short selling and price pressure around acquisition
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SHORT SELLING AND PRICE PRESSURE AROUND
ACQUISITION ANNOUNCEMENT:
EVIDENCE FROM THAILAND
BY
MISS PENSIRI THEPCHOOM
AN INDEPENDENT STUDY SUBMITTED IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR
THE DEGREE OF MASTER OF SCIENCE
PROGRAM IN FINANCE (INTERNATIONAL PROGRAM)
FACULTY OF COMMERCE AND ACCOUNTANCY
THAMMASAT UNIVERSITY
ACADEMIC YEAR 2017
COPYRIGHT OF THAMMASAT UNIVERSITY
Ref. code: 25605902042190NPJ
SHORT SELLING AND PRICE PRESSURE AROUND
ACQUISITION ANNOUNCEMENT:
EVIDENCE FROM THAILAND
BY
MISS PENSIRI THEPCHOOM
AN INDEPENDENT STUDY SUBMITTED IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR
THE DEGREE OF MASTER OF SCIENCE
PROGRAM IN FINANCE (INTERNATIONAL PROGRAM)
FACULTY OF COMMERCE AND ACCOUNTANCY
THAMMASAT UNIVERSITY
ACADEMIC YEAR 2017
COPYRIGHT OF THAMMASAT UNIVERSITY
Ref. code: 25605902042190NPJ
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Independent study title SHORT SELLING AND PRICE PRESSURE
AROUND ACQUISITION ANNOUNCEMENT:
EVIDENCE FROM THAILAND
Author Miss Pensiri Thepchoom
Degree Master of Science (Finance)
Major
field/Faculty/University
Master of Science Program in Finance
(International Program)
Faculty of Commerce and Accountancy
Thammasat University
Independent study advisor Associate Professor Seksak Jumreornvong, Ph.D.
Academic year 2017
ABSTRACT
In this study, we would like to investigate specifically on acquisition
announcement through tender offer in Thailand to see whether it has an impact on
investors choice to short sale the acquiring firm’ stock or not by examining the volume
of short sale around acquisition announcement.
We believed that this study will help us understand investor behavior and
dynamic of the market when there is an event affecting investor strategy to maximize
their profit and whether there’ s a mergers arbitrageurs or risk arbitrageurs who would
attempts to create profit from the news of acquisition announcement through tender offer.
Keywords: short sale, tender offer, price pressure, clinical study
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ACKNOWLEDGEMENTS
I would like to express my gratitude for various people for their contribution to
this Independent Study; My advisor, Associate Professor Seksak Jumreornvong, Ph.D.,
for his patient guidance and knowledge, as well as Assistant Professor Chaiyuth
Padungsaksawasdi, Ph. D. and Ajarn Thanomsak Suwannoi, DBA., the member of
committee for their valuable and constructive advice, I also wish to thank my friends
and family for their endless and continuous encouragement throughout my years of
study. This accomplishment would not have been possible without them. Thank you.
Miss Pensiri Thepchoom
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TABLE OF CONTENTS
Page
ABSTRACT (1)
ACKNOWLEDGEMENTS (2)
LIST OF TABLES (5)
CHAPTER 1 INTRODUCTION 1
1.1 Short Sale 1
1.2 Merger and Acquisition 1
1.3 Tender Offer 2
CHAPTER 2 REVIEW OF LITERATURE 4
2.1 Review of Literature 4
2.1.1 Mitchell M, Pulvino T, and Stafford E, 2004, Price Pressure 4
around Mergers
2.1.2 Blau B, Fuller K, and Wade C, 2015, Short selling and Price 4
Pressure Around Merger Announcements.
2.1.3 Diether K, Lee K, and Werner I, 2009, Can Short-sellers 5
Predict Returns? Daily Evidence.
2.1.4 Zhu P, Malhotra S, 2008, Announcement Effect and Price 6
Pressure: An Empirical Study of Cross-Border Acquisitions by
Indian Firms
2.1.5 Liu T, Wu J, 2014, Merger Arbitrage Short Selling and Price 6
Pressure
2.2 Theoretical Framework 7
2.2.1 Short Interest Theory 7
2.2.2 Merger arbitrage 7
2.2.3 Hubris Hypothesis 7
2.2.4 Synergies 8
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CHAPTER 3 RESEARCH METHODOLOGY 10
3.1 Data 10
3.2 Research Methodology 11
3.2.1 Ordinary Least Squares: OLS 11
3.2.2 Paired t-test 13
3.2.3 Hausman Test and Fixed Effect Model 14
3.3 Clinical Study 15
CHAPTER 4 RESULTS 26
4.1 Price Pressure 26
4.2 Significant difference between acquiring firm pre-announcement 27
and post-announcement return
4.3 Short selling during post announcement period 28
4.3.1 Clinical Studies Results 29
CHAPTER 5 CONCLUSION 50
REFERENCES 52
BIOGRAPHY 54
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LIST OF TABLES
Tables Page
3.1 Acquirer firm’s stocks 10
3.2 Correlation Matrix where j =1 12
3.3 Correlation Matrix where j =4 13
3.4 Correlation Matrix where j =9 13
3.5 Transaction Timeline of BJC and BIGC 17
4.1 Summary statistics of data used to test for price pressure 26
4.2 Results from OLS regression of equation (1) 26
4.3 P-values from Paired T-Test 27
4.4 Summary statistics of data used to test for significant short selling 28
4.5 Results from Fixed Effect Model 29
4.6 Summary Statistic of BBL 30
4.7 Results from OLS regression of BBL 30
4.8 Summary Statistic of BJC 31
4.9 Results from OLS regression of BJC 31
4.10 Summary Statistic of CPALL 32
4.11 Results from OLS regression of CPALL 32
4.12 Summary Statistic of WHA 33
4.13 Results from OLS regression of WHA 33
4.14 Summary Statistic of MAJOR 34
4.15 Results from OLS regression of MAJOR 34
4.16 Summary Statistic of PF 35
4.17 Results from OLS regression of PF 35
4.18 Summary Statistic of BAY 36
4.19 Results from OLS regression of BAY 36
4.20 Summary Statistic of BDMS 37
4.21 Results from OLS regression of BDMS 37
4.22 Summary Statistic of DTAC 38
4.23 Results from OLS regression of DTAC 38
4.24 Summary Statistic of KKP 39
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Tables Page
4.25 Results from OLS regression of KKP 39
4.26 Summary Statistic of LH 40
4.27 Results from OLS regression of LH 40
4.28 Summary Statistic of MINT 41
4.29 Results from OLS regression of MINT 41
4.30 Summary Statistic of SCB 42
4.31 Results from OLS regression of SCB 42
4.32 Summary Statistic of SCC 43
4.33 Results from OLS regression of SCC 43
4.34 Summary Statistic of TCAP 44
4.35 Results from OLS regression of TCAP 44
4.36 Summary Statistic of TMB 45
4.37 Results from OLS regression of TMB 45
4.38 Summary Statistic of TU 46
4.39 Results from OLS regression of TU 46
4.40 Summary Statistic of UV 47
4.41 Results from OLS regression of UV 47
4.42 Summary Statistic of VGI 48
4.43 Results from OLS regression of VGI 48
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CHAPTER 1
INTRODUCTION
1.1 Short sale
Short sale is a sale of securities in which investors do not own the securities,
they simply borrowed the securities, usually from the broker in expectation that the
securities price will decline and allow them to make profit by buying back the securities
at a lower price. Short selling often used by investors to either hedge or speculate, and
can be classified as speculative activity. The benefit of a short sale is that it allows
investors to add value to their portfolio even when there is a bear market since it can be
difficult to make profit in a bear market without short sale and if investors use short
sale to hedge, they can minimize their portfolio risk. The downfall of short sale is that
the loss can be limitless if the price of the securities rise instead of fall and investors
has to buy back the securities at a higher price.
1.2 Merger and Acquisition
Mergers and acquisition is a process in which a company or an acquiring
company buys target company in order to grow or change the nature of their position
in the industry. More specifically, there are three types of mergers. The first one is
Horizontal mergers which is when the company acquires another company in the same
industry often occurs with a large company to gain more complete product line or even
realized economies of scale and greater market share. The second one is a vertical
merger or vertical integration, an example of this merger is when the manufacturer
merges with their supplier in order to cut costs or to have more cost effectively, increase
synergies and realized a higher profit. Vertical merger can be further divided into 2
types which are backward integration and forward integration. Backward integration
refers to an integration with raw material or component firms whereas forward
integration refers to an integration with distribution firms. The third type of merger is
conglomerate mergers which can be described as two companies that has unrelated
business merge together to diversify the company and reduce risk. After the merger is
complete, the two companies would become one new company.
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An acquisition of the company is different from the merger since the target
company is usually smaller and the acquiring company would buy target company’ s
stock or their assets or both and then the target company would generally be absorbed
into the acquiring company or run as a subsidiary The acquiring company may decide
to perform an acquisition to another company for numerous reasons such as to gain a
greater market share in the industry, seeking an economies of scale, a reduce in cost or
synergy increase.
Motivations for M&A
1. Economies of scale which will occur when a company increased total output,
which leads to a reduced in cost per unit or operating more efficiently with an
increasing operating unit
2. Synergy refer to a greater combined value of 2 combining companies which can
lead to cost reduction and increased in various benefits such as revenue increase,
improvement in operation and increase in managerial effectiveness which will
eventually lead to a better financial performance of a company.
3. Growth – By merging or acquiring another company gives the acquiring
company room to grow their market share and also eliminating competition at
the same time if there’re merging with a company within the same industry.
M&A are appropriate choice for a company that need immediate growth for the
business without having to wait for their sales or marketing strategy to pay off.
4. Diversification – If the two companies merging are operating in an unrelated
business, they both can diversified and reduce risk through this amalgamation.
5. Accessing new markets – Merging or acquiring a distributor can open up an
opportunity for a company to sell their existing product to a brand new market.
6. Tax Benefits - Financial advantages might instigate mergers and corporations
will fully build use of tax- shields, increase monetary leverage and utilize
alternative tax benefits (Hayn, 1989).
1.3 Tender Offer
The tender offer is a transaction in which the acquirer offers to buy the target
companies by making a public offer to purchase the target’ s firm stock at a specific
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price usually at a premium over market price. The acquirer company uses tender offer
to acquire the company in order to gain control of the target company and with the
successful completion of the tender offer became the merger of two companies. In a
case in which stockholder does not accept the tender offer, if the acquirer company able
to gather a large enough proportion of target firm’ s stock, the acquirer can force the
remaining stockholders to sell their stock and delist or take the company private or
merge into existing business, in this case it’s also known as a hostile takeover.
In this study, we would like to investigate specifically on the acquisition
announcement through a tender offer in Thailand to see whether it has an impact on the
investors choice to short sale the acquiring firm’ stock or not by examining the volume
of short sale around acquisition announcement. According to Harris and Gurel, 1986;
Shleifer, 1986; Bagwell, 1992; Madhavan, 2001.Mitchell, Pulvino, and Stafford (2004),
short selling response to merger announcement can increase the effective supply of
shares causing the acquiring firm’ s stock price to decrease. We will examine whether
post announcement short selling add price pressure to acquiring firm’ s stock price. In
addition, we will also test whether there’s high short selling in acquiring firm’s stock
during post announcement period.
We believed that this study will help us understand investor behavior and
dynamic of the market when there is an event affecting investor trading strategy to
maximize their profit and whether there is a merger arbitrageurs or risk arbitrageurs
who would attempt to create profit from the news of merger and acquisition
announcement through the tender offer by simultaneously short sale acquiring firm’ s
stock and buy the target firm’s stock.
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CHAPTER 2
REVIEW OF LITERATURE
2.1 Review of Literature
2.1.1 Mitchell M, Pulvino T, and Stafford E, 2004, Price Pressure around
Mergers
In this paper, they used Merger announcement of U. S. publicly traded
companies between 1994 and 2000 and short interest data from the NYSE, NASDAQ
and AMEX between 1994 to 2001 to examine trading behavior of investors and to find
whether the announcement of merger has an effect on stock price or add price pressure
to stock by measure the change in stock price and the shorting activities around the
process of merger. The result of their studies shows that there is an existence of short
term price pressure around the mergers which leads to a temporary change in price since
these effects only appear for a short period of time.
2.1.2 Blau B, Fuller K, and Wade C, 2015, Short selling and Price Pressure
Around Merger Announcements.
In this paper, they used Mergers announced between January 1, 2005 and
December 31, 2006, Daily short sale data for NYSE- and NASDAQ- listed stocks,
Prices, Return, Daily volume, Shares outstanding and market capitalization to test
whether there’re abnormal short selling activities around Merger announcement. While
Harris and Gurel, 1986; Shleifer, 1986; Bagwell, 1992; Madhavan, 2001). Mitchell,
Pulvino, and Stafford (2004) or MPS from previous study suggested that an increase
in supply of acquiring firm’s stock due to the short selling in response to the
announcement of the merger would decrease the acquiring firm’stock price, this paper
use daily short sale data instead of monthly short sale data like MPS and restudy MPS
to determine whether the short selling activity after the announcement add price
pressure to the acquiring firm’s stock or leads to a decrease in acquiring firm’s stock
price. If the short selling add price pressure to the acquiring firm’s stock it means that
post announcement return of acquiring firm’s stock would have a negative relationship
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with short selling activity after the announcement. Their results suggested that there’s
no relationship between post announcement return and short selling activity which
leads to a conclusion that short selling does not add price pressure to the acquiring firm
stock. Furthermore, they also test whether there’s high short selling activity around the
merger announcement by examine short selling activity around the merger
announcement. The result of their study shows a significant increase in short selling
activity on event day and after the announcement, but no significant short sale prior to
the announcement, which suggested that the short selling activity does not hold any
private information about the upcoming announcement.
2.1.3 Diether K, Lee K, and Werner I, 2009, Can Short-sellers Predict Returns?
Daily Evidence.
In this paper, they used daily short-selling activity for all NYSE and Nasdaq
listed US stocks during 2005. They’re focusing on the trading strategies used by short
sellers and test whether short sellers are contrarian traders who target on stocks with
recent price increases or momentum traders who target on stocks with recent price
decrease. The results from their study shows that short sellers are primarily contrarian
traders, contrarian traders would increase their short sale of stock with a positive return
and decrease their short sale of stock following negative return. But not all short seller
are contrarian since they also find an evidence that some short sellers are momentum
short sellers who follows momentum strategy by increase their short sale of stock with
negative return and decrease their short sale with positive return.
They also test whether short sellers in the U. S. are able to predict future
returns, their results suggested that an increased in short selling activity by short sellers
predicts negative abnormal future returns as much as five days out. From the result of
their study, they conclude that short seller are not the villain, instead, they help correct
short term overreactions and underreaction of stock prices to information.
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2.1.4 Zhu P, Malhotra S, 2008, Announcement Effect and Price Pressure:
An Empirical Study of Cross-Border Acquisitions by Indian Firms
This paper studied cross border mergers and acquisitions and examines the
short term stock performance of Indian firms acquiring U.S. firms from 1999 to 2005.
They investigated whether cross border mergers and acquisitions announce has an
impact on acquiring firm’s stock price, they also test whether there’s price pressure on
the announcement return. By using cumulative abnormal return, their analysis
suggested an increase in Indian acquiring firm’s stock price following the merger
announcement but these positive impacts lasted for a short period of time since the
abnormal return of acquiring firm’s stock started to decrease after 3 days of the
announcement. For the price pressure, they followed a methodology proposed by
Michaely, Thaler, and Womack (1995), where they calculate the abnormal trading
volume around the mergers and acquisition announcement date. They propose that, if
the security demand curve is downward sloping in the short term, stock prices may be
influenced by excess demand or supply. By using OLS and 2SLS regression where they
used Average Daily Abnormal Trading Volume as dependent variable and used
cumulative abnormal return and size as the independent variable, their results support
price pressure where there’s high trading volume around announcement period.
2.1.5 Liu T, Wu J, 2014, Merger Arbitrage Short Selling and Price Pressure
This paper examined short selling data available from January 2005 through
June 2007 to study short selling price pressure around mergers in an attempt to provide
new evidence on merger arbitrage short selling price pressure hypothesis by using short
selling over 3 days period. They also used all announced deals instead of only
completed deals. For the proxy of the exchange ratio, they employ the actual fixed
exchange ratios collected from merger documents instead of using a ratio market cap
of an acquirer to its target. Their results show that large negative returns to the fixed-
exchange-ratio stock acquirers are predominantly driven by the downward price
pressure from merger short arbitrage.
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2.2 Theoretical Framework
2.2.1 Short Interest Theory
The related theory for this study is the Short Interest Theory, which holds
that securities with a high level of short interest may increase in price. This theory
suggested that heavily shorted securities may have a significant price appreciation in
the near future because the short position must eventually be covered by the purchased
of the securities.
2.2.2 Merger arbitrage
According to Harris and Gurel, 1986; Shleifer, 1986; Bagwell, 1992;
Madhavan, 2001.Mitchell, Pulvino, and Stafford (2004), “short selling will increase
during the post merger announcement because of the trading by merger arbitrageurs”
which can be described as a trading strategy that investors use to profit from the
difference between the offer price and target firm’s stock price (Mitchell and Pulvino,
2001). Merger arbitrage also known as risk arbitrage is an event driven trading strategy,
practiced by simultaneously buying the target firm’s stock and short sale the acquiring
firm’s stock to create riskless profit. If the merger succeeds, arbitrageurs can earn the
arbitrage spread which is the difference between target firm’s stock price that would
trade at discount and price that the acquirer offers. In a case where the merger did not
succeed, price of the target firm’s stock may decrease to a price closer to pre-
announcement price resulting in a loss. For fixed exchange rate mergers, acquiring
company will exchange fixed amount of their stock for each target firm’s stock then
merger arbitrageurs will try to take profit from the mergers by short selling a fixed
amount of acquiring firm’s stock to minimize the market risk and the short position in
the acquiring firm’s stock will be cancelled after the merger is close and the target
firm’s stocks are converted to acquiring firm’s stock.
2.2.3 Hubris Hypothesis
Hubris refer to excessive pride, self-confidence or arrogance. The hubris
hypothesis (Roll, 1986) implies that pure economic gains to the acquiring firm are not
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the primary motivation in the acquisition. Roll ( 1986) stated that in order to explains
takeover by hubris hypothesis, the following should occur
1. The stock price of the acquiring firm should fall after the market becomes aware
of the takeover since the takeover is not in the best interests of acquiring firm’s
shareholders and the takeover isn’t an efficient allocation of their wealth.
2. The stock price of the target firm should increase because the acquiring firm
will pay a premium to the target firm or might even pay a premium for excess
value of the target firm.
3. When the target firm value increased and acquiring firm value decreased, the
combined effect should be negative when considers the cost of the takeover.
Hubris hypothesis (Roll, 1986), refers a psychological effect of overconfidence
suggested that the acquiring firm have a tendency to pay too much for the target firm,
the company management are over optimistic about their ability to create value to a
target firm. Malmendier and Tate, 2005; Heaton, 2002 suggested that overconfident
managers are overestimating the return of their investment resulted in an overpaid the
premium.
2.2.4 Synergies
The concept of synergies is 1+1 = 3 or that the value of the two companies
together should be greater than a value of two separate companies. Sirower (1997)
defines synergies as “increases in competitiveness and resulting cash flows beyond
what the two companies are expected to accomplish independently”. In mergers and
acquisitions, there are different types of synergies, Sevenius (2003) has classified
synergies as followed:
- Revenue synergies which related to economies of scope and increasing in
revenue. An example of this are extensions of customers and products
(Sevenius, 2003), and cross selling or bundling (Schriber, 2009).
- Cost synergies which allow the companies to reduce cost from economies of
scale, cost of logistics, overhead costs or administrative costs. The company can
also have a more efficient utilization of resources.
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- Financial synergies which related to decreased costs of capital through lowered
risks, better cash flows and increased financial margins (Sevenius, 2003).
- Market synergies which related to higher margins achieved through increased
negotiation capabilities towards suppliers and customers (Sevenius, 2003).
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CHAPTER 3
RESEARCH METHODOLOGY
3.1 Data
For this study, we gathered tender offer data in Thailand between 2004 to 2016
from the SEC (The Securities and Exchange Commission) where both acquiring firms
and target firms are publicly traded in SET (The Stock Exchange of Thailand) We also
used daily short sale data, daily volume, prices, returns, market capitalization and a
number of shares outstanding from set smart.
As we gathered tender offer data from the SEC in total of 239 tender offers, and
daily short sale data from 2002-2016, the data shows that there’re only 41 tender offers
out of 239 tender offers that the acquiring firm's stock were shorted by investor and
there’ re a total of 19 acquirers in 41 tender offers. The short sale data also show that
the acquirer’s stock were not shorted at all between 2002-2003 therefore, we will use a
total of 41 tender offers and examine the volume of short sale between a period of 2004
to 2016.
Our limitation of this study is that tender offer data from the SEC is not
including all of mergers and acquisition in Thailand since the SEC has only tender offer
data that an offerer files tender offer document 247-4 form to the SEC.
Table 3.1 Acquirer firm’s stocks
Acquirer’s stocks
BAY BANK OF AYUDHYA PCL
BBL BANGKOK BANK PCL
BDMS BANGKOK DUSIT MEDICAL SERVICES PCL
BJC BERLI JUCKER PCL
CPALL CP ALL PCL
DTAC TOTAL ACCESS COMMUNICATION PCL
KKP KIATNAKIN BANK PCL
LH LAND AND HOUSES PCL
MAJOR MAJOR CINEPLEX GROUP PCL
MINT MINOR INTERNATIONAL PCL
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Table 3.1 Continued
Acquirer’s stocks
PF PROPERTY PERFECT PCL
SCB THE SIAM COMMERCIAL BANK PCL
SCC THE SIAM CEMENT PCL
TCAP THANACHART CAPITAL PCL
TMB TMB BANK PCL
TU THAI UNION GROUP PCL
UV UNIVENTURES PCL
VGI VGI GLOBAL MEDIA PCL
WHA WHA CORPORATION PCL
3.2 Research Methodology
3.2.1 Ordinary Least Squares: OLS
For the first hypothesis, to test whether post announcement short sale drives
the negative post announcement return or add price pressure to the acquiring firm’s
stock price, we used the following equation
𝑅𝑒𝑡𝑢𝑟𝑛𝑖,𝑡,𝑡+𝑗 = 𝛽0 + 𝛽1𝑆𝑖𝑧𝑒𝑖,𝑡 + + 𝛽2𝑅𝑣𝑜𝑙𝑡𝑖,𝑡 + 𝛽3𝑇𝑢𝑟𝑛𝑖,𝑡 + 𝛽4𝑆ℎ𝑜𝑟𝑡𝑟𝑎𝑡𝑖𝑜𝑖,𝑡,𝑡+𝑗
+ ε𝑖,𝑡,𝑡+𝑗
(1)
Where;
Dependent Variable
𝑅𝑒𝑡𝑢𝑟𝑛𝑖,𝑡,𝑡+𝑗 is the post announcement return of acquiring firm’s stock from day t to
to t+j where j = 1, 4, 9
𝑅𝑒𝑡𝑢𝑟𝑛 = 𝐸𝑛𝑑𝑖𝑛𝑔𝑃𝑟𝑖𝑐𝑒 − 𝑆𝑡𝑎𝑟𝑡𝑖𝑛𝑔 𝑃𝑟𝑖𝑐𝑒
𝑆𝑡𝑎𝑟𝑡𝑖𝑛𝑔 𝑃𝑟𝑖𝑐𝑒
Independent Variable
𝑆𝑖𝑧𝑒𝑖,𝑡 acquiring firm's market capitalization on event day
𝑀𝑎𝑟𝑘𝑒𝑡 𝐶𝑎𝑝𝑖𝑡𝑎𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 = 𝐶𝑙𝑜𝑠𝑒 𝑃𝑟𝑖𝑐𝑒 ∗ 𝑆ℎ𝑎𝑟𝑒𝑠 𝑂𝑢𝑡𝑠𝑡𝑎𝑛𝑑𝑖𝑛𝑔
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𝑅𝑣𝑜𝑙𝑡𝑖,𝑡 return volatility which is the standard deviation of daily returns from
day t-10 to t
𝑇𝑢𝑟𝑛𝑖,𝑡 shareturnover on event day, share turnover is a measure of trading
activity which is a ratio of daily trade volume relative to shares
outstanding
𝑆ℎ𝑎𝑟𝑒 𝑇𝑢𝑟𝑛𝑜𝑣𝑒𝑟 = 𝐷𝑎𝑖𝑙𝑦 𝑇𝑟𝑎𝑑𝑒 𝑉𝑜𝑙𝑢𝑚𝑒
#𝑆ℎ𝑎𝑟𝑒𝑠 𝑜𝑢𝑡𝑠𝑡𝑎𝑛𝑑𝑖𝑛𝑔
𝑆ℎ𝑜𝑟𝑡𝑟𝑎𝑡𝑖𝑜𝑖,𝑡,𝑡+𝑗 a measure of shorting activity of acquiring firm’ stock which is a
ratio of daily short volume relative to daily trade volume from day t
to to t+j where j = 1,4,9
𝑆ℎ𝑜𝑟𝑡 𝑅𝑎𝑡𝑖𝑜 = 𝐷𝑎𝑖𝑙𝑦 𝑆ℎ𝑜𝑟𝑡 𝑉𝑜𝑙𝑢𝑚𝑒
𝐷𝑎𝑖𝑙𝑦 𝑇𝑟𝑎𝑑𝑒 𝑉𝑜𝑙𝑢𝑚𝑒
To test this hypothesis, First, We used Correlation Matrix to find if there’s any
relationship between independent variables. If coefficient estimates are greater than 0.8
then we would have Multicollinearity which is a state where there is high inter
correlations among the independent variables and coefficient estimates of the multiple
regression may change erratically in response to small changes in the model.
Table 3.2 Correlation Matrix where j =1
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟏 𝑺𝒊𝒛𝒆𝒊,𝒕 𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 𝑻𝒖𝒓𝒏𝒊,𝒕 𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟏
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟏 1.0000
𝑺𝒊𝒛𝒆𝒊,𝒕 0.0709 1.0000
𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 0.2546 -0.1189 1.0000
𝑻𝒖𝒓𝒏𝒊,𝒕 0.1173 -0.1184 0.4768 1.0000
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟏 0.0791 0.2286 0.2444 -0.0316 1.0000
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Table 3.3 Correlation Matrix where j =4
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟒 𝑺𝒊𝒛𝒆𝒊,𝒕 𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 𝑻𝒖𝒓𝒏𝒊,𝒕 𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟒
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟏 1.0000
𝑺𝒊𝒛𝒆𝒊,𝒕 0.1648 1.0000
𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 -0.1658 -0.1189 1.0000
𝑻𝒖𝒓𝒏𝒊,𝒕 0.0210 -0.1184 0.4768 1.0000
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟒 -0.2063 0.3062 0.2769 -0.0309 1.0000
Table 3.4 Correlation Matrix where j =9
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟗 𝑺𝒊𝒛𝒆𝒊,𝒕 𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 𝑻𝒖𝒓𝒏𝒊,𝒕 𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟗
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟗 1.0000
𝑺𝒊𝒛𝒆𝒊,𝒕 0.2664 1.0000
𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 -0.2140 -0.1189 1.0000
𝑻𝒖𝒓𝒏𝒊,𝒕 -0.0678 -0.1184 0.4768 1.0000
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟗 -0.1058 0.2842 0.2454 -0.0491 1.0000
Results from Correlation Matrix shows no coefficient estimates greater than 0.8
which suggested no Multicollinearity.
By using Ordinary Least Squares: OLS, we would determine whether the post
announcement short sale activity add price pressure to acquiring firm’s stock price
which lead to a decrease in acquiring firm’s stock price or not. We will test this
hypothesis for 3 different period, 2 days, 5 days and 10 days after the event. If the post
announcement short selling leads to a decrease in acquiring firm’s stock price or add
price pressure to the acquiring firm’s stock price then 𝛽4 which is the coefficient of the
short ratio would be negative.
3.2.2 Paired t-test
We would also test whether there’s a significant difference between
acquiring firm pre-announcement return and post-announcement return for 3 different
periods, 2 days, 5 days and 10 days by using Paired t-test
𝑅𝑒𝑡𝑢𝑟𝑛 = 𝐸𝑛𝑑𝑖𝑛𝑔 𝑃𝑟𝑖𝑐𝑒 − 𝑆𝑡𝑎𝑟𝑡𝑖𝑛𝑔 𝑃𝑟𝑖𝑐𝑒
𝑆𝑡𝑎𝑟𝑡𝑖𝑛𝑔 𝑃𝑟𝑖𝑐𝑒
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Hypothesis
Ho: True mean difference is equal to zero, No statistically significant difference
between acquiring firm pre-announcement return and post-announcement
return
Ha: True mean difference is more than zero, pre-announcement return is higher than
post-announcement return
3.2.3 Hausman Test and Fixed Effect Model
For this hypothesis, we aimed to test whether there’s high short selling in
acquiring firm’s stock during post announcement period by using the following
equation
𝑠ℎ𝑜𝑟𝑡𝑟𝑎𝑡𝑖𝑜𝑖,𝑡,𝑡+4 = 𝛽0 + 𝛽1𝐴𝑁𝑁𝑡 + 𝛽2𝑅𝑒𝑡𝑖,𝑡,𝑡+4+𝛽3𝑅𝑒𝑡𝑖,𝑡−5,𝑡−1
+𝛽4𝑆ℎ𝑜𝑟𝑡𝑟𝑎𝑡𝑖𝑜𝑖,𝑡−5,𝑡−1+𝛽5𝑃_𝑣𝑜𝑙𝑡𝑖,𝑡,𝑡+4+ 𝛽6𝑃_𝑣𝑜𝑙𝑡𝑖,𝑡−5,𝑡−1 +
𝛽7𝑇𝑢𝑟𝑛𝑖,𝑡−5,𝑡−1 + ε𝑖,𝑡,𝑡+4
(2)
Where;
𝑠ℎ𝑜𝑟𝑡𝑟𝑎𝑡𝑖𝑜𝑖,𝑡,𝑡+4 the average short ratio of acquiring firm’ stock from day t to
t+4
𝐴𝑁𝑁𝑡 an indicator variable equal to 1 on the announcement day, 0
otherwise
𝑅𝑒𝑡𝑖,𝑡,𝑡+4 average return of acquiring firm’s stock from day t to t+4
𝑅𝑒𝑡𝑖,𝑡−5,𝑡−1 lagged return which is the average return of acquiring firm’s
stock from day t-5 to t-1
𝑆ℎ𝑜𝑟𝑡𝑟𝑎𝑡𝑖𝑜𝑖,𝑡−5,𝑡−1 lagged dependent variable which is the average short ratio of
acquiring firm’ stock from day t to t+4 to control for serial
correlation
𝑃_𝑣𝑜𝑙𝑡𝑖,𝑡,𝑡+4 average price volatility of acquiring firm’s stock from day t to
t+4 where price volatility is the difference between the daily
high price and the daily low price, divided by the daily high
price (Diether et al. 2009).
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𝑃_𝑣𝑜𝑙𝑡𝑖,𝑡−5,𝑡−1 lagged price volatility of acquiring firm’s stock from day t-5
to t-1
𝑇𝑢𝑟𝑛𝑖,𝑡−5,𝑡−1 lagged share turnover of acquiring firm’s stock from day t-5
to t-1 where share turnover is a ratio of daily trade volume
relative to shares outstanding
Hypothesis
Ho: No significance short selling in acquiring firm's stock during post announcement
period
Ha: Significance short selling in acquiring firm's stock during post announcement
period
By using Panel regression, we aimed to deploy Hausman Test to determine
whether Fixed effect model or Random effect model is suitable for the data by stating
the hypothesis as follow
Ho: Random Effect model is appropriate
Ha: Fixed effect model is appropriate
Result from Hausman Test shows P-value of 0.0000. We rejected the null
hypothesis which means that Fixed effect model is the appropriate model.
Next, we regressed (2) equation using Fixed Effect Model to test whether there’s
significance short selling in acquiring firm's stock during post announcement period. If
P-Values of ANN, indicator variable is less than 0.05 we would reject the null
hypothesis which means that there’s significance short selling in acquiring firm's stock
during post announcement period.
3.3 Clinical Studies
Since we have a small set of data, we will also test for significance short selling
in each acquiring firm's stock in total, of 19 stocks during post announcement period
by using Ordinary Least Squares: OLS.
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3.3.1 WHA and HEMRAJ
Date of submission of the Tender offer: December 2, 2015WHA or WHA
Corporation Public Company Limited is Thailand’ s leader in fully integrated logistics
and industrial facilities with 2 main core business which are Real Estate Development
and Solar PV Rooftop.
HEMRAJ or Hemraj Land and Development Public Company Limited’ s
business are real estate development of industrial for sale having factory and warehouse
for rent, utility services and power business. Benefits that come with the acquisition of
HEMRAJ is significant synergies to be captured. While WHA customer base are
focusing on consumer products and healthcare product, HEMRAJ are focusing on
automotive and petrochemicals, with different product WHA can expand their customer
base and also realized economies of scale. Furthermore, with WHA’ s roof area
combined with HEMRAJ’ s, they would be able to expand their solar PV Rooftop to
almost 2 million square meters.
3.3.2 BJC and BIGC
Date of submission of the Tender offer: March 28, 2016
BJC or BERLI JUCKER PUBLIC COMPANY LIMITED became Big C’s
major shareholder when it purchased 58. 55% of Big C’ s shares and after the tender
offer for the remaining shares in total, of 39.39% at THB 252.88 per share, BJC holds
a total of 97.94% of the Big C shares. Berli Jucker core business can be divided into 4
business units Packaging business unit, Healthcare and Technical business unit,
Consumer business unit and others business unit. After the acquisition of Big C
Supercenter, modern retail supply chain became the fifth core business of Berli Jucker.
Big C Supercenter is Thailand’ s leading retailer with over 100 branches. It core
business can be divided into two groups, retail and property. With the acquisition of
Big C, Berli Jucker has transformed its business model from primarily concentrate on
trading and manufacturing company to an integrated retailer with a full value chain
where Big C accounted for the largest proportion of sale.
Rationale for the acquisition of Big C is to penetrate into the modern retail
business, enhance the competitiveness and create the expansion opportunity in Thailand
and ASEAN. There’ re various significant synergies through integration of Big C
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Supercenter. First is an economy of scale through leveraging manufacturing capability
for private brands such as cross selling a variety of Berli Jucker’ s product through Big
C network. Second is fully integrate logistics operations across the entire value chain
such as improving Big C’ s infrastructure. Third is combining purchasing power and
optimize retail operations by utilizing Big C’ s expertise in retail to improve
performance of Berli Jucker smaller retail banner. Furthermore, Berli Jucker can cross
utilize IT and back office infrastructure by sharing IT system to optimize cost.
3.3.2.1 Transaction Overview
BJC Supercenter Company Limited “ BJCT” acquired 264,797,600
shares directly from Geant International BV or 32. 10% and SAMPHUNSAMER
Company Limited “Samphunsamer” which is a direct subsidiary of BJCT acquired the
amount of 218,280,000 shares, representing 26. 45% of the total issued and paid- up
shares of BigC and 26. 45% of the total voting rights of Big C. Therefore, BJCT and
Samphunsamer directly and indirectly acquired the Big C’ s shares in total of
483,077,600 shares or 58. 55% and with the tender offer for the remaining shares of
BigC from BJCRH, BJCT and Samphunsamer, BJC owns a total off 807. 99 million
shares of Big C or 97.94%.
Table 3.5 Transaction Timeline of BJC and BIGC
Date Event
22 Feb 2016 BOD’s Meeting acquisition of Big C
21 Mar 2016 - Direct and indirect acquisition of shares in Big C equivalent to
58.55%
- BJC has consolidated Big C financial statement
29 Mar – 11 May 2016 Tender offer period for 25 days
11 May 2016 Total shares hold by BJC in total of 97.94%
In quarter 1, 2016 after the acquisition of Big C, Modern retail supply chain
reported sales of THB 3,580 million and gross profit of THB 595 million or 16.60% of
gross profit margin. EBIT is equal to THB 281 million, with 7. 80% of EBIT margin
and net profit is THB 119 million with 3.30% of net profit margin. For quarter 2, 2016
modern retail supply chain reported sales of THB 30,187 million, gross profit of THB
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4,344 million or 14. 40 % of gross profit margin. They also reported 9. 10% of EBIT
margin and 6.10% net profit margin or THB 1,838 million.
Significant Synergies through Integration of Big C
Economies of scale through leveraging manufacturing capability for private brands
- Promote BJC Group Product: Cross selling of BJC products through Big C network
- Private Label: Potential to increase penetration of private label
- Cross selling of insurance products across Big C / BJC customers
- Optimize tenant mix of shopping malls to improve profitability and optimize real
estate management through internalization within BJC team
- Fully integrate logistics operations across entire value chain
- Leveraging BJC’s leadership in consumer supply chain and logistics
- Logistics: Improving Big C’s infrastructure
- Utilizing Big C’s expertise in retail to improve performance of BJC’ s smaller
retail banner.
3.3.2.2 News related to the acquisition
Thai BJC shareholders approve $6.2 billion Big C buy, MARCH 21,
2016, REUTERS ( https://www.reuters.com/article/us-berli-jucker-m-a-casino-id
USKCN0WN1AH)
BANGKOK (Reuters) - Thailand’s Berli Jucker Pcl (BJC) (BJC.BK)
shareholders have voted in favor of a $6.2 billion acquisition of hypermarket operator
Big C Supercenter Pcl BIGC.BK from France’s Casino Group (CASP.PA), sources told
Reuters. Some 99.99 percent of voters approved the plan at Monday’s meeting, two
financial sources who attended it said. Berli, the core retail business of Thai tycoon
Charoan Sirivadhanabhakdi’s TCC group, won a hotly contested auction for Casino’s
58.6 percent stake in Big C.
Earlier, Casino said it was on track to reduce debt as promised after
Standard & Poor’s cut the French retailer’s credit rating to junk, citing falling profits,
weakness in Brazil and competition at home. The Thai group secured $6.2 billion short-
term financing deal with 15 banks to fund the Big C acquisition on Wednesday.
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Berli is expected to pay Casino by the end of March and the company
will buy the remaining shares from minority shareholders in a tender offer, to be
completed by May, one source said.
BJC closes Big C tender offer, May 12, 2016, BANGKOKPOST
SET-listed Berli Jucker Plc (BJC), the major shareholder in Big C
Supercenter Plc, yesterday closed its 25-day tender offer for the remaining 41.45%
stakes in the hypermarket chain. BJC did not report the result of its tender offer. But it
is expected that BJC, which held a 58.55% stake in Big C before the tender offer, can
at least raise its holding to 85%, said an informed source at BJC.
Central Group, which has a 25% stake in Big C, on Tuesday agreed to
sell its holding at the tender offer of 252.88 baht per share. A minor shareholder with a
1.45% stake also agreed to sell. A source close to the share sale said Central would get
about 50 billion baht from the Big C share sale and it would use the money to fund its
Big C Vietnam purchase. BJC has prepared a budget of 86.46 billion baht to buy the
remaining 41.45% or 341.92 million shares in Big C.
BJC’s tender offer agents are Krungthai Bank, KT Semico Securities,
Bualuang Securities, Kasikorn Securities and Phatra Securities. The tender offeror is
BJC Supercenter, which also represents BJC Retail Holding and Samphunsamer. All of
them are BJC subsidiaries. Prior to the tender offer, BJC held a 58.55% stake in Big C
through BJC Supercenter (32.1%) and Saowanee Holding (26.45%).
TCC Group, led by billionaire Charoen Sirivadhanabhakdi, won the
bidding to buy the Big C assets in Thailand from French retailer Casino Group for €3
billion (120 billion baht). The group assigned BJC, its flagship retail unit, to control
Big C. Big C has plans to open 84 new stores this year, including branches of Big C
Market and Mini Big C as well as Pure drugstores. A retail industry source said Central
decided to sell its 25% stake in Big C because it wanted to unlock itself from an
agreement with Casino that meant Central could not operate its hypermarket or discount
store business on its own in Thailand.
BJC shares closed yesterday on the Stock Exchange of Thailand at 36.50
baht, up 50 satang, in trade worth 45.7 million baht. Big C shares closed at 236 baht,
down two baht, in trade worth 4.53 million baht.
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3.3.3 CPALL and MAKRO
Date of submission of the Tender offer: June 27, 2013
CP All Plc. was established in 1988 by the Charoen Pokphand Group.
The Company is the sole operator of 7-Eleven convenience stores in Thailand, which
has been granted an exclusive right from 7-Eleven, Inc., USA to conduct business under
the Area License Agreement. In 1989, the first 7-Eleven outlet in Thailand was opened
on Patpong Road.
CP All business are as follow: Convenience Store Services such as
7-eleven and Kudson, Financial Services, Ready to eat and Bakery Service, Education
Services and Retail Business, Information Services, Marketing Communications
Services, Management Services to Logistics and after the acquisition of MAKRO,
Wholesale Services.
At the end of the year 2012, CP ALL had a total of 6,822 7-Eleven stores
nationwide. Of the total, 3,177 stores are in Bangkok and vicinity or 46.60% and 3,645
stores are in provincial areas or 53.40%. CP ALL also expanded another 546 new
outlets both as stand-alone stores and stores located in PTT gas stations to reach more
target customers both in Bangkok, the vicinity and provincial areas. At the end of 2012,
CP ALL had 5,842 stand-alone stores which is 85.60% and 980 stores in PTT gas
stations which equal to 14.40%. (www.cpall.co.th)
Siam Makro Public Company Limited (MAKRO) has been operating as the
Cash and Carry Trade Centers, selling consumer goods to customers which consist of
various product such as Electrical Appliances, restaurant and food service business,
Textile and clothes and Beverages, snacks. The acquisition of MAKRO makes CP ALL
PCL Thailand’s leading in both retail and wholesale business and Asia third largest
retailer not including Japan. By acquiring shares of MAKRO both directly and
indirectly resulting in an increase to more than 50% holding of total voting right.
3.3.3.1 Transaction Overview
Transaction structure can be divided into two steps. First is the initial
acquisition where CP ALL acquires approximately 64.35% and the second step is the
tender offer for the remaining shares at the tender offer price of THB 787 per share.
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CP ALL acquired shares of MAKRO both directly and indirectly by
acquiring shares from Siam Makro PCL “Makro”, Siam Makro Holdings Co., Ltd. And
OHT Co., Ltd. resulting in a total shareholding of 64.35% or 154,429,500 shares. CP
All also offering to purchase the remaining 81,264,900 shares through tender offer
which is equivalent to 33.86% of the Company’s total issued and paid-up shares and
the Company’s total voting rights.
Rationale behind the acquisition of MAKRO are as follow : Improve
operational efficiency, Enhance economy of scale that would allow cost saving and new
products offering opportunities , Optimize capital structure, Open opportunity for
international expansion in Myanmar, Vietnam, Laos and Cambodia, Acquire top tier
asset and capture a new segment of retail market with well equipped plat form to further
expand and becoming Leading regional multi-format retailer and to unlock value of
under-utilized land.
In quarter 2, 2013 after the acquisition of MAKRO, total revenue of CP
ALL increased from last year by 12.40% or from THB 47,731 million to THB 53,633
million. EBIT margin decreased from 7.00% to 6.20% and net margin also decreased
from 5.50% to 4.90%
On March 28, 2018 CP ALL sell MAKRO a total of 230,248,000 shares
at the price of THB 44 representing 4.80% of the total issued share capital of Makro
through the SET Big Lot Board. According to CP ALL, the main objective of this
transaction is to increase the trading liquidity of Makro shares in the Stock Exchange
of Thailand. Following the Big Lot Transaction, CPALL will decrease its shareholding
in Makro from 97.88% to 93.08% of the total issued share capital of Makro.
3.3.3.2 News related to the acquisition
Thailand's CP All offers $6.6 billion to buy Siam Makro, APRIL
22, 2013, REUTERS (https://www.reuters.com/article/thailand-cpall-makro-
idUSL3N0DA0LV20130423)
BANGKOK, April 23 (Reuters) - CP All Pcl, a Thai convenience store
company controlled by the country’s richest man, is offering 787 baht ($27.44) per
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share to buy control of wholesaler Siam Makro Pcl, valuing the target at $6.6 billion,
CP All said in a statement on Tuesday.
The offer represents a 15.4 percent premium to Siam Makro’s last traded price on
Friday, before its shares were halted on Monday pending an announcement. CP All said
it will fund the entire acquisition using debt and does not plan to issue new shares. ($1
= 28.6850 Thai baht) (Reporting by Khettiya Jittapong; Editing by Daniel Magnowski)
Thai CP All shareholders approve Siam Makro acquisition, JUNE
12, 2013, REUTERS (https://www.reuters.com/article/thailand-cpall-makro-idUS
L3N0EO0YZ20130612)
BANGKOK, June 12 (Reuters) - A majority of CP All Pcl shareholders
approved on Wednesday a planned $6.6 billion acquisition of cash-and-carry wholesaler
Siam Makro Pcl which is expected to be completed by the third-quarter of this year.
Thailand’s largest convenience store operator aims to use Siam Makro’s
stores to expand in Asia. The two companies have combined sales of more than 300
billion baht ($9.7 billion).
CP All Chief Executive Korsak Chairasmisaka said just over 87 percent
of the company’s shareholders had voted in favour of the acquisition deal at
Wednesday’s meeting.
CP All operates stores under the 7-Eleven brand. It is controlled by
Thailand’s wealthiest man, Dhanin Chearavanont of unlisted Charoen Pokphand
Group. ($1 = 30.96 baht) (Reporting by Manunphattr Dhanananphorn; Writing by
Khettiya Jittapong; editing by Miral Fahmy)
3.3.4 MAJOR and MPIC
Date of submission of the Tender offer: August 2, 2013
Major Cineplex Group Public Company Limited is the largest operator
of movie theaters in Thailand which also involved in the bowling alley business. With
the mix of cinema and entertainment business, Major core business is Major cineplex
and bowling, karaoke and ice skating rink as secondary core business and advertising
service, rental and service, film distribution and other businesses as its supplementary
business.
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M Pictures Entertainment Public Company Limited or MPIC engages in
a movie business through its subsidiaries, consisting of a foreign film rights importing
and distributing business, a Thai moviemaking business, producing movies on VCD,
DVD and Blue- Ray, and/ or selling rights for those movie release on Free TV, Cable
TV, Pay Digital TV, Internet and/or IPTV.
Transaction Overview, according to 247-4 form the transaction are as follows
- MAJOR approved the selling ordinary shares of Major Kantana Broadcasting
Co.,Ltd. (“M Channel”) in the amount of 1,799,996 shares which equivalent to
45 % of total shares of M Channel at THB 14.38 per share, and of Talent One
Co.,Ltd. (“T1”) in the amount of 320,000 shares which equivalent to 80 % of
total shares of T1 at THB 59.68 per share to MPIC. M Channel and T1 are the
subsidiary of MAJOR, and
- MPIC approved the purchase of ordinary shares in M Channel and T1 from
MAJOR as said details. MPIC will offer newly issued shares in amount of
16,579,978 shares at the offering price of THB 2.71 per share to MAJOR instead
of cash payment of M Channel and T1 shares.
The entering of the transaction resulted in MAJOR holding more than 75% of
total issue shares of MPIC and required to make the tender offer of the remaining shares
of MPIC
3.3.5 BBL and BLS
Date of submission of the Tender offer January 17, 2012
Bangkok Bank is a leading commercial bank in Thailand, providing a
wide range of business and consumer banking and financial services in Thailand and
abroad, including corporate and personal lending, trade financing, deposit- taking and
checking account services, investment banking services, corporate financing, cash
management, credit card services and securities custody services. It main business
activities are conducted through 5 key business units: Corporate, Commercial,
Business, Consumer, and International.
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Bualuang Securities Public Company Limited engage in six activities as
follow, securities brokerage, securities trading, investment advisory service, securities
underwriting, private fund management and securities borrowing and lending
(www.bualuang.co.th)
According to 247-4 form, Bangkok bank made a tender offering to
purchase 117,884,470 shares of Bualuang Securities’s stock at THB 22 per share which
are equivalent to 43.66% of the Company’s total issued and paid up shares in order to
gain full control follow the strategy of universal banking to better satisfy customers and
cope with a rapid change in market circumstances and fast-changing technology. This
is a result of the Financial Sector Development Plan, the Capital Market Development
Plan, and the establishment of the ASEAN Economic Community ( AEC) , which
provides for financial liberalization, allowing commercial banks to engage in a greater
variety of businesses.
3.3.6 PF and TPROP, PF and GRAND
3.3.6.1 PF and TPROP
Date of submission of the Tender offer April 27, 2015
Property Perfect Public Company Limited or PF was established on
14 August 1985 by the group of Maneeya Estate’s operators which operate in the
property development business, with the focus in single houses and condominiums in
Bangkok. Property Perfect subsidiaries and associated companies operate in five
business as follow: 1. Property development group 2. Rental property and hospitility 3.
Retail group 4. Construction group and 5. Service group and others.
Thai Property Public Company Limited or TPROP was established
on 15 January 1985. At the beginning of the business, TPROP’s main business involved
in developing residential projects, such as detached house, townhouse and vacant land
for sale. In 1993, TPROP started to develop Shopping Complex project on the land
leased from the Office of National Buddhism and others.
To diversifying the source of revenue of the company, expanding the
operating in both horizontal and vertical real estates, and stabilizing revenue from
properties for rent from office buildings and hotels, Property Perfect make a tender offer
Ref. code: 25605902042190NPJ
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to purchase TPROP share at the offering price of THB 0.57 per share with conditions
that at the end of tender offer period, shareholders of TPROP who accept the offer must
hold at least 75% of the total issued and paid-up shares of TPROP.
3.3.6.2 PF and GRAND
Date of submission of the Tender offer June 16, 2015
Grande Asset Hotels and Property or GRAND focuses its business
and long term investment in hotel and real estate development. For the investment in
hotel, the Company focused mainly on the investment in international and globally
managed brand of 4-5 star hotel. With the successful acquisition of PTROP, Property
Perfect will have a significant control in GRAND indirectly (Chain Principle) resulted
in an obligation to make the Tender Offer of all securities of GRAND since TPROP is
a major shareholder of GRAND.
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CHAPTER 4
RESULTS
4.1 Price Pressure
Table 4.1 Summary statistics of data used to test for price pressure
Mean Std. Dev. Min Max
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟏 -.0005679 .0153907 -.0467698 .0335553
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟒 -.0006574 .0080003 -.021359 .0230142
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝟗 .0008925 .0054573 -.0114439 .0125697
𝑺𝒊𝒛𝒆𝒊,𝒕 1.41e+11 1.48e+11 3.26e+09 4.78e+11
𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 .0195361 .0093012 0 .0452054
𝑻𝒖𝒓𝒏𝒊,𝒕 .0044687 .0116044 .000142 .0757379
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟏 1.549024 3.922969 0 21.33
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟒 1.185366 2.840957 0 15.72
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟗 1.514878 3.194056 0 15.93
Table 4.2 Results from OLS regression of equation (1)
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝒋
(j=1)
(1)
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝒋
(j=4)
(2)
𝑹𝒆𝒕𝒖𝒓𝒏𝒊,𝒕,𝒕+𝒋
(j=9)
(3)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝒋 -.0000425
(0.951)
-.0006861
(0.179)
-.0002534
(0.397)
𝑺𝒊𝒛𝒆𝒊,𝒕 1.10e-14
(0.533)
1.28e-14
(0.170)
1.08e-14
(0.085)
𝑹𝒗𝒐𝒍𝒕𝒊,𝒕 .4456022
(0.171)
-.1001304
(0.551)
-.093734
(0.404)
𝑻𝒖𝒓𝒏𝒊,𝒕 .0013294
(0.996)
.0669253
(0.598)
.0168885
(0.844)
Intercept -.0107602
(0.121)
6.26e-06
(0.999)
.0015046
(0.524)
𝑨𝒅𝒋. 𝑹𝟐 -0.0274 0.0118 0.0286
𝑷𝒓𝒐𝒃 > 𝑭 0.5756 0.3624 0.2906
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Results from Table 7 suggested the estimate for short ratio of -.0000425 (p-
value = 0.951) -.0006861 (p-value = 0.179) and -.0002534 (p-value = 0.397) and since
these estimates are all negative and statistically close to zero, it means that 2 day, 5 days
and 10 days post announcement short selling activity is negatively related to post
announcement return indicated that short selling does add price pressure to acquiring
firm’s stock. These result can be explain by the idea that short sellers are momentum
traders who would trade on stocks with recent price decrease.
4.2 Significant difference between acquiring firm pre-announcement return and
post-announcement return
Table 4.3 P-values from Paired T-Test
2 days 5 days 10 days
BBL 0.7947 0.3883 0.4993
BJC 0.3400 0.6381 0.4484
CPALL 0.5081 0.5002 0.9121
WHA 0.7071 0.1114 0.8096
MAJOR 0.7460 0.7562 0.7990
PF 0.5000 0.2616 0.3034
BAY 0.1513 0.0908 0.4096
BDMS 0.0020 0.0077 0.4985
DTAC 0.6751 0.6645 0.2217
KKP 0.5000 0.1782 0.0252
LH 0.9905 0.7768 0.6800
MINT 0.4172 0.1687 0.0296
SCB 0.5010 0.6109 0.1664
SCC 0.8197 0.6453 0.8720
TCAP 0.9165 0.5076 0.3792
TMB 0.6503 0.1124 0.0267
TU 0.0509 0.8188 0.5317
UV 0.9555 0.1244 0.4029
VGI 0.6431 0.1193 0.7583
Statistical significance at the 0.05 level
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Our null hypothesis for this test in No statistically significant difference
between acquiring firm pre-announcement return and post-announcement return.
Results from table 8 indicated that for 10 days period, pre-announcement return of
KKP, MINT and TMB are higher than post-announcement return. For BDMS, pre-
announcement return are also higher that post-announcement for 2 days and 5 days
period. The results from our analysis suggested that 15 acquiring firm’s stock out of 19
shows no statistically significant difference between pre-announcement return and
post-announcement return.
4.3 Short selling during post announcement period
Table 4.4 Summary statistics of data used to test for significance short selling
Mean Std. Dev. Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟒 1.63011 3.626593 0 32.81
𝑨𝑵𝑵𝒕 .0492537 .216559 0 1
𝑹𝒆𝒕𝒊,𝒕,𝒕+𝟒 .0901426 .66576 -3.583333 4.99
𝑹𝒆𝒕𝒊,𝒕−𝟓,𝒕−𝟏 .0686297 .5373629 -2.9157 4.99
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕−𝟓,𝒕−𝟏 1.631991 3.479728 0 30.084
𝑷_𝒗𝒐𝒍𝒕𝒊,𝒕,𝒕+𝟒 .0256327 .0134076 -.0463846 .0972762
𝑷_𝒗𝒐𝒍𝒕𝒊,𝒕−𝟓,𝒕−𝟏 .025902 .0139447 -.0398855 .0938113
𝑻𝒖𝒓𝒏𝒊,𝒕−𝟓,𝒕−𝟏 .2031213 .2167267 0 2.68
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Table 4.5 Results from Fixed Effect Model
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.2945546
(0.523)
-.3896722
(0.392)
-.2203236
(0.622)
𝑹𝒆𝒕𝒊,𝒕,𝒕+𝟒 -.4968307
(0.002)
-.4284518
(0.006)
𝑹𝒆𝒕𝒊,𝒕−𝟓,𝒕−𝟏 -.751025
(0.000)
-.5616942
(0.004)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝒊,𝒕−𝟓,𝒕−𝟏 .2252358
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝒊,𝒕,𝒕+𝟒 -7.213889
(0.491)
𝑷_𝒗𝒐𝒍𝒕𝒊,𝒕−𝟓,𝒕−𝟏 8.024167
(0.466)
𝑻𝒖𝒓𝒏𝒊,𝒕−𝟓,𝒕−𝟏 -.0982667
(0.893)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.644617
(0.000)
1.745631
(0.000)
1.347579
(0.000)
𝑹𝟐 .0429 .0046 .9313
Prob > F .5229 .0002 .0000
Results from Table 10 are from Fixed Effect Model where column ( 2) shows
results when we include both contemporaneous return and past return and column ( 3)
are results after include all of the independent variables. ANN which is the interest
variable suggested a negative estimate and show P-values of 0.523, 0.392 and 0.622 for
column ( 1) , ( 2) and ( 3) respectively, These result leads us to accepted the null
hypothesis which indicated that there’s no significance short selling in acquiring firm's
stock during post announcement period.
4.3.1 Clinical Study Results
For our clinical study, we specifically conducted a test on all 19 acquiring
firm’ stocks to examine whether there’s significance short selling during post
announcement period by using 21 days period around the announcement.
Ref. code: 25605902042190NPJ
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Table 4.6 Summary Statistics of BBL
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑩𝑳,𝒕,𝒕+𝟒 1.806789 1.088224 .0075671 5.0775
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑩𝑩𝑳,𝒕,𝒕+𝟒 .0011716 .0054118 -.0106912 .0093023
𝑹𝒆𝒕𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 -.0003876 .004825 -.0078929 .0074096
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 2.796 1.801335 1.238 6.14
𝑷_𝒗𝒐𝒍𝒕𝑩𝑩𝑳,𝒕,𝒕+𝟒 .0152906 .0030146 .0100927 .0214477
𝑷_𝒗𝒐𝒍𝒕𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 .015892 .0027966 .0107678 .0203277
𝑻𝒖𝒓𝒏𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 .0021963 .0005754 .0008775 .0029179
Table 4.7 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑩𝑳,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -1.889183
(0.090)
-.8307554
(0.228)
-1.902589
(0.000)
𝑹𝒆𝒕𝑩𝑩𝑳,𝒕,𝒕+𝟒 -155.6591
(0.000)
-116.6333
(0.000)
𝑹𝒆𝒕𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 -29.6617
(0.320)
-76.91056
(0.065)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 . -.0500724
(0.730)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑩𝑳,𝒕,𝒕+𝟒 162.3131
(0.042)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 -10.28475
(0.900)
𝑻𝒖𝒓𝒏𝑩𝑩𝑳,𝒕−𝟓,𝒕−𝟏 -237.9694
(0.448)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.89675
(0.000)
2.017229
(0.000)
.3484588
(0.875)
𝑹𝟐 .1435 .7203 .9402
Prob > F .0904 .0001 .0000
For BBL, Results shows negative coefficient of interest variable ANN and P-
values are 0.090, 0.228 and 0.000 respectively. The result from column ( 3 ) after
included all independent variables leads us to rejected the null hypothesis which
Ref. code: 25605902042190NPJ
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indicated that there’s significance short selling in BBL during post announcement
period.
Table 4.8 Summary Statistics of BJC
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑱𝑪,𝒕,𝒕+𝟒 10.17369 8.356813 .0925 32.81
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑩𝑱𝑪,𝒕,𝒕+𝟒 -.0006622 .0048843 -.0082198 .0087667
𝑹𝒆𝒕𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 -.0014742 .0035457 -.006859 .0056528
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 10.97238 9.094389 .074 30.084
𝑷_𝒗𝒐𝒍𝒕𝑩𝑱𝑪,𝒕,𝒕+𝟒 .0232405 .0049608 .0168469 .0341464
𝑷_𝒗𝒐𝒍𝒕𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 .0231139 .0045474 .0175315 .0354697
𝑻𝒖𝒓𝒏𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 .0003253 .0001617 .0001956 .0007535
Table 4.9 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑱𝑪,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -6.298625
(0.476)
-7.70742
(0.395)
-.6035351
(0.904)
𝑹𝒆𝒕𝑩𝑱𝑪,𝒕,𝒕+𝟒 405.2126
(0.374)
395.8641
(0.286)
𝑹𝒆𝒕𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 853.6297
(0.185)
556.3799
(0.105)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 -.0390349
(0.887)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑱𝑪,𝒕,𝒕+𝟒 611.7854
(0.184)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 265.679
(0.613)
𝑻𝒖𝒓𝒏𝑩𝑱𝑪,𝒕−𝟓,𝒕−𝟏 41380.85
(0.021)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 10.47363
(0.000)
12.06747
(0.000)
-22.10899
(0.253)
𝑹𝟐 .0271 .1292 .8325
Prob > F .4762 .4902 .0004
Ref. code: 25605902042190NPJ
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For BJC, Results shows negative coefficient of interest variable ANN and P-
values are 0.476, 0.395 and 0.904 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in BJC during
post announcement period.
Table 4.10 Summary Statistics of CPALL
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑪𝑷𝑨𝑳𝑳,𝒕,𝒕+𝟒 10.43381 6.169602 .8475 17.705
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑪𝑷𝑨𝑳𝑳,𝒕,𝒕+𝟒 -.0032453 .0175375 -.0372864 .0313227
𝑹𝒆𝒕𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 -.0056507 .0134766 -.0310637 .0237761
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 7.530762 5.92927 1.314 17.704
𝑷_𝒗𝒐𝒍𝒕𝑪𝑷𝑨𝑳𝑳,𝒕,𝒕+𝟒 .0368751 .0114222 .0181466 .0595594
𝑷_𝒗𝒐𝒍𝒕𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 .0395308 .0086847 .0305865 .0557012
𝑻𝒖𝒓𝒏𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 .0047979 .0022811 .0017624 .0087273
Table 4.11 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑪𝑷𝑨𝑳𝑳,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 4.188125
(0.522)
-.5162319
(0.929)
2.695308
(0.373)
𝑹𝒆𝒕𝑪𝑷𝑨𝑳𝑳,𝒕,𝒕+𝟒 228.7116
(0.022)
-43.53804
(0.546)
𝑹𝒆𝒕𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 354.1357
(0.010)
73.38304
(0.437)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 .8019241
(0.006)
𝑷_𝒗𝒐𝒍𝒕𝑪𝑷𝑨𝑳𝑳,𝒕,𝒕+𝟒 -256.3475
(0.016)
𝑷_𝒗𝒐𝒍𝒕𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 241.9919
(0.299)
𝑻𝒖𝒓𝒏𝑪𝑷𝑨𝑳𝑳,𝒕−𝟓,𝒕−𝟏 205.8517
(0.806)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 10.23438
(0.000)
13.20175
(0.000)
3.438772
(0.722)
𝑹𝟐 .0219 .3631 .8908
Prob > F .5216 .0485 .0000
Ref. code: 25605902042190NPJ
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For CPALL, Results shows both positive and negative coefficient of interest
variable ANN and P-values are 0.522, 0.929 and 0.373 respectively. These result leads
us to accepted the null hypothesis which indicated that there’s no significance short
selling in CPALL during post announcement period.
Table 4.12 Summary Statistics of WHA
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑾𝑯𝑨,𝒕,𝒕+𝟒 .7495833 1.011106 0 3.775
𝑨𝑵𝑵𝒕 .047619 .2155403 0 1
𝑹𝒆𝒕𝑾𝑯𝑨,𝒕,𝒕+𝟒 -.002271 .0107331 -.021604 .0222829
𝑹𝒆𝒕𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 -.0048367 .0091301 -.0211265 .0131151
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 .9344762 1.40189 0 5.596
𝑷_𝒗𝒐𝒍𝒕𝑾𝑯𝑨,𝒕,𝒕+𝟒 .0372098 .0077261 .0233459 .0579049
𝑷_𝒗𝒐𝒍𝒕𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 .0361988 .0089174 .0187584 .058168
𝑻𝒖𝒓𝒏𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 .003939 .0030276 .0011096 .0124937
Table 4.13 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑾𝑯𝑨,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.25025
(0.737)
-.2036268
(0.800)
.3011438
(0.584)
𝑹𝒆𝒕𝑾𝑯𝑨,𝒕,𝒕+𝟒 5.543111
(0.745)
20.60893
(0.119)
𝑹𝒆𝒕𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 -12.3152
(0.523)
-10.20421
(0.543)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 .0298024
(0.832)
𝑷_𝒗𝒐𝒍𝒕𝑾𝑯𝑨,𝒕,𝒕+𝟒 85.66705
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 56.14806
(0.009)
𝑻𝒖𝒓𝒏𝑾𝑯𝑨,𝒕−𝟓,𝒕−𝟏 -23.8615
(0.737)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 .7615
(0.000)
.7123034
(0.001)
-4.421314
(0.000)
𝑹𝟐 .0028 .0229 .6406
Prob > F .7372 .8276 .0000
Ref. code: 25605902042190NPJ
34
For WHA, Results shows negative coefficient of interest variable ANN and P-
values are 0.737, 0.800 and 0.584 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in WHA
during post announcement period.
Table 4.14 Summary Statistics of MAJOR
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑨𝑱𝑶𝑹,𝒕,𝒕+𝟒 .0392857 .0882421 0 .3225
𝑨𝑵𝑵𝒕 .047619 .2155403 0 1
𝑹𝒆𝒕𝑴𝑨𝑱𝑶𝑹,𝒕,𝒕+𝟒 -.0042388 .0089362 -.0262838 .0104348
𝑹𝒆𝒕𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 -.0014478 .006332 -.0168866 .0125788
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 .0392857 .0801265 0 .262
𝑷_𝒗𝒐𝒍𝒕𝑴𝑨𝑱𝑶𝑹,𝒕,𝒕+𝟒 .0255467 .0100416 .0111668 .0578607
𝑷_𝒗𝒐𝒍𝒕𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 .0246228 .0094181 .0133229 .0534314
𝑻𝒖𝒓𝒏𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 .1748095 .1035554 .014 .334
Table 4.15 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑨𝑱𝑶𝑹,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 .006
(0.927)
.0137432
(0.835)
.0299256
(0.644)
𝑹𝒆𝒕𝑴𝑨𝑱𝑶𝑹,𝒕,𝒕+𝟒 -2.412565
(0.193)
-.7273982
(0.725)
𝑹𝒆𝒕𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 -1.472983
(0.570)
.9861871
(0.725)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 .0723933
(0.733)
𝑷_𝒗𝒐𝒍𝒕𝑴𝑨𝑱𝑶𝑹,𝒕,𝒕+𝟒 .5373783
(0.719)
𝑷_𝒗𝒐𝒍𝒕𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 1.657017
(0.303)
𝑻𝒖𝒓𝒏𝑴𝑨𝑱𝑶𝑹,𝒕−𝟓,𝒕−𝟏 .4117147
(0.010)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 .039
(0.009)
.0262724
(0.141)
-.0931391
(0.175)
𝑹𝟐 .0002 .0445 .2821
Prob > F .9266 .6250 .0987
Ref. code: 25605902042190NPJ
35
For MAJOR, Results shows positive coefficient of interest variable ANN and
P-values are 0.927, 0.835 and 0.644 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in MAJOR
during post announcement period.
Table 4.16 Summary Statistics of PF
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑷𝑭,𝒕,𝒕+𝟒 .0250504 .1744153 0 2.7575
𝑨𝑵𝑵𝒕 .0012594 .0354719 0 1
𝑹𝒆𝒕𝑷𝑭,𝒕,𝒕+𝟒 -.0001728 .0149544 -.2085123 .0828803
𝑹𝒆𝒕𝑷𝑭,𝒕−𝟓,𝒕−𝟏 -.000138 .0135453 -.1677982 .0729206
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑷𝑭,𝒕−𝟓,𝒕−𝟏 .0250504 .1612921 0 2.286
𝑷_𝒗𝒐𝒍𝒕𝑷𝑭,𝒕,𝒕+𝟒 .0295963 .0151683 .0071266 .1381607
𝑷_𝒗𝒐𝒍𝒕𝑷𝑭,𝒕−𝟓,𝒕−𝟏 .029643 .0144244 .0072073 .1217286
𝑻𝒖𝒓𝒏𝑷𝑭,𝒕−𝟓,𝒕−𝟏 .6180998 1.32587 .01 15.042
Table 4.17 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑷𝑭,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.025082
(0.774)
-.0240563
(0.782)
-.0142935
(0.868)
𝑹𝒆𝒕𝑷𝑭,𝒕,𝒕+𝟒 -.7242707
(0.000)
-.6976706
(0.001)
𝑹𝒆𝒕𝑷𝑭,𝒕−𝟓,𝒕−𝟏 -.1055253
(0.644)
-.1788019
(0.456)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑷𝑭,𝒕−𝟓,𝒕−𝟏 .1760895
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑷𝑭,𝒕,𝒕+𝟒 .0992872
(0.665)
𝑷_𝒗𝒐𝒍𝒕𝑷𝑭,𝒕−𝟓,𝒕−𝟏 .1383994
(0.600)
𝑻𝒖𝒓𝒏𝑷𝑭,𝒕−𝟓,𝒕−𝟏 .0058675
(0.036)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 .025082
(0.000)
.0249409
(0.000)
.0098442
(0.224)
𝑹𝟐 .0000 .0040 .0343
Prob > F .7738 .0054 .0000
Ref. code: 25605902042190NPJ
36
For PF, Results shows negative coefficient of interest variable ANN and P-
values are 0.774, 0.782 and 0.868 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in PF during
post announcement period.
Table 4.18 Summary Statistics of BAY
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑨𝒀,𝒕,𝒕+𝟒 6.8725 6.929664 0 22.495
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑩𝑨𝒀,𝒕,𝒕+𝟒 .001613 .0074434 -.0122756 .0169791
𝑹𝒆𝒕𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 -.0008608 .0046992 -.0107243 .0088682
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 7.561048 5.144827 1.754 17.996
𝑷_𝒗𝒐𝒍𝒕𝑩𝑨𝒀,𝒕,𝒕+𝟒 .019213 .006901 .0109468 .0332053
𝑷_𝒗𝒐𝒍𝒕𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 .0188642 .0062102 .011656 .0322785
𝑻𝒖𝒓𝒏𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 .2620952 .1093334 .094 .418
Table 4.19 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑨𝒀,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -4.869375
(0.507)
-6.159065
(0.420)
2.864159
(0.582)
𝑹𝒆𝒕𝑩𝑨𝒀,𝒕,𝒕+𝟒 -193.0663
(0.409)
-368.1117
(0.059)
𝑹𝒆𝒕𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 369.5696
(0.333)
-115.5602
(0.736)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 -.1223383
(0.764)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑨𝒀,𝒕,𝒕+𝟒 537.4062
(0.127)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 -945.4898
(0.001)
𝑻𝒖𝒓𝒏𝑩𝑨𝒀,𝒕−𝟓,𝒕−𝟏 79.6642
(0.007)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 7.104375
(0.000)
7.795352
(0.000)
-5.213464
(0.671)
𝑹𝟐 0.0235 0.1665 0.7578
Prob > F 0.5069 .3641 .0032
Ref. code: 25605902042190NPJ
37
For BAY, Results shows negative coefficient of interest variable ANN and P-
values are 0.507, 0.420 and 0.582 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in BAY during
post announcement period.
Table 4.20 Summary Statistics of BDMS
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑫𝑴𝑺,𝒕,𝒕+𝟒 .2709821 .5490699 0 2.325
𝑨𝑵𝑵𝒕 .047619 .2142379 0 1
𝑹𝒆𝒕𝑩𝑫𝑴𝑺,𝒕,𝒕+𝟒 -.0022679 .0083069 -.0206398 .0202665
𝑹𝒆𝒕𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 -.001458 .0076864 -.018851 .0211379
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 .2976429 .5502017 0 2.218
𝑷_𝒗𝒐𝒍𝒕𝑩𝑫𝑴𝑺,𝒕,𝒕+𝟒 .021743 .0069703 .0094127 .0418803
𝑷_𝒗𝒐𝒍𝒕𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 .0225279 .008605 .0105605 .0580117
𝑻𝒖𝒓𝒏𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 .1244286 .0883335 .016 .338
Table 4.21 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑫𝑴𝑺,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 .0613125
(0.829)
.0670763
(0.813)
.0144214
(0.958)
𝑹𝒆𝒕𝑩𝑫𝑴𝑺,𝒕,𝒕+𝟒 -9.374569
(0.222)
-9.483159
(0.236)
𝑹𝒆𝒕𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 -10.73711
(0.196)
-8.787389
(0.275)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 .1286659
(0.241)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑫𝑴𝑺,𝒕,𝒕+𝟒 9.53103
(0.349)
𝑷_𝒗𝒐𝒍𝒕𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 -22.57393
(0.005)
𝑻𝒖𝒓𝒏𝑩𝑫𝑴𝑺,𝒕−𝟓,𝒕−𝟏 .681009
(0.337)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 .2680625
(0.000)
.2308729
(0.001)
.4142527
(0.081)
𝑹𝟐 .0006 .0307 .1489
Prob > F .8290 .4729 .0813
Ref. code: 25605902042190NPJ
38
For BDMS, Results shows negative coefficient of interest variable ANN and P-
values are 0.829, 0.813 and 0.958 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in BDMS
during post announcement period.
Table 4.22 Summary Statistics of DTAC
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑫𝑻𝑨𝑪,𝒕,𝒕+𝟒 2.209338 2.774868 0 22.42
𝑨𝑵𝑵𝒕 .0004296 .0207257 0 1
𝑹𝒆𝒕𝑫𝑻𝑨𝑪,𝒕,𝒕+𝟒 .0003027 .0134099 -.1282964 .0988771
𝑹𝒆𝒕𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 .0002865 .0118823 -.0936281 .0972835
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 2.207545 2.64257 0 21.262
𝑷_𝒗𝒐𝒍𝒕𝑫𝑻𝑨𝑪,𝒕,𝒕+𝟒 .0183327 .0179487 0 .1393773
𝑷_𝒗𝒐𝒍𝒕𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 .0183852 .0177002 0 .1201019
𝑻𝒖𝒓𝒏𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 .2974175 .3403237 .024 3.486
Table 4.23 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑫𝑻𝑨𝑪,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -2.210288
(0.426)
-3.459447
(0.201)
-1.348369
(0.567)
𝑹𝒆𝒕𝑫𝑻𝑨𝑪,𝒕,𝒕+𝟒 -39.14387
(0.000)
-29.16553
(0.000)
𝑹𝒆𝒕𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 -35.57482
(0.000)
-15.68481
(0.000)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 .4120768
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑫𝑻𝑨𝑪,𝒕,𝒕+𝟒 -23.8492
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 -4.60568
(0.373)
𝑻𝒖𝒓𝒏𝑫𝑻𝑨𝑪,𝒕−𝟓,𝒕−𝟏 .1186837
(0.414)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 2.210288
(0.000)
2.232866
(0.000)
1.80016
(0.000)
𝑹𝟐 .0003 .0537 .2887
Prob > F .4259 .0000 .0000
Ref. code: 25605902042190NPJ
39
For DTAC, Results shows negative coefficient of interest variable ANN and P-
values are 0.426, 0.201 and 0.567 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in DTAC
during post announcement period.
Table 4.24 Summary Statistics of KKP
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑲𝑲𝑷,𝒕,𝒕+𝟒 1.63131 1.587765 .0375 5.265
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑲𝑲𝑷,𝒕,𝒕+𝟒 .0011209 .0072029 -.0104812 .0137226
𝑹𝒆𝒕𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 .0033757 .0077476 -.008385 .0163711
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 1.251143 1.503112 .058 4.212
𝑷_𝒗𝒐𝒍𝒕𝑲𝑲𝑷,𝒕,𝒕+𝟒 .0202554 .0047299 .0123841 .0287794
𝑷_𝒗𝒐𝒍𝒕𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 .0225695 .004146 .0159069 .0308329
𝑻𝒖𝒓𝒏𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 .004578 .0022168 .0022547 .009644
Table 4.25 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑲𝑲𝑷,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 2.418875
(0.141)
2.591755
(0.148)
-.2689448
(0.791)
𝑹𝒆𝒕𝑲𝑲𝑷,𝒕,𝒕+𝟒 20.76561
(0.693)
-96.22352
(0.149)
𝑹𝒆𝒕𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 -12.44689
(0.801)
131.6622
(0.073)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 . -.8750339
(0.003)
𝑷_𝒗𝒐𝒍𝒕𝑲𝑲𝑷,𝒕,𝒕+𝟒 -70.58865
(0.337)
𝑷_𝒗𝒐𝒍𝒕𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 223.6747
(0.099)
𝑻𝒖𝒓𝒏𝑲𝑲𝑷,𝒕−𝟓,𝒕−𝟏 -983.2926
(0.000)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.516125
(0.000)
1.526634
(0.001)
3.285428
(0.342)
𝑹𝟐 .1105 .1204 .8161
Prob > F .1409 .5236 .0006
Ref. code: 25605902042190NPJ
40
For KKP, Results shows positive coefficient of interest variable ANN and P-
values are 0.141, 0.148 and 0.791 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in KKP during
post announcement period.
Table 4.26 Summary Statistics of LH
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑳𝑯,𝒕,𝒕+𝟒 1.453373 1.247453 0 3.9425
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑳𝑯,𝒕,𝒕+𝟒 -.0019768 .0082704 -.0164034 .0153076
𝑹𝒆𝒕𝑳𝑯,𝒕−𝟓,𝒕−𝟏 -.0011235 .0060162 -.0152504 .0103265
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑳𝑯,𝒕−𝟓,𝒕−𝟏 1.459905 1.145954 0 3.416
𝑷_𝒗𝒐𝒍𝒕𝑳𝑯,𝒕,𝒕+𝟒 .0311382 .0046434 .0182226 .0371413
𝑷_𝒗𝒐𝒍𝒕𝑳𝑯,𝒕−𝟓,𝒕−𝟏 .027054 .0077166 .0135094 .0356424
𝑻𝒖𝒓𝒏𝑳𝑯,𝒕−𝟓,𝒕−𝟏 .1805476 .0617948 0 .264
Table 4.27 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑳𝑯,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -1.526042
(0.242)
- 1.259945
(0.186)
-.0425661
(0.986)
𝑹𝒆𝒕𝑳𝑯,𝒕,𝒕+𝟒 -39.71073
(0.139)
--38.51608
(0.370)
𝑹𝒆𝒕𝑳𝑯,𝒕−𝟓,𝒕−𝟏 -155.6957
(0.000)
-147.3778
(0.006)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑳𝑯,𝒕−𝟓,𝒕−𝟏 -.0745228
(0.897)
𝑷_𝒗𝒐𝒍𝒕𝑳𝑯,𝒕,𝒕+𝟒 -4.693573
(0.939)
𝑷_𝒗𝒐𝒍𝒕𝑳𝑯,𝒕−𝟓,𝒕−𝟏 -22.86777
(0.795)
𝑻𝒖𝒓𝒏𝑳𝑯,𝒕−𝟓,𝒕−𝟏 6.920583
(0.433)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.526042
(0.000)
1.259945
(0.000)
.8377957
(0.716)
𝑹𝟐 .0713 .5684 .5904
Prob > F .2421 .0021 .0596
Ref. code: 25605902042190NPJ
41
For LH, Results shows negative coefficient of interest variable ANN and P-
values are 0.242, 0.186 and 0.986 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in LH during
post announcement period.
Table 4.28 Summary Statistics of MINT
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑰𝑵𝑻,𝒕,𝒕+𝟒 1.050833 1.233643 0 4.0975
𝑨𝑵𝑵𝒕 .047619 .2155403 0 1
𝑹𝒆𝒕𝑴𝑰𝑵𝑻,𝒕,𝒕+𝟒 -.0011334 .0185521 -.0446721 .0412909
𝑹𝒆𝒕𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 .0009881 .0150899 -.0294086 .0348315
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 1.034238 1.12616 0 3.838
𝑷_𝒗𝒐𝒍𝒕𝑴𝑰𝑵𝑻,𝒕,𝒕+𝟒 .0419225 .016109 .0186507 .0676499
𝑷_𝒗𝒐𝒍𝒕𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 .0406626 .0143205 .0199206 .0687156
𝑻𝒖𝒓𝒏𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 .3097619 .0985358 .11 .49
Table 4.29 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑰𝑵𝑻,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.2305625
(0.800)
.1401447
(0.871)
.189744
(0.828)
𝑹𝒆𝒕𝑴𝑰𝑵𝑻,𝒕,𝒕+𝟒 -3.094739
(0.757)
-1.570985
(0.879)
𝑹𝒆𝒕𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 -33.77535
(0.009)
-36.83535
(0.009)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 -.4612168
(0.062)
𝑷_𝒗𝒐𝒍𝒕𝑴𝑰𝑵𝑻,𝒕,𝒕+𝟒 4.991757
(0.082)
𝑷_𝒗𝒐𝒍𝒕𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 10.60544
(0.509)
𝑻𝒖𝒓𝒏𝑴𝑰𝑵𝑻,𝒕−𝟓,𝒕−𝟏 26.53641
(0.330)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.061813
(0.000)
1.074027
(0.000)
2.49368
(0.006)
𝑹𝟐 .0016 .1756 .2688
Prob > F .8000 .0593 .1225
Ref. code: 25605902042190NPJ
42
For MINT, Results shows negative coefficient of interest variable ANN and P-
values are 0.800, 0.871 and 0.828 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in MINT
during post announcement period.
Table 4.30 Summary Statistics of SCB
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑩,𝒕,𝒕+𝟒 1.501769 2.453464 0 10.055
𝑨𝑵𝑵𝒕 .047619 .2136869 0 1
𝑹𝒆𝒕𝑺𝑪𝑩,𝒕,𝒕+𝟒 .4141553 1.376622 -3.583333 4.99
𝑹𝒆𝒕𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 .3168651 1.115007 -2.9175 4.99
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 1.456748 2.308152 0 9.886
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑩,𝒕,𝒕+𝟒 .0234286 .0082189 .0116517 .0484572
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 .0234374 .0079598 .0120793 .0442703
𝑻𝒖𝒓𝒏𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 .3542313 .1670784 .118 .87
Table 4.31 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑩,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.0614821
(0.949)
-.5109675
(0.568)
-.0377319
(0.938)
𝑹𝒆𝒕𝑺𝑪𝑩,𝒕,𝒕+𝟒 -.498324
(0.001)
-.3485612
(0.000)
𝑹𝒆𝒕𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 -.7522944
(0.000)
.0354522
(0.735)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 .6457138
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑩,𝒕,𝒕+𝟒 36.79483
(0.011)
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 83.20328
(0.001)
𝑻𝒖𝒓𝒏𝑺𝑪𝑩,𝒕−𝟓,𝒕−𝟏 -4.129945
(0.000)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.504696
(0.000)
1.97086
(0.000)
-.6531186
(0.098)
𝑹𝟐 .0000 .1460 .7604
Prob > F .9487 .0000 .0000
Ref. code: 25605902042190NPJ
43
For SCB, Results shows negative coefficient of interest variable ANN and P-
values are 0.949, 0.568 and 0.938 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in SCB during
post announcement period.
Table 4.32 Summary Statistics of SCC
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑪,𝒕,𝒕+𝟒 1.058312 1.622247 0 7.4525
𝑨𝑵𝑵𝒕 .0509554 .2206104 0 1
𝑹𝒆𝒕𝑺𝑪𝑪,𝒕,𝒕+𝟒 .0014587 .0071849 -.016702 .0235931
𝑹𝒆𝒕𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 .0035935 4.98e-16 .0035935 .0035935
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 1.030994 1.378421 0 4.882
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑪,𝒕,𝒕+𝟒 .0197596 .0066532 .008547 .0449343
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 .0199197 .0071275 .0100149 .0427435
𝑻𝒖𝒓𝒏𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 .2380382 .163303 .066 .984
Table 4.33 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑪,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.6979383
(0.237)
-.8440222
(0.146)
-.8772597
(0.064)
𝑹𝒆𝒕𝑺𝑪𝑪,𝒕,𝒕+𝟒 -50.33885
(0.005)
-36.36182
(0.014)
𝑹𝒆𝒕𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 0 0
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 .6482945
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑪,𝒕,𝒕+𝟒 -10.91278
(0.644)
𝑷_𝒗𝒐𝒍𝒕𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 -4.066999
(0.866)
𝑻𝒖𝒓𝒏𝑺𝑪𝑪,𝒕−𝟓,𝒕−𝟏 .0121605
(0.991)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.093876
(0.000)
1.174749
(0.000)
.7814171
(0.117)
𝑹𝟐 .0090 .0583 .3926
Prob > F .2370 .0098 .0000
Ref. code: 25605902042190NPJ
44
For SCC, Results shows negative coefficient of interest variable ANN and P-
values are 0.237, 0.146 and 0.064 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in SCC during
post announcement period.
Table 4.34 Summary Statistics of TCAP
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑪𝑨𝑷,𝒕,𝒕+𝟒 .8146757 1.864149 0 20.25
𝑨𝑵𝑵𝒕 .0003149 .0177443 0 1
𝑹𝒆𝒕𝑻𝑪𝑨𝑷,𝒕,𝒕+𝟒 .000508 .0107054 -.075984 .0925555
𝑹𝒆𝒕𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 .0005082 .0094683 -.0700464 .0796782
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 .8146757 1.773686 0 22.092
𝑷_𝒗𝒐𝒍𝒕𝑻𝑪𝑨𝑷,𝒕,𝒕+𝟒 .0247149 .0111823 .005682 .1706169
𝑷_𝒗𝒐𝒍𝒕𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 .0247277 .010728 .0075307 .1733357
𝑻𝒖𝒓𝒏𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 .5127056 .5153006 .04 7.134
Table 4.35 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑪𝑨𝑷,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.8149323
(0.662)
-.7644583
(0.681)
-.4268436
(0.797)
𝑹𝒆𝒕𝑻𝑪𝑨𝑷,𝒕,𝒕+𝟒 -8.590443
(0.005)
-10.37249
(0.000)
𝑹𝒆𝒕𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 -9.71374
(0.005)
-5.202188
(0.110)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 .4749739
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑻𝑪𝑨𝑷,𝒕,𝒕+𝟒 -3.851231
(0.215)
𝑷_𝒗𝒐𝒍𝒕𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 -1.496382
(0.663)
𝑻𝒖𝒓𝒏𝑻𝑪𝑨𝑷,𝒕−𝟓,𝒕−𝟏 -.0298628
(0.650)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 .8149323
(0.000)
.8242174
(0.000)
.5832696
(0.000)
𝑹𝟐 .0001 .0047 .2120
Prob > F .6621 .0019 .0000
Ref. code: 25605902042190NPJ
45
For TCAP, Results shows negative coefficient of interest variable ANN and P-
values are 0.662, 0.681 and 0.797 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in TCAP
during post announcement period.
Table 4.36 Summary Statistics of TMB
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑴𝑩,𝒕,𝒕+𝟒 .0025 .005244 0 .0175
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑻𝑴𝑩,𝒕,𝒕+𝟒 -.0032462 .013362 -.0243163 .0182697
𝑹𝒆𝒕𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 -.0074468 .008304 -.0224233 .004874
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 .0009524 .0013593 0 .004
𝑷_𝒗𝒐𝒍𝒕𝑻𝑴𝑩,𝒕,𝒕+𝟒 .0308712 .0075729 .0199935 .0472165
𝑷_𝒗𝒐𝒍𝒕𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 .027329 .0062241 .0195444 .0410643
𝑻𝒖𝒓𝒏𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 .352 .082314 .272 .588
Table 4.37 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑴𝑩,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.002625
(0.637)
-.0026878
(0.611)
.0003071
(0.900)
𝑹𝒆𝒕𝑻𝑴𝑩,𝒕,𝒕+𝟒 .0802036
(0.405)
-.0601449
(0.300)
𝑹𝒆𝒕𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 .2480413
(0.113)
-.4849169
(0.026)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 -1.882597
(0.016)
𝑷_𝒗𝒐𝒍𝒕𝑻𝑴𝑩,𝒕,𝒕+𝟒 .1773987
(0.107)
𝑷_𝒗𝒐𝒍𝒕𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 -.6040062
(0.017)
𝑻𝒖𝒓𝒏𝑻𝑴𝑩,𝒕−𝟓,𝒕−𝟏 .0642845
(0.000)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 .002625
(0.041)
.0047355
(0.004)
-.0111257
(0.037)
𝑹𝟐 .0119 .2787 .8889
Prob > F .6374 .1266 .0000
Ref. code: 25605902042190NPJ
46
For TMB, Results shows negative coefficient of interest variable ANN and P-
values are 0.637, 0.611 and 0.900 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in TMB during
post announcement period.
Table 4.38 Summary Statistics of TU
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑼,𝒕,𝒕+𝟒 2.762143 1.621043 .3625 5.995
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑻𝑼,𝒕,𝒕+𝟒 -.0045208 .0192212 -.0463846 .0274358
𝑹𝒆𝒕𝑻𝑼,𝒕−𝟓,𝒕−𝟏 -.0051063 .016725 -.0398855 .0270507
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑼,𝒕−𝟓,𝒕−𝟏 2.809524 1.413701 .668 5.374
𝑷_𝒗𝒐𝒍𝒕𝑻𝑼,𝒕,𝒕+𝟒 -.0045208 .0192212 -.0463846 .0274358
𝑷_𝒗𝒐𝒍𝒕𝑻𝑼,𝒕−𝟓,𝒕−𝟏 -.0051063 .016725 -.0398855 .0270507
𝑻𝒖𝒓𝒏𝑻𝑼,𝒕−𝟓,𝒕−𝟏 .0025207 .0007611 .0016176 .004132
Table 4.39 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑼,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.293625
(0.865)
.110325
(0.903)
.1773726
(0.853)
𝑹𝒆𝒕𝑻𝑼,𝒕,𝒕+𝟒 23.83096
(0.039)
20.1275
(0.311)
𝑹𝒆𝒕𝑻𝑼,𝒕−𝟓,𝒕−𝟏 -73.3157
(0.000)
-68.02263
(0.000)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑻𝑼,𝒕−𝟓,𝒕−𝟏 -.0978603
(0.578)
𝑷_𝒗𝒐𝒍𝒕𝑻𝑼,𝒕,𝒕+𝟒 0
𝑷_𝒗𝒐𝒍𝒕𝑻𝑼,𝒕−𝟓,𝒕−𝟏 0
𝑻𝒖𝒓𝒏𝑻𝑼,𝒕−𝟓,𝒕−𝟏 185.8911
(0.708)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 2.776125
(0.000)
2.490251
(0.000)
2.303705
(0.094)
𝑹𝟐 .0016 .7859 .7912
Prob > F .8649 .0000 .0001
Ref. code: 25605902042190NPJ
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For TU, Results shows negative and positive coefficient of interest variable
ANN and P-values are 0.865, 0.903 and 0.853 respectively. These result leads us to
accepted the null hypothesis which indicated that there’s no significance short selling
in TU during post announcement period.
Table 4.40 Summary Statistics of UV
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑼𝑽,𝒕,𝒕+𝟒 .0584635 .3269044 0 5.63
𝑨𝑵𝑵𝒕 .0003149 .0177443 0 1
𝑹𝒆𝒕𝑼𝑽,𝒕,𝒕+𝟒 .0006408 .0167445 -.0732273 .1468535
𝑹𝒆𝒕𝑼𝑽,𝒕−𝟓,𝒕−𝟏 .0006702 .01511665 -.0713045 .1438979
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑼𝑽,𝒕−𝟓,𝒕−𝟏 .0584635 .3043434 0 4.504
𝑷_𝒗𝒐𝒍𝒕𝑼𝑽,𝒕,𝒕+𝟒 .0357955 .019823 0 .159576
𝑷_𝒗𝒐𝒍𝒕𝑼𝑽,𝒕−𝟓,𝒕−𝟏 .0358521 .0188897 0 .1468659
𝑻𝒖𝒓𝒏𝑼𝑽,𝒕−𝟓,𝒕−𝟏 .0073031 .0144769 0 .1540351
Table 4.41 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑼𝑽,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.0584819
(0.858)
-.0566473
(0.862)
-.0382689
(0.904)
𝑹𝒆𝒕𝑼𝑽,𝒕,𝒕+𝟒 -.6990635
(0.044)
-.9644726
(0.005)
𝑹𝒆𝒕𝑼𝑽,𝒕−𝟓,𝒕−𝟏 -.9359887
(0.015)
-.8045942
(0.052)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑼𝑽,𝒕−𝟓,𝒕−𝟏 .2652071
(0.000)
𝑷_𝒗𝒐𝒍𝒕𝑼𝑽,𝒕,𝒕+𝟒 .2905299
(0.377)
𝑷_𝒗𝒐𝒍𝒕𝑼𝑽,𝒕−𝟓,𝒕−𝟏 .4085193
(0.293)
𝑻𝒖𝒓𝒏𝑼𝑽,𝒕−𝟓,𝒕−𝟏 -.1365724
(0.795)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 .0584819
(0.000)
.0595565
(0.000)
.0200793
(0.166)
𝑹𝟐 .0000 .0034 .0655
Prob > F .8581 .0124 .0000
Ref. code: 25605902042190NPJ
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For UV, Results shows negative coefficient of interest variable ANN and P-
values are 0.858, 0.862 and 0.904 respectively. These result leads us to accepted the
null hypothesis which indicated that there’s no significance short selling in UV during
post announcement period.
Table 4.42 Summary Statistics of VGI
Mean Std. Dev Min Max
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑽𝑮𝑰,𝒕,𝒕+𝟒 1.596429 1.621842 0 5.64
𝑨𝑵𝑵𝒕 .047619 .2182179 0 1
𝑹𝒆𝒕𝑽𝑮𝑰,𝒕,𝒕+𝟒 .0078152 .0109696 -.0070326 .0321502
𝑹𝒆𝒕𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 .0081573 .0091657 -.0061702 .0257202
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 2.282762 1.556685 .282 4.974
𝑷_𝒗𝒐𝒍𝒕𝑽𝑮𝑰,𝒕,𝒕+𝟒 .0278919 .0108064 .0098986 .0420852
𝑷_𝒗𝒐𝒍𝒕𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 .0243563 .0087845 .0097046 .0393739
𝑻𝒖𝒓𝒏𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 .0026205 .0028224 .0002901 .0080336
Table 4.43 Results from OLS regression
𝒔𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑽𝑮𝑰,𝒕,𝒕+𝟒
(1) (2) (3)
𝑨𝑵𝑵𝒕 -.29025
(0.867)
.8533093
(0.571)
.3332697
(0.747)
𝑹𝒆𝒕𝑽𝑮𝑰,𝒕,𝒕+𝟒 -30.30538
(0.311)
-44.88303
(0.158)
𝑹𝒆𝒕𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 -109.6838
(0.005)
-12.53628
(0.723)
𝑺𝒉𝒐𝒓𝒕𝒓𝒂𝒕𝒊𝒐𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 -.3116966
(0.300)
𝑷_𝒗𝒐𝒍𝒕𝑽𝑮𝑰,𝒕,𝒕+𝟒 -86.93622
(0.006)
𝑷_𝒗𝒐𝒍𝒕𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 -53.81604
(0.243)
𝑻𝒖𝒓𝒏𝑽𝑮𝑰,𝒕−𝟓,𝒕−𝟏 -300.7071
(0.116)
𝑰𝒏𝒕𝒆𝒓𝒄𝒆𝒑𝒕 1.61025
(0.000)
2.687365
(0.000)
7.268705
(0.002)
𝑹𝟐 .0015 .3878 .8028
Prob > F .8665 .0356 .0010
Ref. code: 25605902042190NPJ
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For VGI, Results from shows negative and positive coefficient of interest
variable ANN and P-values are 0.867, 0.571 and 0.747 respectively. These result leads
us to accepted the null hypothesis which indicated that there’s no significance short
selling in VGI during post announcement period.
Ref. code: 25605902042190NPJ
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CHAPTER 5
CONCLUSION
During an acquisition, stock price of a target company tends to increase to create
an incentive for the target firm’s shareholders to approve the acquisition and sell their
shares to the acquiring firm. For acquiring firm stocks, their price tends to fall since
they have to pay premium in order to acquire the target company which required a great
amount of money and their stock might suffer from this process. Beside this, there are
also several explanations that would help explain the fall of the acquiring firm’s stock
during an acquisition. For this study, by using tender offer data in Thailand over a
period of 2004 to 2016 in total, of 41 tender offers with 19 acquiring firms, we aimed
to find whether short selling activity following the acquisition announcement through
the tender offer add price pressure or drives the negative post announcement return on
acquiring firm’ s stock by using a short ratio as our measure of shorting activity. Our
results suggested that post announcement short sale drives the negative post
announcement return or add price pressure to the acquiring firm’s stock which means
that short selling activity is negatively related to post announcement return. These
results are consistent with previous studies, Mitchell, Pulvino, and Stafford (2004) or
MPS who suggested that excess demand curves are downward sloping which leads to
an increase in the supply of shares caused by short selling will add pressure to
equilibrium stock prices. Furthermore, we examined each acquiring firm’ stock return
whether there’s a significant difference between pre-announcement and post-announce
return. Our results suggested pre-announcement return for BDMS, KKP, MINT and
TMB are greater than post-announcement return while the rest of the acquiring firm’s
stock shows no statistically significant difference between pre-announcement and post-
announcement return
We also test whether there’s significance short selling in acquiring firm's stock
during post announcement period by using short ratio as our measure of shorting
activity, the result from Fixed Effect Model indicated that there’ s no significant short
selling during post announcement period. Furthermore, we also conduct a clinical study
to test this hypothesis on each of the acquiring firm stock in total, of 19 stocks by using
Ref. code: 25605902042190NPJ
51
21 days period around the announcement. Out of 19 acquiring firm’s stock, only BBL
shows significant short selling around the announcement suggested that during the
period of BBL acquisition of BLS, investors or merger arbitragers seek to make profit
from this news by shorting BBL stock.
The regulations of short sale in Thailand may play a part for this insignificance
of short selling activity since short sale regulations stated that “a member may conduct
a short sale only the securities specified by the Exchange. This is except in the case of
a short sale by a market maker whereby short sales of the securities listed as that market
maker's responsibility may also be made.” Furthermore, it also has a rules for
prohibiting short sale from The Stock Exchange of Thailand as follow (www.set.or.th):
1. The stock exchange of Thailand may prescribe the maximum volume of any security
which can be sold short and has not yet been covered. If the short sale is more than the
prescribed volume, the Exchange may prohibit short sales on the business day following
the date the short sale is more than the prescribed volume, until such volumes are
reduced. 2. The Exchange may temporarily prohibit the short sale of any security if the
Exchange considers the continuance of short sales of such a security may cause risk or
damage to securities trading conditions at the Exchange 3. The Exchange may
temporarily prohibit a member from short selling or order the member to purchase in
return securities which have been sold short if the Exchange considers that such a
member has any security under short sale which has not been purchased in return at
such a high volume that may expose the company’s financial condition and stability to
risk. 4. Where a member violates or fails to comply with the provisions prescribed in
these Regulations, the Exchange may prohibit such a member from conducting short
sales. Said rules and regulations of short sale or regulatory risks led us to believe that
short sale in Thailand might not be favorable among investors. In addition, short sales
involves significant cost and is not for everybody since this strategy is suitable for
experienced investors and not recommended for investors with low risk tolerance or
little experienced traders.
Ref. code: 25605902042190NPJ
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REFERENCES
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BIOGRAPHY
Name Miss Pensiri Thepchoom
Date of birth June 1, 1991
Educational attainment
2014: Bachelor of Business Administration,
Finance
Work position Relationship Officer
Bangkok Bank
Work Experiences Relationship Officer, Bangkok Bank
Corporate Service Officer, Bangkok Bank
Ref. code: 25605902042190NPJ
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