Determinants of IPO underpricing in New York and Hong Kong Is the underpricing an additional incentive for Chinese companies to go public on the New York Stock exchange rather than the Hong Kong Stock Exchange, based on the underpricing in the period from 20052015? Alex Moonen (10191836) Supervisor: Yumei Wang June 2016 In this thesis, the IPO underpricing of the New York Stock Exchange and the Hong Kong Stock exchange are examined in the period from 2005-2015. Institutional differences and restrictions of both exchanges have been disclosed. A sample of 965 New York Stock Exchange and 1529 Hong Kong Stock Exchange IPOs is used for this study. The underpricing in the period from 2005-2015 is 6,70% point higher on the New York Stock Exchange and is tested by the Propensity Score Matching method. The factors influencing the level of underpricing are still consistent with previous literature. The book runner (indicating that the IPO is underwritten by a prestigious underwriter) has a positive effect on underpricing. Also, the high-tech industry effect is positive and significant.
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Determinants of IPO underpricing in New York and Hong Kong
Is the underpricing an additional incentive for Chinese companies to go public on the New York Stock
exchange rather than the Hong Kong Stock Exchange, based on the underpricing in the period from
2005-‐2015?
Alex Moonen (10191836) Supervisor: Yumei Wang
June 2016
In this thesis, the IPO underpricing of the New York Stock Exchange and the Hong Kong Stock
exchange are examined in the period from 2005-2015. Institutional differences and restrictions of both
exchanges have been disclosed. A sample of 965 New York Stock Exchange and 1529 Hong Kong
Stock Exchange IPOs is used for this study. The underpricing in the period from 2005-2015 is 6,70%
point higher on the New York Stock Exchange and is tested by the Propensity Score Matching
method. The factors influencing the level of underpricing are still consistent with previous literature.
The book runner (indicating that the IPO is underwritten by a prestigious underwriter) has a positive
effect on underpricing. Also, the high-tech industry effect is positive and significant.
1
Statement of Originality
This document is written by Alex Moonen who declares to take full responsibility for the contents of
this document. I declare that the text and the work presented in this document is original and that
no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the
3.3.1 Underwriter theory .............................................................................................................. 12
3.3.2 Asymmetric information ...................................................................................................... 13
3.3.3 Symmetric information ........................................................................................................ 14
4. Data & methodology ........................................................................................................................ 15
4.1 Data ............................................................................................................................................ 15
In this study the model including the following variables is used: lag, deal size and three dummy
variables: book-‐runner, high-‐tech and recession. The time between the announcement date and
issue date of the IPO is defined as the lag variable. The IPO value is the total deal size and defined as
total shares times the offer price, this variable is indicated by Ln(Size). If the IPO occurred between
2007 and 2009 (financial recession period) the dummy variable for recession in the United States
takes the value 1 and 0 otherwise. However the recession had its impact since Q4 2008 and
recovered in Q4 2009 in China (Fung, 2014). The dummy variable book-‐runner takes the value 1 if
the book-‐runner is prestigious and 0 otherwise. When the book-‐runners are part of the top six
underwriters in the United States or China the underwriter is indicated as ‘prestigious’. The
distinction is made between high-‐tech and non-‐high-‐tech firms following SIC (Standard Industrial
Classification) codes followed by (Loughran & Ritter, 2002).
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4.2.1 Hypothesis Hypothesis 1:
This hypothesis is related to the research question of this thesis, which is whether the underpricing in New York is lower than the underpricing in Hong Kong. This hypothesis will be tested by the method of ‘Propensity Score Matching’.
H0: β! = 0
H1: β! < 0
Hypothesis 2 and 3 will be tested by running an ordinary least squares (OLS) regression.
Hypothesis 2:
The second hypothesis will test if the IPO of high-‐tech firms will result in a higher level of
underpricing. Loughran & Ritter (2002) argue high-‐tech firms will result in a positive relationship
with underpricing.
H0: β! = 0
H1: β! > 0
Hypothesis 3:
The third hypothesis will test if the IPO underpricing is higher when underwritten by a prestigious
book-‐runner. Beatty & Ritter (1986) and Carter et al. (1986) have shown with empirical research that
book-‐runners with a better reputation decrease underpricing. Dewenter & Field (2010) investigated
IPOs in relation to underwriter reputation in Hong Kong. The investigation revealed that investment
banks avoid issues that could provide high speculation around the issue in order to maintain their
reputation. This tends more towards a positive relationship with underpricing in Hong Kong. The
direction of the relationship is not clear ex-‐ante.
H0: β! = 0
H1: β! ≠ 0
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5. Results The descriptive statistics of the sample are presented in table 1. From the Thomson One database
the offer price, closing price after the first day, deal value (total IPO size) and the book-‐runners are
retrieved. From the Zephyr database the announcement date was retrieved.
Table 1: Descriptive statistics variables Variable Mean Std.Dev Min Max
Within the used sample, prestigious underwriters on the NYSE execute IPOs more often. This can be
deduced from the table because New York is used as the treatment group, and has a coefficient of
1.79. Furthermore, more high-‐tech companies are contained in the sample of New York (indicated
by the high-‐tech coefficient). The total size of IPOs is larger on the NYSE. The variable lag does not
have a significant effect on the probability being in one of the two markets so it looks like there is no
significant difference in lag between the two markets. From the regression results in Table 3, the
conclusion can be made that the underpricing in New York is 6,70 percentage point higher that the
underpricing in Hong Kong. This leads to the result of hypothesis 1:
H0: β! = 0
H1: β! < 0
H0 is rejected, however the alternative hypothesis cannot be accepted since β! is significantly larger than 0. This means there is more underpricing in New York than in the Hong Kong exchange.
To test the second and third hypothesis an OLS regression is done. The total dataset is used.
Hypothesis 2 tests the effect on underpricing of the market sector high-‐tech. The influence of the
book-‐runner on the IPO underpricing is tested with hypothesis 3. The dummy variable market is used
to indicate the exchange, and take the value 1 if the IPO took place in New York and 0 otherwise.
Results are showed in Table 4.
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Table 4: Regression results OLS Variables
10.310***
Market -‐1.240
-‐0.000 Lag (.010)
0.010 LN(size) (.210)
1.520 Bookrunner -‐1.050
11.350*** High-‐tech -‐2.060
-‐1.130 Recession -‐1.430
-‐1.120 Constant (.940) R-‐squared 0.180 N 1201 * significant at 10% level ** significant at 5% level *** significant at 1% level
From the results, the variable high-‐tech is significant and positive. This is consistent with the
expectation stated in hypothesis 2. Therefore hypothesis 2 is consistent with (Loughran & Ritter,
2002). The third hypothesis, the direction of the relationship was not clear ex-‐ante because of
divergent and contradictory literature. As table 4 shows, the variable book-‐runner is positive but not
significant, for this reason a valid assumption cannot be made about the influence of the book-‐
runner. However from the 95% confidence interval [-‐0.62 and 3.53] it tends to be positive.
To see if the book-‐runner has an effect on the excess return, the insignificant variables are deducted
from the model and results are showed in table 5. By leaving the inconsistent variables out, almost
the same results and R-‐squared are obtained. The results show that the variable book-‐runner has no
significant effect on the excess return of IPOs.
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Table 5: Regression results OLS Variables
11.260***
Market
(.900)
11.440*** High-‐tech
(2.050)
-‐1.070*** Constant (.230) R-‐squared
0.1762
N
1201 * significant at 10% level ** significant at 5% level *** significant at 1% level
From the analysis above, the variable LAG is not relevant in the regression. Table 4 shows no
significant effect on excess return. Due to this conclusion the variable LAG can be omitted. As
mentioned before, the variable LAG was limiting our number of observations due to missing
announcement dates.
In the next section the variable LAG is excluded and the same regression is done. The number of
Again, the US market is used as the treatment group. By leaving out the variable lag, it becomes
clear that the difference in excess return is smaller. The difference in the excess return is now 3.29
percentage points. In the new dataset, again in New York prestigious book runners execute more
IPOs. Also more high-‐tech firms are included in the US dataset and the US dataset contains more
IPOs during recession. The total IPO value of IPOs on the NYSE is higher than on the HKSE.
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Table 9: Regression results OLS Variables
8.507***
Market (.875)
-‐0.121 LN(size) (.120)
1.460** Book-‐runner (0.640)
8.730*** High-‐tech -‐1.500
-‐1.520 Recession (0.980)
-‐0.450 Constant (.500) R-‐squared 0.15 N 2177 * significant at 10% level ** significant at 5% level *** significant at 1% level
The variable book-‐runner is positive and significant. This is consistent with literature by Dewenter &
Field (2001). The variable High-‐tech is just as in the first regression positive and significant. This is
consistent with the expectation made in hypothesis 2 and also by the literature written by (Loughran
& Ritter, 2002).
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6. Conclusions This thesis compares the underpricing on the Hong Kong Stock Exchange in relation to the
underpricing on the New York Stock Exchange in the period from 2005-‐2015. The study is done with
a sample of 965 Hong Kong IPOs and 1529 IPOs on the New York Stock Exchange. Several theories
that explain underpricing are; the underwriter theory, asymmetric information theory and the
symmetric information theory and they are discussed in part 3.
The main research question of this paper is: Is the underpricing an additional incentive for Chinese
companies to go public on the New York Stock exchange rather than the Hong Kong Stock Exchange,
based on the underpricing in the period from 2005-‐2015?
In the period from 2005-‐2015, the underpricing found on the New York Stock Exchange was 6,70
percentage point higher than the underpricing in Hong Kong.
This result is consistent with findings by Dreher & Hopp (2013), in their research the underpricing
levels in the US exceeds the underpricing in Hong Kong. But inconsistent with results found by
Banerjee, Dai & Shrestha (2011). Several drivers for the underpricing are found. First, the market
sector high-‐tech showed a positive relationship with underpricing and consistent with hypothesis 2.
When the number of IPOs marked by the high-‐tech industry increases, the IPO underpricing
increases. These companies have more ex ante uncertainty and higher risk, this is because these
firms are valued mainly from growth opportunities. In contrast, determinant LAG is not significant,
contradicting literature by Tian (2003). For this reason this variable is dropped out in the second
regression. By leaving out this limiting variable, the second (positive) relationship with underpricing
was found. This Second relationship with underpricing, consistent with hypothesis 3, was the factor
book-‐runner. This relationship is consistent with the findings by Dewenter & Field (2001).
Summarizing, the IPO underpricing is not an additional incentive for Chinese companies to list on the
New York Stock Exchange rather than the Hong Kong Stock Exchange. However from the literature
we can identify possible explanations for Chinese companies to list on the NYSE instead of the HKSE.
First, the additional requirements for listing in the US by the Sarbanes-‐Oxley act. Besides financial
requirement are stricter on the HKSE than on the NYSE. Another potential advantage for Chinese
companies to list in New York is the international recognition and better global visibility by listing
abroad.
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7. Limitations Unfortunately for the first regressions, a lot of announcement dates were missing. Due to these
missing dates a lot of observations were lost because this information was needed to conduct the
variable lag. In the second regression, a lot more observations were used. By this changing number
of observations, a smaller difference in underpricing between the two exchanges was found. Due to
missing observations, an unrepresentative image of the IPO excess returns can be the result.
The effect of the recession period can give a unrepresentative image of IPO underpricing, first the
time of influence of the recession period is not equal on both stock markets. Second there is a
significant drop in economic activity during periods of recession and IPO activity decreases.
8. Recommendations for future research Despite the large amount of underpricing literature regarding IPO underpricing, there is still room for
future research. Because of changing regulations on the both stock markets, for instance the
implications of the Sarbanes-‐Oxley act in the United States. Deregistration of firms from the NYSE
were seen as a result from the Sarbanes-‐Oxley act. New research can be done on the implications of
this act of listing of Chinese companies on the US stock market.
These issues, related to corporate governance and IPO underpricing are relatively new in the Chinese
stock market. And due the growing economy and its role in the global interconnected economy this
subject become more and more interesting.
Furthermore, an interesting issue may be the ‘one country, two systems’ formula between China
and Hong Kong. What are the future implications of this relationship and China’s socialist economic
system in relationship with Hong Kong?
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