short selling and price pressure around acquisition

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

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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



3.5 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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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


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


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

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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)


(j=4)

(2)


(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)


(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


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


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)


(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


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


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)


(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


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


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

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For WHA, Results shows negative coefficient of interest variable ANN and P-


null hypothesis which indicated that there’s no significance short selling in WHA


Table 4.14 Summary Statistics of MAJOR


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


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)


(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


Table 4.16 Summary Statistics of PF


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in PF during


Table 4.18 Summary Statistics of BAY


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in BAY during


Table 4.20 Summary Statistics of BDMS


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in BDMS


Table 4.22 Summary Statistics of DTAC


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in DTAC


Table 4.24 Summary Statistics of KKP


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in KKP during


Table 4.26 Summary Statistics of LH


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in LH during


Table 4.28 Summary Statistics of MINT


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in MINT


Table 4.30 Summary Statistics of SCB


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in SCB during


Table 4.32 Summary Statistics of SCC


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in SCC during


Table 4.34 Summary Statistics of TCAP


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in TCAP


Table 4.36 Summary Statistics of TMB


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


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)


(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-


null hypothesis which indicated that there’s no significance short selling in TMB during


Table 4.38 Summary Statistics of TU


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


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)


(0.000)

2.490251

(0.000)

2.303705

(0.094)

𝑹𝟐 .0016 .7859 .7912

Prob > F .8649 .0000 .0001

Ref. code: 25605902042190NPJ

47

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


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


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)


(0.000)

.0595565

(0.000)

.0200793

(0.166)

𝑹𝟐 .0000 .0034 .0655

Prob > F .8581 .0124 .0000

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For UV, Results shows negative coefficient of interest variable ANN and P-


null hypothesis which indicated that there’s no significance short selling in UV during


Table 4.42 Summary Statistics of VGI


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


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)


(0.000)

2.687365

(0.000)

7.268705

(0.002)

𝑹𝟐 .0015 .3878 .8028

Prob > F .8665 .0356 .0010

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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.

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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

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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.

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REFERENCES

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Merger Announcements, Journal of Financial Services Research 48, 143-160

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of-the-month anomaly

3. Christophe, S. , M. Ferri, and J. Angel, 2004, Short- Selling Prior to Earnings

Announcements, The Journal of Finance 59, 1845-1875.

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the information role of short interest in the NASDAQ market. J Financ 52:2263–2287

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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

short selling and price pressure around acquisition

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