Syntax Idea: p�ISSN: 2684-6853 e-ISSN: 2684-883X�
Vol. 3, No.11, November 2021
Novita Emildasari, Dewi Tamara
Binus Business School, Binus
University, Indonesia�
Email: [email protected],
[email protected]
Abstract
This
research is to identify the company's financial performance after two years of
merging and acquisition. This research analyzes the effect of Money Supply, Inflation
and Foreign Exchange) and the stock trading volume, earning per share, and
price to earning ratio) on yield and capital gain.
The population is companies that did mergers & acquisitions in 2018. This
research data is monthly data throughout 2018 and 2020. Data analysis techniques
include regression of panel data using views 10, and Chow, Lagrange Multiplier,
and Hausman test). The results are there is an increase in the stock market
performance and variables of capital gain, yield, trade volume activity earnings
per share, except for price to earning ratio. Foreign
exchange, trading volume, EPS, and PER have a positive and significant impact
on capital gains and yields. Meanwhile, money supply and inflation insignificantly
positive affect capital gains and yields.
Keywords:
acquisition; merger; macroeconomic; stock market; capital�� gain; ield�
Received:
2021-09-22; Accepted: 2021-10-05; Published: 2021-10-20
Introduction
The phenomenon of mergers and acquisitions
transactions is increasingly common among companies, including companies in
Indonesia. A merger and acquisition transaction should increase the company's
capabilities in a short period of time compared to internal growth or organic
growth which usually takes a slower time to produce equivalent growth (Lynch & Lind, 2002).
Many previous studies have examined why many
companies undertake mergers and/or acquisitions. (Agnihotri, 2013) examines
the determinants of M&A from the perspective of the Indian state. The
results of his research show that earnings volatility and business group
affiliation are determinants of the occurrence of M&A in companies in
India. Research by (Antoniou et al., 2008)
shows the variables that drive M&A, namely the results of management
studies on market valuations. M&A policy is more driven by bullish market
conditions.
Other previous studies looked at the factors that
determine the success of the company after conducting (Schraeder & Self, 2003)
examines it from the perspective of organizational culture (organizational
culture), organizational change, organizational strategy, and organizational
development management as important catalysts for the success of M&A. (Stahl et al., 2013)
examines the success of M&A from the aspect of human resources. Jochem T.
Hummel and (Hummel & Amiryany, 2015)
assessed the performance determinants of the acquiring company as seen from the
intensity of research and development (R & D intensity). The two researchers
classified the acquired companies into three categories based on the intensity
of research and development, namely high-tech companies, medium-tech companies,
and low-tech companies. Both researchers view that R & D intensity is a
determinant that determines the success of the company's performance after the
acquisition.
More specifically, research by (Kim et al., 2019) finds
that macroeconomic factors (overal activity, market
value, cost of debt, and inflation) are the determinants of the success of
mergers and acquisitions. A number of studies have shown how macroeconomic variables
and the stock market can affect company performance, especially financial
performance. Financial performance can be based on accounting, such as Return
on Equity (ROE), Return on Assets (ROA), and Gross Profit Margin (GPM).
Financial performance can also be market-based such as Stock Returns, Earning
Yield ratio (EYR), Earning per Share (EPS), and Dividend Yield ratio (DYR).
This research contributes in several ways. First, to
fill the gap in the literature of post-merger study in terms of macroeconomic
and microeconomic. Second, time horizon of two years is regarded as sufficient
benchmark to investigate the post-merger result. Third, this research includes
the variables from stock market such as trading volume activity.
Financial performance can also be based on a mixture
of accounting and market bases such as Tobin's Q ratio. These studies are shown
in Table 1.
Table 1
Position of
Financial Indicators Before and After Merger
|
Variables |
1 Year before Merger (Mean) |
1 Year After Merger (Mean) |
2 years After Merger (Mean) |
3 years after Merger (Mean) |
4 years after Merger (Mean) |
|
Current Ratio |
1,9888 |
1,7520 |
2,0188 |
2,1532 |
2,2676 |
|
Quick ratio |
1,2304 |
1,2460 |
1,4040 |
1,4972 |
1,5268 |
|
Debt to Asset Ratio |
0,6360 |
0,4768 |
0,5380 |
0,4980 |
0,4516 |
|
Debt to Equity Ratio |
1,1800 |
1,2384 |
1,5732 |
1,7272 |
0,9784 |
|
Inventory Turnover Ratio |
14,9308 |
8,2340 |
9,1312 |
9,8440 |
10,0036 |
|
Asset Turnover Ratio |
0,9160 |
0,6820 |
0,6556 |
0,6160 |
0,6796 |
|
Return on Total Asset |
0,1128 |
0,0428 |
0,0400 |
0,0408 |
0,0612 |
|
Return on Equity |
0,1624 |
0,0616 |
0,0488 |
0,1060 |
0,1016 |
|
Net Profit Margin |
0,1968 |
0,1140 |
0,0828 |
0,1648 |
1,1640 |
|
Operating Profit Margin |
0,2296 |
0,1420 |
0,1016 |
0,1864 |
0,2016 |
Research Methods
The study
units are companies that have merged or acquired in 2018 and have gone public
or are listed on the IDX. This research used the database from Business Competition Supervisory Commission (KPPU) (https://kpu.go.id/belief.merger.2018/) in year
2018. Based on this criterion, then 17 business entities can be identified as
the population in this study.
This study
used quantitative method using panel data from the five years data including
the financial report and variables. The quantitative will use regression to
test the hypothesis. For regression it will follow the rules of thumb of classical
assumption. �The study will test the sensitivity
using Chow test, Lagrange Multiplier test and Hausman test to identify the
fixed or random effect model.
Results and Discussions
The
variables of this study include the independent variable and the dependent
variable. The first independent construct in this study is Macroeconomics (X1)
with research indicators consisting of Money Supply (X11), Inflation (X12, and
Exchange Rates (X13). The second independent variable
is the Stock Market (X2) which consists of Trading Volume indicators Stocks (X21),
EPS (X22), and PER (X23).The dependent variable of this study is Financial
Performance (Y) with Yield (Y1) and Capital Gain (Y2) indicators.
The
description of this research variable will be presented with four kinds of data,
namely (i) a description of the overall data variables (2018-2020), (ii) a
description of the variables before the M & (2018) occurs, (iii) a
description of the variables after one year of M & A (2019), and (iv) a
description of the variables after two years of M&A (2020). The presentation
of these four types of data can be compared so that a better picture of the
company's development can be obtained from before conducting the M & A
(2018), one year after the M & A (2019), two years after the M & A
(2020) according to the research title, and overall performance for three years
(2018-2020).
1. Test the hypothesis with t test
Statistical tests basically show how
far the influence of one explanatory/independent variable individually in
explaining the variation of the dependent variable. Null hypothesis (H0): the
parameter under test is equal to zero. Alternative hypothesis (Ha): the
parameters tested are not equal to zero (Ghozali, 2012). Decision making
is carried out as follows (Ghozali, 2012): Comparing the
calculated t value with the t value according to the t table. If the value of t
count is greater than t table, then Ho and are rejected and Ha (alternative
hypothesis) is accepted. Vice versa.
Based on Table 4.26 it appears that,
statistically, the t-count results for each independent variable (EPS, Exchange
Rate, Inflation, Money Supply, PER, Trading Volume) on the dependent variable
Financial Performance with the Yield proxy (Y).
a. Hypothesis testing of the effect of Macroeconomic
variables (X1) on the dependent variable of Financial Performance with the
Yield (Y) proxy with
1) Influence based on the Money Supply
indicator (X11)
The value of the coefficient of the
effect of money supply on yield is 0.080109 (8.01%). Means that Money Supply
has a positive effect on Yield with a standardized coefficient of 0.080109
(8.01%). It means that an increase in Money Supply by 1 (one) unit will
increase the Yield by 0.080109; or an increase in Money Supply by 100% will
increase Yield by 8.01%. The remaining influence (100%-8.01%= 91.99%) on Yield
can be explained by other variables other than Money Supply.
The t-statistical test is shown in
Table 4.26 that the magnitude of the t-count regression of Money Supply (X1) on
Financial Performance (Yield proxy) (Y) is t=0.842622, p-value= 0.3967. This
means that the value of tcount (0.842622) < ttable (1.97208), H0 is accepted and H1 is rejected. In
addition, the p-value is 0.3967, which means > 0.05. This means that the Money
Supply (X11) has a positive but not significant effect on Yield (Y).
2) Influence based on Inflation indicator
(X12)
The value of the coefficient of the
effect of inflation on yield is 0.094543 (9.45 %). Means that inflation has a
positive effect on Yield with a standardized coefficient of 0.094543 (9.45%).
It means that 1 (one) unit increase in Inflation will increase Yield 0.094543;
or an increase in Inflation by 100% will increase Yield by 9.45%. The remaining
effect (100%-9.45%=90.55%) on Yield can be explained by other variables other
than inflation.
The t-statistical test is shown in
Table 4.25 that the magnitude of the t-count regression of Inflation (X2) on
Financial Performance (Yield proxy) (Y) is t=1.797774, p-value= 0.4153. This
means that the value of tcount (1.797774) < ttable (1.97208), H0 is accepted and H1 is rejected. In
addition, the p-value is 0.4153, which means > 0.05. This means that
inflation (X12) has a positive but not significant effect on Yield (Y).
3) Influence based on the Exchange Rate
indicator (X13)
The coefficient of the effect of the
Exchange Rate on Yield is 0.203247 (20.32 %). It means that the exchange rate
has a positive effect on yield with a standardized coefficient of 0.203247
(20.32 %). It means that an increase in the Exchange Rate of 1 (one) unit will
increase the Yield 0.203247 (20.32 %).; or an increase in the Exchange Rate by
100% will increase the Yield by 20.32%. The remaining influence
(100%-20.32%=79.68%) on Yield can be explained by other variables outside the
Exchange Rate variable.
The t-statistical test is shown in
Table 4.25 that the magnitude of the t-count regression of Exchange Rate (X2)
on Financial Performance (Yield proxy) (Y) is t=3.987147, p-value= 0.2521. This
means that the value of tcount (3.987147> ttable (1.97208), H0 is accepted and H1 is rejected. In
addition, the p-value is 0.2521 which means <0.05 This means that the
Exchange Rate (X13) has a positive and significant effect on Yield (Y) .
b. Testing the hypothesis of the
influence of the Stock Market variable (X2) on the dependent variable Financial
Performance with the Yield (Y) proxy
1) Influence based on Trading Volume
indicator (X21)
The coefficient value of the effect
of Trading Volume on Yield is 0.146710 (14.67%). It means that Trading Volume
has a positive effect on Yield with a standardized coefficient of 0.146710
(14.67%). Means an increase in Trading Volume of 1 (one) unit will increase
Yield 0.146710 (14.67%); or a 100% increase in Trading Volume will increase
Yield by 14.67%. The remaining influence (100%-14.67 %=85.37%) on Yield can be
explained by other variables other than the Trading Volume variable.
The t-statistical test is shown in
Table 4.25 that the magnitude of the t-count regression of Trading Volume (X2)
on Financial Performance (Yield proxy) (Y) is t=3.750363, p-value= 0.1002. This
means that the value of tcount (3.750363) > ttable (1.97208), H0 is accepted and H1 is rejected. In addition,
the p-value is 0.1002 which means <0.05. This means that Trading Volume
(X21) has a positive and significant effect on Yield (Y).
2) �Influence based on Earning per Share (EPS)
indicator (X22)
The coefficient of the effect of
Earning per Share (EPS) on Yield is 0.11798 (20.17%). It means that Earning per
Share (EPS) has a positive effect on Yield with a standardized coefficient of
0.11798 (20.17%). It means that an increase in Earning per Share (EPS) of 1
(one) unit will increase Yield 0.11798 (20.17%); or increase in Earning per
Share (EPS) by 100% will increase Yield by 20.17%. The remaining influence
(100%-20,17 %=79.83%) on Yield can be explained by other variables outside the
Earning per Share (EPS) variable.
The t-statistical test is shown in Table
4.25 that the magnitude of t-count regression Earning per Share (EPS) (X2) on
Financial Performance (Yield proxy) (Y) is t=2.986337, p-value= 0.0178. This
means that the value of tcount (2.986337) < ttable (1.97208), H0 is accepted and H1 is rejected. In
addition, the p-value is 0.0178 which means <0.05. This means that Earning
per Share (EPS) (X22) has a positive and significant effect on Yield (Y).
3) Effect based on Price Earning Ratio (PER) (X23) indicator
The coefficient value of the effect
of Price Earning Ratio (PER) on Yield is 0.102816
(10.28%). It means that Price Earning Ratio (PER) has
a positive effect on Yield with a standardized coefficient of .102816 (10.28%).It means that an increase in Price Earning
Ratio (PER) of 1 (one) unit will increase Yield .102816 (10.28%). ; or an
increase in Price Earning Ratio (PER) by 100% will
increase Yield by 10.28%. The remaining influence (100% -10.28% = 89.72%) on
Yield can be explained by other variables outside the Price Earning
Ratio (PER) variable.
The t-statistical test is shown in
Table 4.25 that the magnitude of t-count regression of Price Earning Ratio (PER) (X2) on Financial Performance (Yield
proxy) (Y) is t=2.166173, p-value= 0.0500. This means that the value of tcount (2.166173) > ttable
(1.97208), H0 is accepted and H1 is rejected. In addition, the p-value is
0.0500 which means <0.05. This means that the Price Earning
Ratio (PER) (X23) (X22) has a positive and significant effect on Yield (Y).
The results
showed that there was an increase in financial performance, especially stock
market performance, in 17 companies that went public in 2020 after they carried
out a merger/acquisition (M&A) two years earlier (2018). The increase in
the performance of these shares is as follows: (a) The average capital gain in
2018 is Rp. 0.613281/share. The average yield in 2018 was IDR 1.439011/share,
increasing in 2020 to IDR 2.302451/share. (b) Stock trading volume (trade volume
activity/ TVA), the average TVA in 2018 was 665,224,3923 lots (1 lot=500
shares), increased in 2020 to 1,209,726, 338 lots. (c). Earning
per share (EPS), the average EPS in 2008 was 111,.0441 %; increased in 2020 to
195.3034 %. The decrease only occurred in the Price earning
ratio (PER), where. the average PER in 2018 was 53,46448%. decreased in 2020 to
45.58041%.
Externally,
M & A companies, in this case macroeconomic variables, with three proxies
(money supply, inflation, exchange rates), also experienced changes for three
years (2018-2020). The average money supply per month (monthly) is IDR
3,861,538,333 billion (2018), decreasing to an average per month (monthly) of
IDR 446,660,545 billion (2020). The monthly IDR exchange rate against USD
increased from IDR 13,398, 17 in 2018 to IDR 14,625.25 in 2020. The average
monthly inflation in 2018 was 3.1975 also increased to 2,035833% in 2020. Based
on the results of the study, the three The
macroeconomic variable has a positive but not significant effect on stock
returns. The results of this study support the results of previous studies that
exchange rates, inflation, and exchange rates have a positive effect on stock
returns (de Sousa et al., 2018).
The results
of this study support the results of research by (Murphy et al., 2010), (Stahl et
al., 2013), (Toyoshima et al., 2014), (Hummel & Amiryany, 2015)
and (Kim et al., 2019). However, the output
of this study contradicts the output of the study by (Romero et al., 2014)
who conducted research on the financial performance of manufacturing companies
after they had mergers and acquisitions. The finding of this study is that the
financial performance of companies that acquire manufacturing companies does
not significantly increase after the merger process. Liquidity, profitability,
and capital position did not significantly increase, even the company's
efficiency worsened in the period after the merger.
The difference
in the results of these studies can be caused by many things. Among them is the
use of research indicators. Research by (Romero et al., 2014)
uses indicators of liquidity, profitability, and capital position. While this
study uses macroeconomic indicators and the stock market. In addition, there
are differences regarding the object of research. The object of research by (Romero et al., 2014)
is a manufacturing company, while this study chooses the object of research in
the company sector in general.
This study
adds to the wealth of macroeconomic impacts on stock market performance. For
example, previous studies have proven the positive effect of inflation on
returns. (Ouma & Muriu, 2014)
and share index (Laichena & Obwogi, 2015)
This study proves the positive effect of inflation on capital gains and yields
in companies that have conducted M&A two years before. This study supports
the results of research (Pathirawasam, 2011)
(Tehranchian,
A. M., Behravesh, M., & Hadinia, 2014) which proves that stock trading volume
is proven to affect stock returns.
This
research also creates a research gap. For example, research (Ruhomaun et al., 2019)
proves that exchange rates have a negative effect on firm performance. (Ouma & Muriu, 2014)
proves the negative effect of Exchange Rate on Return. While this study proves
otherwise that the exchange rate has a positive effect on returns (capital gains
and yields).
Theoretically,
the results of this study support the opinion of (Agrawal et al., 2012), (Ivanov
et al., 2014), and (Vyas et al., 2012)
which basically states that the motivation of companies to conduct M&A is
motivated by the desire to obtain financial synergies, market power, gain
access to a distribution channel, or to enter a new geographic access. The
results of this study indicate that the financial performance of the 17
companies increased after two years of conducting M&A (2020).
Theoretically
there are many indicators that show the company's development after conducting
M&A. For example, (Ivanov et al., 2014)
and (Vyas et al., 2012)
that through M&A the acquirer can gain direct access to the technology,
distribution channel, and market share of the company's target. The technology
transfer factor (know-how) is a strong reason for companies to conduct M&A,
so this factor is one of the measuring tools for the success/failure of the
company after conducting M&A. Meanwhile, this study measures the
success/failure of the M&A from a stock market perspective.
Considering
that this research intends to measure the success/failure of the company conducting
the M&A from the stock market perspective, the proxy used is stock return.
The basis for measuring financial performance in this study is the stock
market, namely stock returns. Stock returns are chosen as a proxy for financial
performance, because this proxy is proven to be influenced by macroeconomic
variables and the stock market. Stock return is the profit obtained from
investment. Stock return is the level of profit obtained by investors or a
stock investment that they do. Stock returns are divided into realized returns
and expected returns. This study chooses stock returns in terms of stock
realization (relized return), with two indicators,
namely yield and capital gain. Yield is the percentage of periodic cash receipts
to the investment price in a certain investment period. Yield= (dividend per
share/close price) x100%. Meanwhile, Capital gain/loss is the difference
between the current investment price and the past investment price. Capital
gain/loss: (Close price (Pt) � close price (Pt-1)/ Pt-1) x 100%.
Macroeconomic analysis. The money
supply (supply of money) affects stock returns positively but not
significantly. Money supply (money supply) is the monetary obligation of a
monetary system to the public, in Indonesia the money consists of the amount of
currency outside the monetary system and demand deposits on behalf of parties
who are not members of the monetary system (bi.go.id/ Dictionary .aspx?id=U). The results of this study prove that the
participants in the stock market are also people who pay attention to the
movement of money circulating in the community.
Inflation is
proven to affect stock returns but not significantly. The results of this study
prove that the participants in the stock market are also people who pay
attention to the movement of inflation in society. Inflation in this study is monthly
inflation published by Bank Indonesia (BI) as measured by the Consumer Price
Index (CPI).
Likewise
exchange rates. The exchange rate is one of three macroeconomic variables that
positively and significantly affect stock returns. This is considering the
exchange rate of the rupiah (IDR) against the US dollar (USD) increased from
Rp. 13,398, 17 in 2018 to Rp. 14,625.25 in 2020. The fluctuations in the
exchange rate of the IDR against the USD are factors that also influence investors
to transact shares in the stock market, thus affecting the volume of stock
trading and stock prices. Changes in stock prices will determine stock returns.
Stock market
analysis. Stock trading volume variable (trading volume activity, TVA) is
proven to have a positive and significant influence on stock returns. TVA is
the number of shares traded with the number of shares outstanding. This TVA
indicator is useful for measuring whether individual investors know the information
issued by the company and use it in buying or selling shares. The results of
this study which prove that TVA has a positive and significant effect indicate
that investors know about the dynamics of TVA in Tbk
companies that carry out M&A.
The results
of the study prove that EPS has a positive and significant effect on stock
returns. earning per share (EPS) is a ratio that
shows how much the ability per share to generate profits or is a ratio that
describes the amount of rupiah earned for each share of common stock. will be
earnings per share.
Price Earning Ratio (PER) is proven to positively and
significantly affect Stock returns. PER is the ratio of the company's share
price to the company's earnings per share. PER is the share price divided by
EPS (Rahmadewi & Abundanti,
2018). EPS and PER are closely related statistically. EPS is proven to affect
stock returns, in this study it is proven that EPS and
PER are directly proportional in influencing stock returns.
Conclusion
This study
examines the effect of six independent variables (EPS, Exchange Rate, Inflation,
Money Supply, PER, Trading Volume) on one dependent variable (financial
performance with stock return proxies, with capital gain indicators, and
yields) in 17 companies listed on the IDX. in 2020, after the 17 companies
conducted a merger/acquisition (M&A) two years earlier (2018). The study
also compared the stock market performance of 17 companies simultaneously
between 2018 (when the M&A took place) and 2020 (after two years of
M&A). The following are the results of the study: (1.) The development of
the 17 companies after two years of conducting M&A can be viewed from the
stock market variables/indicators as follows: a.) Stock return variables (stock
return), with indicators Yield (Y1) and Capital Gain (Y2). The average capital
gain in 2018 was IDR 0.613281/share, while the average capital gain in 2020 was
IDR 2.50. The average yield in 2018 was IDR 1.439011/share, increasing in 2020
to IDR 2.302451/share. 2.) Stock trading volume (trade volume activity/ TVA).
The average TVA in 2018 was 665,224,3923 lots (1 lot=500 shares), increased in
2020 to 1,209,726, 338 lots. 3.) EPS. The average EPS in 2008 was 111,.0441 %;
increased in 2020 to 195.3034 %.. 4.) PER. The average
PER in 2018 was 53,46448%. decreased in 2020 to 45.58041%. (2.) In relation to
the effect of six independent variables (EPS, Exchange Rate, Inflation, Money
Supply, PER, Trading Volume) on one dependent variable (financial performance
with stock return proxy, which is divided into two indicators: capital gains,
and yields) in 17 company two years after the M&A (2020) it can be
concluded that: a.) Money supply affects capital gain positively but not
significantly, with a coefficient value of 0.0800308 (8.03%). Money supply
affects yield positively but not significantly, with a coefficient value of
0.080109 (8.01%). It means that the effect of money supply on yield is greater
than the effect of money supply on capital gains. The results of this study
prove hypothesis 1a which reads that the money supply has an effect on stock
returns. b.) Inflation affects capital gains positively but not significantly, with
a coefficient value of 0.069325 (6.93 %). Inflation affects yields positively
but not significantly, with a coefficient value of 0.094543 (9.45 %). It means
that the effect of inflation on yield is greater than the effect of inflation
on capital gains. The results of this study prove hypothesis 2a which reads
that inflation affects stock returns. c.) Exchange rate affects capital gains
positively and significantly, with a coefficient value of 0.206036 (20.60 %).
Exchange rate affects yield positively and significantly, with a coefficient
value of 0.203247 (20.32 %). It means that the effect of the exchange rate on
capital gains is greater than the effect of the exchange rate on the yield. The
results of this study prove hypothesis 2b which reads that the exchange rate
has an effect on stock returns. d.) Trading Volume affects capital gains
positively and significantly, with a coefficient value of 0.181019 (18.10%).
Trading Volume affects yield positively and significantly, with a coefficient
value of 0.146710 (14.67 %). It means that the effect of Trading Volume on
capital gain is greater than the effect of Trading Volume on yield. The results
of this study prove hypothesis 2a which reads that trading volume has an effect
on stock returns. e.) Earning per share affects capital gain positively and
significantly, with a coefficient value of 0.206036 (20.60%). Earning per share affects yield positively and
significantly, with a coefficient value of 0.11798 (20.17%). This means that
the effect of Earning per Share on capital gains is greater than the effect of
Earning per Share on yield. The results of this study prove hypothesis 2b which
reads Earning Per Share (EPS) has an effect on stock returns. f.) Price Earning Ratio (PER) affects capital gain positively and
significantly, with a coefficient value of 0.127826 (12.78%). Earning per share affects yield positively and
significantly, with a coefficient value of 0.102816 (10.28%). It means that the
effect of Price Earning Ratio on capital gain is greater
than the effect of Price Earning Ratio on yield. The
results of this study prove hypothesis 2c which reads Price Earning
Ratio (PER) has an effect on stock returns.
BIBLIOGRAFI
Agnihotri, A. (2013). Determinants of acquisitions: An Indian
perspective. Management Research Review.Google Scholar
Agrawal,
A., Misra, S., Narayanan, R., Polepeddi, L., & Choudhary, A. (2012). Lung
cancer survival prediction using ensemble data mining on SEER data. Scientific
Programming, 20(1), 29�42. Google Scholar
Antoniou,
A., Guo, J., & Petmezas, D. (2008). Merger momentum and market valuations:
the UK evidence. Applied Financial Economics, 18(17), 1411�1423. Google Scholar
Asiamah,
N., Mensah, H. K., & Oteng-Abayie, E. F. (2017). General, target, and
accessible population: Demystifying the concepts for effective sampling. The
Qualitative Report, 22(6), 1607. Google Scholar
De
Sousa, A. M., Noriller, R. M., Huppes, C. M., Lopes, A. C. V., & Meure, R.
M. (2018). Relation between the macroeconomic variables and the stock return in
companies of the finance and insurance sector from Latin American stock market.
GCG: Revista de Globalizaci�n, Competitividad y Gobernabilidad, 12(3),
20�30. Google Scholar
Ghozali,
I. (2012). Aplikasi Analisis Multivaruate dengan Program IBM SPSS. Edisi 1.
Badan Penerbit Universitas Diponegoro.
Hummel,
J. T., & Amiryany, N. (2015). Determinants of acquisition performance: A
multi-industry analysis. In Advances in mergers and acquisitions.
Emerald Group Publishing Limited. Google Scholar
Ivanov,
S. H., Ivanova, M. G., & Iankova, K. (2014). Sustainable tourism practices
of accommodation establishments in Bulgaria: an exploratory study. Tourismos
(Forthcoming). Google Scholar
Kim,
J., Zheng, T., & Arendt, S. W. (2019). Identification of merger and
acquisition waves and their macroeconomic determinants in the hospitality
industry. Journal of Hospitality & Tourism Research, 43(2),
249�271. Google Scholar
Laichena,
K. E., & Obwogi, T. N. (2015). Effects of macroeconomic variables on stock
returns in the East African community stock exchange market. International
Journal of Education and Research, 3(10), 305�320. Google Scholar
Lynch,
J. G., & Lind, B. (2002). Escaping merger and acquisition madness. Strategy
& Leadership. Google Scholar
Murphy,
L., Denis, R., Ward, C. P., & Tartar, J. L. (2010). Academic stress
differentially influences perceived stress, salivary cortisol, and immunoglobulin-A
in undergraduate students. Stress, 13(4), 366�371. Google Scholar
Ouma,
W. N., & Muriu, P. (2014). The impact of macroeconomic variables on stock
market returns in Kenya. International Journal of Business and Commerce,
3(11), 1�31. Google Scholar
Pathirawasam,
C. (2011). The Relationship Between Volume Perdagangan and Jump Processes in
Financial Markets. Journal of Competitiveness, 41(3), 41�49.
Romero,
R., Miranda, J., Chaiworapongsa, T., Korzeniewski, S. J., Chaemsaithong, P.,
Gotsch, F., Dong, Z., Ahmed, A. I., Yoon, B. H., & Hassan, S. S. (2014).
Prevalence and clinical significance of sterile intra‐amniotic
inflammation in patients with preterm labor and intact membranes. American
Journal of Reproductive Immunology, 72(5), 458�474. Google Scholar
Ruhomaun,
M. A., Saeedi, M., & Nagavhi, N. (2019). The Efects of Selected Macro and
Mico Economics Variables on Firm Performance for Listed Firms in the Industrial
Products Sector in Malaysia. International Jurnal of Recent Technology and
Engineering, 7(5), 95�101. Google Scholar
Sandjaja,
B., & Heriyanto, A. (2011). Panduan Penelitian, jakarta: Prestasi Pustakaraya. Google Scholar
Schraeder, M., & Self, D. R.
(2003). Enhancing the success of mergers and acquisitions: an organizational
culture perspective. Management Decision. Google Scholar
Stahl, G. K., Angwin, D. N.,
Very, P., Gomes, E., Weber, Y., Tarba, S. Y., Noorderhaven, N., Benyamini, H.,
Bouckenooghe, D., & Chreim, S. (2013). Sociocultural integration in mergers
and acquisitions: Unresolved paradoxes and directions for future research. Thunderbird
International Business Review, 55(4), 333�356. Google Scholar
Tehranchian,
A. M., Behravesh, M., & Hadinia, S. (2014). On the relationship between
stock returns and Volume Perdagangan. A Case Study. European Online Journal
of Natural and Social Science, 3(3), 425.
Toyoshima,
M., Munemasa, Y., Takenaka, H., Takayama, Y., Koyama, Y., Kunimori, H.,
Kubooka, T., Suzuki, K., Yamamoto, S., & Taira, S. (2014). Introduction of
a terrestrial free-space optical communications network facility: IN-orbit and
Networked Optical ground stations experimental Verification Advanced testbed
(INNOVA). Free-Space Laser Communication and Atmospheric Propagation XXVI,
8971, 89710R. Google Scholar
Vyas,
M. V, Garg, A. X., Iansavichus, A. V, Costella, J., Donner, A., Laugsand, L.
E., Janszky, I., Mrkobrada, M., Parraga, G., & Hackam, D. G. (2012). Shift
work and vascular events: systematic review and meta-analysis. Bmj, 345. Google Scholar
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