, weakening
their financing, and reducing the efficiency of
resource allocation in the primary market. At the
same time, it has been a long-standing iron law in the
secondary market that new stocks are undefeated, and
influenced by various factors such as investor
sentiment and information asymmetry, the prices of
new stocks often jump wildly on the first day of
listing in the secondary market, seriously affecting
the fairness and rationality of market pricing.2020 In
June 2020, the STB began to implement the
registration system reform on a trial basis, and the
stock market as a whole evolved in a market-oriented
direction, with the role played by the market in
valuation and pricing is increasing day by day, and
this initiative helps to guide the market towards
rationalization, enhance market activity and the
effectiveness of resource allocation, and guide the
rationalization of the market valuation and pricing
process. This paper aims to explore the impact of
innovation output capacity on the degree of
underpricing of stocks listed on the Sci-Tech
Innovation Board for the first time, and to explore the
relationship between stock valuation pricing and its
intrinsic value after the registration system reform.
Cheng, Q. and Wang, S.
Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model.
DOI: 10.5220/0011177700003440
In Proceedings of the International Conference on Big Data Economy and Digital Management (BDEDM 2022), pages 335-345
ISBN: 978-989-758-593-7
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
335
1.1.1 Changes in IPO Review and Pricing
Brought about by the
Registration-based IPO System
The reform of the registration system of the China
Science and Technology Innovation Board (STIB)
has clarified the issuance and listing review and
registration procedures, shortened the working days
required for registration review by the SFC, and
further optimized the STIB delisting indicators. The
registration system has improved the order of entry
and exit in the capital market, effectively combating
the investment behavior of the market and
emphasizing the focus and screening of the intrinsic
value of companies. This initiative creates a high-
quality capital market and financing environment for
science-based companies under the new normal of
economic environment. At the same time, it hedges
the negative impact of the epidemic on the capital
market, accelerating the recovery of capital market
vitality, as well as boosting the high-quality
development of China's economy.
1.1.2 Innovation Capacity is Becoming an
Increasingly Important Indicator of
the Value of Listed Companies
With the gradual implementation of China's
innovation-driven development strategy, improving
innovation capability and truly realizing value
innovation are important requirements for companies
to achieve differentiation and improve industry
competitiveness. In recent years, enterprises are
interested in the key significance of innovation
activities such as technological output for their long-
term survival and development, and more and more
listed companies are taking the initiative to disclose
data on technological innovation, using R&D
expenditure, patent quantity, intangible assets, etc. as
indicators to measure their innovation capability and
conduct empirical research related to enterprise value
(Lu, 2009). In this paper, we will start from the
innovation output capability of enterprises and
introduce indicators such as relative patent intensity
and intangible assets to explore the correlation
between them and enterprise value, and then explore
the impact on the IPO suppression of enterprises.
1.2 Research Value of the Problem
Compared with the existing literature, the
contribution of this paper as long as the research is as
follows: The research object is science and
innovation companies to explore whether the science
and innovation board is tilted towards companies
with strong innovation capability at the valuation
pricing level. Most scholars in the past have
mostly used R&D inputs to measure the R&D
innovation capability of enterprises mainly, ignoring
the role of the capability of the actual outcome output
in valuation pricing. This paper starts from the
innovation output capability of enterprises and
explains the impact of innovation capability influence
on the IPO suppression of science and technology
innovation enterprises from a new perspective,
making the evaluation system of valuation pricing
more complete.
2 REVIEW OF THE
LITERATURE AND
THEORETICAL
FOUNDATIONS
2.1 Study on IPO Price Suppression
2.1.1 Interpretation of the Concept of IPO
Price Suppression Rate
IPO (initial public offerings) pricing, which is a
reasonable valuation of the intrinsic value of the
proposed listed company, has always occupied an
important position in the financial field (Dong, Liu,
Xu). Since the proposed listed company cannot
predict the market demand for its shares, the issuer
will give its issue price to the investment bank, which
will be responsible for issuing and underwriting the
shares of the proposed company. Due to the
uniqueness of a company's IPO listing event and the
lack of historical trading data for the IPO company's
stock, underwriters usually need to combine different
valuation methods to more accurately predict the
price of a company's IPO stock (Roosenboom, 2007).
Due to the difficulty of IPO pricing, it is usually
necessary to make judgments about the
reasonableness of the pricing. In addition to the
method of valuing and judging reasonableness by
using comparable companies (companies with
financial and industry characteristics similar to those
of the proposed IPO) as a reference, a central measure
of the efficiency of the IPO market is the degree of
IPO price suppression (CHAMBERS, 2009,
DIMSON, 2009). A central measure of the efficiency
of the Initial Public Offering (IPO) market is the
extent to which issues are underpriced.
The IPO price suppression phenomenon, which
refers to the pricing of initial public offerings of listed
BDEDM 2022 - The International Conference on Big Data Economy and Digital Management
336
companies below the market price on the first day of
listing (Li, 2020, Li, 2020), is widespread in stock
markets around the world, and the degree of IPO
price suppression in China's main board market is
particularly significant (Gao, 2020). China's
securities market has experienced a high degree of
IPO depression in the A-share market for a long time
since the establishment of a unified stock issuance
system in 1993. In China, although the high IPO price
suppression has promoted the rapid development of
the capital market in the early years, the long-term
high price suppression has affected the efficiency of
resource allocation in the primary market for stock
issuance. Also, the high IPO price suppression has
affected the normal financing function of the
secondary market. With a long period of high IPO
price suppression, IPO subscribers can often obtain
risk-free excess returns in the primary market, while
small and medium-sized investors in the secondary
market can often only buy new shares at high levels.
This obviously unbalanced risks and returns of
investors in the primary and secondary markets have
resulted in a large number of secondary market
investors transferring funds to the primary market to
wait for new shares to be purchased. Seriously, the
secondary market financing function is low.
2.1.2 Causes and Mechanisms of Action of
IPO Price Suppression
The phenomenon of IPO price suppression in IPO
pricing was first identified by Hatfield and Reilly in
their study that investors in IPOs tend to enjoy higher
short- and long-term return returns than the general
market (Reilly, 1969, Hatfield, 1969). There has been
foreign literature on IPOs, mainly based on the
premise that secondary markets are efficient and
based on the theory of information asymmetry to
explain the phenomenon of IPO price suppression.
Among them, Rock proposed the winner's curse
hypothesis in 1986, explaining IPO price suppression
as compensation by stock issuers to informationally
disadvantaged investors in order to induce them to
join the market to buy shares (Rock, 1986) (Allen,
1989, Faulhaber, 1989) (Levis, 1993). Baron
proposed the investment bank buyer monopoly
hypothesis in 1982. As issuers and underwriters face
the risk of disclosing negative information during the
subscription period, underwriters routinely resort to
discounted offering strategies to reduce the risk of
breakage (Baron, 1982, Myerson, 1982). In addition,
the information transmission theory suggests that in
the IPO market, potential investors lack knowledge
of the true value of a listed company, and the
company entrusts a reputable underwriter to send
signals of lower risk and make investors believe that
they can gain excess returns by purchasing the
company's new shares through IPO price suppression
(Li, 2020, Li, 2020).
Some domestic scholars study the impact of
institutional reform on IPO price suppression from
the perspective of the IPO system. The IPO issuance
system in China's capital market has gone through
three stages: the audit system, the approval system
and the registration system. Due to the late start and
immature development of China's capital market, the
marketization of IPO pricing is low. Before the
reform of the registration system for IPO issuance of
A shares, the administrative intervention in IPO
issuance was more obvious, and the IPO issuance of
enterprises received heavy restrictions. The number
of enterprises that could go public was very limited
and the listing cycle was long, causing the platform
of listed enterprises to become a scarce resource (Li,
2020, Li, 2020). Companies and underwriters often
need to drive down the stock issue price to ensure a
smooth IPO. This makes the IPO pricing deviate from
the actual intrinsic value of firms to a high degree and
weakens the pricing efficiency of IPOs. Under the
long-term IPO price suppression and inflexible stock
supply, IPOs receive frenzied pursuit from investors,
a strong speculative atmosphere in the secondary
market, often blind speculation on IPO prices,
irrational investors follow the trend to buy shares, and
the price of IPOs in the secondary market is further
inflated, further leading to a high degree of IPO price
suppression in the A-share market.
2.2 A Study on the Impact of Firm
Innovation Capability on IPO Price
Suppression
The causes of the extent of IPO price suppression are
now widely discussed by scholars both at home and
abroad. On the one hand, underwriters tend to depress
IPO prices in order to compensate for the costs
required to obtain additional information about the
firm Dong, Liu, Xu) (Benveniste, 1989, Spindt,
1989). Among other things, the more shares
institutional investors receive, the more the IPO
pricing deviates from the firm's internal value and the
less efficient the pricing is Dong, Liu, Xu).
In terms of investor concern, current research
identifies underpricing due to irrational behavior of
small and medium-sized investors as the main reason
why the first day price of IPOs is much higher than
the issue price (Zou, 2020, Cheng, 2020, Chen, 2020,
Ginger, 2020). There is room for arbitrage in the
Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model
337
primary and secondary markets under the current
system, and investor sentiment and speculative
psychology lead to serious overvaluation of IPO
stock prices after listing (Song, 2019, Tang, 2019).
Chi Jing and Padgett find through their study that the
first-day increase of IPO stock limits the signal of the
firm's true value to outside investors, and government
control over IPO issuance exacerbates the extent of
IPO price suppression (Chi, 2005, Padgett, 2005).
On the institutional side, by comparing the IPO of
technology companies listed on the STB and the main
board A-shares in the past year, Takatada verifies
through an empirical study that the key factor of IPO
price suppression of Chinese companies is the change
of the IPO system, and that the reform of the
registration system of stock issuance on the STB is
conducive to the role of the market in pricing and
resource allocation in IPO.
In terms of R&D intensity, at this stage, scholars
at home and abroad have conducted more studies on
the impact of R&D investment on IPO pricing, but
have not yet reached a unified conclusion. From the
perspective of IPO companies, companies with high
R&D intensity and strong technical strength hope to
signal the company's strong R&D capability and gain
investors' recognition through high-quality R&D
investment disclosure, which leads to higher stock
issue pricing and a lower degree of IPO price
suppression (Qiu, 2013, Peng, 2013, Yao, 2013).
Some scholars also argue that large R&D investment
exacerbates cash flow constraints and fails to deliver
current earnings, exposing firms to a situation of high
risk and uncertainty of earnings profile. As a result,
underwriters tend to be associated with undervaluing
firms in order to hedge risk and the degree of IPO
depression rises (Schankerman, 1985, Pakes, 1985)
(Han, 2001, Chuang, 2001).
Most of the existing domestic and international
empirical studies exploring the pricing efficiency of
IPOs on China's A-share STB have focused on the
impact of R&D investment on the causes of IPO price
suppression. The influence factor of innovation
capacity output (IPR output/IPR owned) of STB IPO
firms has been less explored.
A company's intellectual property rights contain
patents, trademarks, copyrights, trade secrets, etc.
Patents, as an important part of a company's
intellectual property, are often discussed more by
domestic and foreign scholars as one of the main
R&D information disclosed by listed companies. It is
widely believed at home and abroad that the core
asset of patented technology owned by a company
can influence the value of the company and its market
value after IPO. The relationship between patent
output and company value has been widely discussed
and verified in mature capital markets in Europe and
the U.S (Li, 2012, Hong, 2012, Wu, 2012). Griliches
first found the positive impact of the growth in the
number of patents on the growth of company market
capitalization and argued that this impact is
particularly significant for smaller companies
(Griliches, 1990). Subsequently, many foreign
scholars have verified the positive relationship
between patent ownership and firm value in their
studies of listed companies in different industries in
European and American capital markets, especially
high-tech listed companies (Hall 2001, Jaffe 2001,
Trajtenberg 2001). Similar findings have been
obtained from relevant studies conducted by our
scholars. By analyzing data on total intangible assets
of listed companies from 1999-2003, it was found
that the market recognizes companies' investment in
intangible assets, among which the value of
technological intangible assets is mainly reflected in
high-tech industries (Shao, 2006, Fang, 2006).
Fabrizi S. at al. further found through a series of
studies that patented technologies developed by
companies can convey to external investors On this
basis, Li Xiaoxia et al. explored the influence of
patent quantity and patent quality on the market
performance of listed companies after IPO, and
concluded that there is a positive relationship
between the number of patents and IPO market
performance of companies, among which, the
contribution of invention patents is particularly
significant (Li, 2019, Luo, 2019, Wang, 2019). Some
other scholars explain the impact of patent
technology on a company's financing ability and
value from the perspective of the company's future
cash flow and operational risk, thus providing some
thoughts on the IPO price suppression phenomenon.
Patents can affect a company's future cash flow by
affecting its operating performance and thus its future
cash flow (Zheng, 2012, Song, 2012). Li et al. argue
that technology brings more stable income, which can
reduce the uncertainty of the company's future
business situation and thus reduce the company's
business risk. Patents can signal to the market that the
company has good R&D capability and
comprehensive value, and reduce the risk of
financing failure (Li, 2019, Luo, 2019, Wang, 2019).
BDEDM 2022 - The International Conference on Big Data Economy and Digital Management
338
3 INTRODUCTION OF THE
RESEARCH CONCEPT AND
HYPOTHESIS FORMULATION
3.1 Introduction of the Research
Concepts in This Paper
This paper mainly adopts literature research method
and empirical research method to investigate the
impact of a company's innovation output capacity on
its IPO depression rate by taking innovative
companies listed on the KCI board as the object of
study, using IPO underpricing rate as the explanatory
variable, using IPR book value and invention patent
intensity as the explanatory variables, and setting
other control variables according to the existing
literature.
3.2 Formulation of the Research
Hypothesis in This Paper
Based on the above analysis, two hypotheses are
proposed in this paper.
H1: The higher the share of a company's
intellectual property in intangible assets, the stronger
the company's innovation potential and innovation
output capacity, the more the secondary market
recognizes the value of the company and has
confidence in its profitability, and the more severe the
price suppression. In other words, there is a
significant positive relationship between a company's
innovation output capacity and the degree of IPO
price suppression.
H2: The higher the number of invention patents
owned by a firm at a certain size, the higher the
proportion of technologies that can really create value
for economic growth, the more confidence secondary
market investors have in the firm's innovation
capability and the easier it is to overestimate the real
value of the firm's stock. There is a significant
positive relationship between the intensity of a
company's invention patents and the degree of IPO
price suppression.
4 MODEL CONSTRUCTION AND
EMPIRICAL STUDY
4.1 Study Sample and Data Sources
In this paper, the initial sample of China A-share KSC
IPO companies from 2019/7/22-2021/2/10 is used
and screened: special marker companies (sample of
companies with unprofitability, voting rights
difference, and red-chip structure) are excluded, and
a final sample of 212 KSC companies is obtained.
The data of financial indicators such as total assets,
gearing ratio, return on net assets, and years of
establishment for the sample of companies in this
paper are obtained from the WIND database.
4.2 Definition of Model Variables
4.2.1 Explained Variables
The explanatory variable is the IPO Underpricing
Rate
(IUR) of the firm. In the robustness test, the
Adjusted Initial Public Offering Underpricing rate
(AIUR) is used as the moderating explanatory
variable in this paper.
4.2.2 Explanatory Variables
The explanatory variables are Book Value of
Intellectual
Property (IPBV) and Intensity of Patent of
Invention (PI). The two are used as indicators of the
level of innovation capacity output of science and
innovation companies.
4.2.3 Control Variables
Control variable is the logarithm value of a
company’s
Total Assets (InTA), Debt to Asset ratio (LEV),
Return on Equity (ROE), Years of Establishment
(Years), The First Big Proportion of Shareholding
(TOPI), Industry Price Earnings ratio (IPE), First-day
Turnover rate (FTR), Online Demand-to-Offer ratio
(OTR), and the number of Shares sold in the online
offering. demand-to-offer ratio (OISR), Issuance
Cost (IC), and Earnings per Share (EPS).
4.3 Construction of the Model
To test the hypothesis, the following model (1) and
model (2) are developed in this paper, respectively.
𝐼𝑈𝑅 = 𝛽
+𝛽
𝐼𝐵𝑃𝑉 + 𝛽
𝑙𝑛𝑇𝐴 + 𝛽
𝐿𝐸𝑉 +
𝛽
𝑅𝑂𝐸 + 𝛽
𝑇𝑂𝑃𝐼 + 𝛽
𝐼𝑃𝐸 + 𝛽
𝐹𝑇𝑅 + 𝛽
𝑂𝐼𝑆𝑅 +
𝛽
𝐼𝐶 + 𝛽

𝐸𝑃𝑆 + 𝛽

𝑌𝑒𝑎𝑟𝑠 (1)
𝐼𝑈𝑅 = 𝛽
+𝛽
𝑃𝐼 + 𝛽
𝑙𝑛𝑇𝐴 + 𝛽
𝐿𝐸𝑉 +
𝛽
𝑅𝑂𝐸 + 𝛽
𝑇𝑂𝑃𝐼 + 𝛽
𝐼𝑃𝐸 + 𝛽
𝐹𝑇𝑅 + 𝛽
𝑂𝐼𝑆𝑅 +
𝛽
𝐼𝐶 + 𝛽

𝐸𝑃𝑆 + 𝛽

𝑌𝑒𝑎𝑟𝑠
(2)
Among them, the explanatory variables of model
(1) are the book value of intellectual property (IBPV)
and the explanatory variable of model (2) is the
Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model
339
intensity of intellectual property (PI). Referring to the
study of Jianghong Zeng and Xiaoxia Li et al. the IPO
underpricing rate is also affected by total assets
(lnTA), gearing ratio (LEV), return on net assets
(ROE), years of establishment (Years), percentage of
shares held by the largest shareholder (TOPI), price-
to-earnings ratio of the industry to which it belongs
(IPE), First-day turnover ratio (FTR), Online
Offering Winning rate (OISR), IPO offering expense
ratio (IC), and earnings per share (EPS). In addition,
the model controls for the company's duration of
establishment (Years), which is calculated by
calculating the number of days between the
company's establishment date and listing date divided
by 365 days, rounded to single digits, and the result
is recorded as the company's duration of
establishment (Years). The specific variables are
defined in Table 1.
Table 1.
Variable definition table
Variable
Type
Variable
Name
Variable
symbol
Variable
definition
Explaine
d
variables
IPO
Underprici
ng Rate
IUR
Moderat
ed
explanat
ory
variables
Adjusted
IPO
Underprici
ng Rate
AIUR
Explanat
ory
variables
Book
Value of
Intellectual
Property
IPBV
(Intangible assets -
land use
rights)/intangible
assets*100
Intensity of
Patent
PI
Total number of
patents
invented/intangible
assets
Control
variables
Total
assets
lnTA
The total assets of
the firm as of the
day before the
sample cut-off date
are taken as the
natural logarithm
Debt to
Asset ratio
LEV
Gearing of the
company as of the
day before the
sample cut-off date
Return on
Equity
ROE
Net return on
equity of the
company on the
day before the
sample cut-off date
The First
Big
Proportion
of
Shareholdi
ng
TOPI
The percentage of
shares held by the
company's largest
shareholder on the
day before the
sample cut-off date
Industry
Price
Earning
Ratio
IPE
P/E ratio of the
company's industry
on the day before
the sample cut-off
date
First-day
Turnover
Rate
FTR
First-day turnover
rate of the
company's initial
listing
Online
Issue
Winning
Rate
(Online
demand-
to-offer
ratio)
OISR
The winning
percentage of the
online offering of
the company's
initial listing
Issuance
Cost
IC
Issue expense ratio
for the company's
initial public
offering
Earnings
per Share
EPS
Earnings per share
for the company's
initial public
offering
Number of
years of
establishm
ent
Years
Logarithm value of
Number of years of
incorporation at the
time of the IPO
4.4 Descriptive Statistics
To preliminarily analyze the relationship between the
book value of IPRs, the intensity of invention patents
and the degree of IPO depression for companies listed
on the KSE since 2019, this paper presents
descriptive statistics on the variables of the sample.
Table 2 shows the results of descriptive statistics
for all variables. The statistics of IPO price
suppression level (IUR, AIUR) show that the high
price suppression phenomenon is serious in China's
science and technology board, with the average price
BDEDM 2022 - The International Conference on Big Data Economy and Digital Management
340
suppression rate as high as 156.26%, and the degree
of price suppression on the first day of listing varies
greatly among different companies in the science and
technology board, with a standard deviation as high
as 124.90.The maximum value of intellectual
property book value (IPBV) is 100.00% and the mean
value is 37.13% with a standard deviation as high as
40.56. The ownership of IPBV of KCI companies in
the sample pool is generally high, but the results from
the cross-sectional comparison show that the
ownership varies greatly from company to company.
The maximum value of Invention Patent Intensity
(PI) is 8.61, the minimum value is 0.00, and the
standard deviation is 0.61. The ability of companies
per unit size in the sample pool to produce invention
patents does not vary much.
Table 2.
Descriptive statistics of variables
Vari
able
s
Number
of
samples
ave
rag
e
val
ue
(statistics)
standard
deviation
minimu
m value
maximu
m value
IUR 212
156
.26
124.90 -2.15 923.91
AIU
R
212
156
.09
124.36 -1.9 908.1
IPB
V
212
37.
13
40.56 0.00 100.00
PI 212
0.0
9
0.61 0.00 8.61
lnT
A
212
3.0
2
0.04 2.93 3.22
LEV 212
32.
99
16.73 83.84 83.84
RO
E
212
13.
28
13.74 -13.70 124.35
TOP
I
212
30.
77
13.86 9.35 81.88
IPE 212
41.
40
15.31 12.97 131.69
FTR 212
74.
53
5.65 57.57 98.96
OIS
R
212
4.0
8
1.57 2.72 22.54
IC 212
9.8
6
3.40 1.67 34.89
EPS 212
0.9
8
1.15 0.00 15.13
Year
s
212
14.
61
4.93 5.00 32.00
4.5 Correlation Analysis
First, this paper analyzes the correlation coefficients
of the explanatory variables, explanatory variables,
and control variables, and Table 3 shows the
correlation matrix encompassing all variables, and
Fig. 1 shows the correlation scatter plots of all
variables. As shown in Table 3, there is a positive
relationship between both IPR book value and
invention patent intensity and IPO price suppression
rate, sign this paper expects.
Table 3: Correlation matrix of variables.
.
Figure 1: Scatter plot of variable correlations.
Names of Variables IUR AIUR IPBV PI lnTA LEV EPS TOPI ROE IC OISR FTR IPE Years
IUR
1 0.999678359 0.093840934 0.114497913 -0.000676464 -0.070021416 -0.169244766 -0.084720052 0.098840555 0.28008789 -0.011714264 0.323672413 0.049335921 0.006696566
AIUR 0.999678359 1 0.093749693 0.116784662 0.000189331 -0.070372874 -0.172612836 -0.085129737 0.101083929 0.28101959 -0.009547488 0.324269707 0.04878373 0.006625652
IPBV 0.093840934 0.093749693 1 0.169573466 -0.141595019 -0.194365617 0.101946362 -0.126692632 -0.083165356 -0.064524001 0.019661625 -0.001071604 0.275435748 -0.147996434
PI 0.114497913 0.116784662 0.169573466 1 -0.072490426 -0.096253892 -0.011129475 -0.002760072 -0.007234123 -0.003622992 -0.044575152 -0.004576718 0.146752875 0.035270101
lnTA -0.000676464 0.000189331 -0.141595019 -0.072490426 1 0.461292227 -0.045142354 0.104621933 -0.081572606 -0.367298739 0.501849641 -0.186094999 -0.174952777 0.004067442
LEV
-0.070021416 -0.070372874 -0.194365617 -0.096253892 0.461292227 1 -0.060762256 0.030269679 -0.009169496 -0.002936206 0.092745503 -0.100470881 -0.1187251 0.027862398
EPS -0.169244766 -0.172612836 0.101946362 -0.011129475 -0.045142354 -0.060762256 1 -0.001354362 0.100987781 -0.244857231 -0.108447175 -0.130830282 -0.044763145 -0.12318908
TOP I
-0.084720052 -0.085129737 -0.126692632 -0.002760072 0.104621933 0.030269679 -0.001354362 1 0.094023322 0.0360487 0.142421646 -0.100391624 -0.086533193 0.112199987
ROE 0.098840555 0.101083929 -0.083165356 -0.007234123 -0.081572606 -0.009169496 0.100987781 0.094023322 1 -0.027090386 -0.111236175 -0.09490774 0.019091321 0.011057491
IC
0.28008789 0.28101959 -0.064524001 -0.003622992 -0.367298739 -0.002936206 -0.244857231 0.0360487 -0.027090386 1 -0.254894591 0.323964966 0.046566388 0.135881387
OISR -0.011714264 -0.009547488 0.019661625 -0.044575152 0.501849641 0.092745503 -0.108447175 0.142421646 -0.111236175 -0.254894591 1 0.033516719 -0.161156709 -0.124907702
FTR 0.323672413 0.324269707 -0.001071604 -0.004576718 -0.186094999 -0.100470881 -0.130830282 -0.100391624 -0.09490774 0.323964966 0.033516719 1 0.035717084 -0.112488673
IPE 0.049335921 0.04878373 0.275435748 0.146752875 -0.174952777 -0.1187251 -0.044763145 -0.086533193 0.019091321 0.046566388 -0.161156709 0.035717084 1 -0.033740989
Years 0.006696566 0.006625652 -0.147996434 0.035270101 0.004067442 0.027862398 -0.12318908 0.112199987 0.011057491 0.135881387 -0.124907702 -0.112488673 -0.033740989 1
Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model
341
Secondly, this paper also performs variance
inflation factor tests on the variables to exclude
multicollinearity, and Tables 4 and 5 use the book
value of intellectual property and patent intensity of
invention as explanatory variables, respectively.
Observing the test results, the VIF values of all
factors are low and stable, and no large values or
significant outliers are found. Therefore, the
multicollinearity is negligible and there are no factors
that need to be excluded.
Table 4.
VIF test (Explanatory Variable 1 IPBV)
IPBV 1.190295224
lnTA 1.995935436
LEV 1.386475373
EPS 1.14023079
TOPI 1.084941262
ROE 1.055505566
IC 1.494960568
OISR 1.500969826
FTR 1.217930872
IPE 1.135804759
Years 1.106044695
Table 5.
VIF Test (Explanatory Variable 2 PI)
PI 1.031047698
lnTA 1.979954064
LEV 1.375743561
EPS 1.128830362
TOPI 1.074703973
ROE 1.045573152
IC 1.494749516
OISR 1.483353476
FTR 1.215232249
IPE 1.074787317
Years 1.09509684
4.6 Multiple Regression Analysis
Table 6 shows the regression results of IPBV and IPO
price suppression of science and innovation firms. the
coefficient of IPBV is positive, which is consistent
with H1, i.e., higher IPBV increases the likelihood of
IPO price suppression of firms. The regression results
in Table 6 show that IPBV has a significant positive
effect on IPO price suppression of innovative firms,
which is in line with the conjecture of H1. The
regression result has a statistic of 5.439 and a p-value
of 1.48e-7, the overall regression is more significant
and the explanatory variable book value of IPR has
some degree of explanation on IPO price suppression
rate.
Table 6.
Regression results of the effect of IPBV on IUR
Variable
s
Estimat
e
Std.
Error
t
value
Pr(>|t|
)
(Intercep
t)
-
1145.73
283.06 -4.05 0.00
**
*
IPBV 0.41
*
0.21
*
1.98
*
0.05
*
*
lnTA 38.58 12.13 3.18 0.00 **
LEV -1.01 0.54 -1.85 0.07
EPS -10.66 7.18 -1.49 0.14
TOPI -0.77 0.58 -1.33 0.19
ROE 1.62 0.58 2.81 0.01 **
IC 9.97 2.76 3.61 0.00
**
*
OISR -4.67 6.11 -0.76 0.45
FTR 6.11 1.51 4.05 0.00
**
*
IPE -0.11 0.54 -0.20 0.84
Years 3.31 23.27 0.14 0.89
Signif. codes: 0‘***’0.001‘**’0.01‘*’0.05‘.’0.1‘ ’1
Multiple R-squared0.2312 Adjusted R-squared: 0.1887
F-statistic: 5.439 on 11 and 199 DF, p value: 1.48e-07
Table 7 shows the regression results of invention
patent intensity on IPO price suppression for COST
companies. The positive coefficient of PI supports the
positive correlation expected by H2, i.e., higher
invention patent intensity exacerbates the degree of
IPO price suppression for COST companies. From
the regression results in Table 7, it can be seen that
invention patent intensity has a less significant
positive effect on IPO depression of innovative
companies. With a statistic of 4.986 and a p-value of
7.682e-7, the overall regression is more significant,
but the explanatory variable invention patent
intensity has a lower degree of explanation for the
IPO price suppression rate.
Table 7.
Regression results of the effect of PI on IUR
Variable
s
Estimat
e
Std.
Error
t
value
Pr(>|t|
)
(Interce
pt)
-
1068.80
283.
77
-
3.77
0.
00
*
**
PI
3.25 53.84 0.06 0.95
lnTA
36.38 12.32 2.95 0.00
**
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342
LEV
-1.12 0.55 -2.04 0.04
*
EPS
-9.25 7.21 -1.28 0.20
TOPI
-0.88 0.58 -1.51 0.13
ROE
1.51 0.58 2.60 0.01
**
IC
9.81 2.79 3.51 0.00
***
OISR
-3.31 6.14 -0.54 0.59
FTR
5.95 1.52 3.90 0.00
***
IPE
0.16 0.53 0.31 0.76
Years
-1.59 23.52 -0.07 0.95
Signif. codes: 0‘***’0.001‘**’0.01‘*’0.05‘.’0.1‘ ’1
Multiple R-squared0.216 Adjusted R-squared: 0.1727
F-statistic: 4.986 on 11 and 199 DF, p value: 7.682e-07
4.7 Robustness Tests
To make the empirical results more reliable, this
paper uses the adjusted IPO underpricing rate
(AIUR), replacing the IPO underpricing rate (IUR) as
the explanatory variable, to conduct the robustness
test of this regression model. The regression results
in Tables 8 and 9 remain largely consistent with those
in Tables 6 and 7, and the empirical results are more
robust. According to the regression results shown in
Tables 8 and 9, the coefficients of the book value of
intellectual property and the intensity of invention
patents are both positive, and both have a positive
effect on the degree of IPO depression of innovative
companies. Among them, the former's has a
significant positive effect on the IPO price
suppression rate of KIC companies. The overall
regression of the model is more significant, but the
explanatory variables are not well explained.
Table 8.
Robust regression results on the effect of IPBV on AIUR
Variable
s
Estimat
e
Std.
Error
t
value
Pr(>|t|
)
(Intercep
t)
-
1142.65
281.21 -4.06 0 **
*
IPBV
0.41 0.21 1.99 0.05
*
lnTA
38.53 12.05 3.2 0
**
LEV
-1.01 0.54 -1.87 0.06
EPS
-10.96 7.13 -1.54 0.13
TOPI
-0.78 0.58 -1.35 0.18
ROE
1.64 0.57 2.86 0
**
IC
9.97 2.74 3.63 0 **
*
OISR
-4.48 6.07 -0.74 0.46
FTR
6.08 1.5 4.06 0 **
*
IPE
-0.11 0.53 -0.21 0.83
Years
3.19 23.12 0.14 0.89
Signif. codes: 0‘***’0.001‘**’0.01‘*’0.05‘.’0.1‘ ’1
Multiple R-squared0.234 Adjusted R-squared: 0.1917
F-statistic: 5.527 on 11 and 199 DF, p value: 1.078e-07
Table 9.
Robust Regression Results on the Effect of Invention
Patent Intensity on IPO Price Suppression Rate
Variables
Estima
te
Std.
Error
t
value
Pr(>|t|)
(Intercept)
-
1065.9
6
281.94 -3.78 0.00 *
*
*
PI
3.36 53.49 0.06 0.95
lnTA
36.33 12.24 2.97 0.00 *
*
LEV
-1.12 0.54 -2.06 0.04
*
EPS
-9.56 7.17 -1.33 0.18
TOPI
-0.89 0.58 -1.53 0.13
ROE
1.53 0.58 2.66 0.01 *
*
IC
9.81 2.77 3.54 0.00 *
*
*
OISR
-3.12 6.10 -0.51 0.61
FTR
5.92 1.51 3.91 0.00 *
*
*
IPE
0.15 0.53 0.29 0.77
Years
-1.70 23.37 -0.07 0.94
Signif. codes: 0‘***’0.001‘**’0.01‘*’0.05‘.’0.1‘ ’1
Multiple R-squared0.2188 Adjusted R-squared: 0.1756
F-statistic: 5.068 on 11 and 199 DF, p value: 5.697e-07
5 CONCLUSIONS AND
RECOMMENDATIONS OF THE
STUDY
5.1 Conclusion
IPO price suppression in China receives multiple
factors, and the price that exists between the IPO
issue price and the first-day closing price of the IPO
is simultaneously undervalued by the primary market
and overvalued by the secondary market. The actual
innovation capability of a company is increasingly
valued in IPO valuation pricing, and this paper
explores the impact of innovation output capability of
Research on the Impact of Innovation Output on IPO Underpricing Rate based on Multiple Linear Regression Model
343
science and technology companies on IPO valuation
pricing by using a sample of IPO listed companies in
China's A-share science and technology board from
2019/7/22-2021/2/10. It is found that both the book
value of intellectual property and the intensity of
invention patents have positive effects on the degree
of IPO price suppression of innovative firms, with the
positive correlation of the book value of intellectual
property being more significant. It is concluded that
the higher the book value of intellectual property
rights or the higher the intensity of invention patents,
the stronger the innovative output capability of the
STB companies, the higher the confidence of
secondary market investors in the competitiveness
and sustainable profitability of the listed companies,
the recognition of the innovative R&D capability and
the actual value of the companies, and the higher the
cumulative excess return after the first IPO of the
companies, the more severe the IPO price
suppression.
5.2 Relevant Recommendations based
on the Findings of the Study
Based on the findings of this paper, the following
recommendations are made.
a) From the perspective of science and technology
companies, while continuously improving their
actual innovation capabilities, science and
technology companies should stand more from the
perspective of investors, and reasonably increase the
quality of information disclosure while ensuring that
key technology secrets are protected, so that the value
and competitiveness of the company is fully
recognized by investors, weakening the pricing bias
caused by information asymmetry in valuation
pricing, and making the company's R&D value
correctly reflected in IPO pricing The company's
R&D value is correctly reflected in the IPO pricing.
b) At the institutional level, the rules and
regulations governing information disclosure by
listed enterprises need to be further improved. It is
recommended to improve the relevant institutional
acts regulating the review of the assessment of
innovation capability of science and innovation
enterprises and the first-day excess return rate of
IPOs, so as to effectively promote the reasonable and
correct reflection of the actual innovation capability
of enterprises in the valuation and pricing process
from an institutional perspective. At the same time,
by limiting the cumulative excess return rate and
related incentives and penalties, the speculation of
stock prices by investment institutions and blind
follow-through investment by investors should be
combated.
c) At the regulatory level, it is recommended that
the relevant authorities should strengthen the
supervision of the rationality of the behavior of
secondary market investors in assessing the
innovation capability of science and innovation
enterprises, help investors to correctly understand the
actual value of enterprises, supervise the orderly
communication of information between enterprises
and the capital market, and build a bridge of
communication between enterprises, investment and
the capital market.
d) From the perspective of education and
publicity, education and guidance for individual
investors in the secondary market should be
strengthened, investors should be guided to
participate in market activities in an orderly manner,
and the threshold for investors to enter the securities
market should be raised moderately. Education and
dissemination of relevant knowledge to investors
should be enhanced to raise the risk awareness of
stockholders and reduce the emergence of speculative
behavior such as blind investment in a flurry of
activity and price hugging.
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