Capital Market Reaction on the Announcement of the First

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Capital Market Reaction on the Announcement of the First COVID-19 Case in Indonesia By the President of The Republic Indonesia: Case Study of Telecommunication Sub Sectors Listed

on the IDX

Davina Vania Mardhiah^1*, Irni Yunita¹

1 Management Business Telecommunication and Informatics, Telkom University, Bandung, Indonesia

*Corresponding Author: [email protected]

Accepted: 15 February 2021 | Published: 1 March 2021

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Abstract: The announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia is one of the company's external events of particular concern to investors. This study aims to determine whether there is a difference in abnormal return and trading volume activity 5 days before and 5 days after the sub-telecommunication shares as a result of the announcement of the President of the Republic of Indonesia regarding the first case of COVID-19 in Indonesia. The results showed that in the shares of the telecommunications sub-sector there were differences in abnormal returns, but there was no difference in trading volume activity before and after the announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia. This means that the announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia contains information that can be absorbed by investors but does not show up significantly in trading volume activity, while abnormal returns are a significant difference.

Keywords: Abnormal Return, Trading Volume Activity, Event Study, COVID-19

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1. Introduction

Currently, investment is a community activity to increase the income they have. There are various choices of types of allocation of funds owned, including savings, deposits, gold, bonds, and stocks. In investing, decisions depend on the level of return and the level of risk that will be borne by the investor (Afriyeni & Marlius, 2019). According to research conducted by the IDX, this type of stock investment has the highest rate of return with 13.13%. Seeing this, it is not surprising if people are interested in investing in stocks seeing the high return that will be obtained, of course, with careful consideration.

The development of activities in the capital market depends on the disclosure of information which is a consideration in making investors' decisions. By obtaining this information, investors will react by investing, so that investors' decisions become rational. One of the information is COVID-19 which is currently sweeping the world.

Coronaviruses (CoV) is a virus that attacks the human respiratory system. This disease has flu symptoms in general, such as cough, fever, shortness of breath, and loss of appetite. The disease caused by the coronavirus was discovered in 2019 which had never previously been identified as attacking humans (World Health Organization, 2020). In Indonesia, the first case of COVID- 19 appeared on Monday, March 2, 2020. At that time, Indonesian President Joko Widodo

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announced that he had been infected with two Indonesian citizens aged 31 years and 64 years.

Since the announcement of the first case in Indonesia, the number of infected cases has been increasing every day.

So that to reduce and anticipate the number of coronavirus sufferers in Indonesia, the government provides a policy of limiting activities outside the home. This is intended to break the chain of virus spread, given the very fast spread of this virus. School activities, lectures, and work are carried out using online media. According to data from the Ministry of Communication and Informatics, there has been a shift in internet use during the pandemic, it is estimated that the increase in internet use will occur by up to 40% (Ministry of Communication and Informatics, 2020). The dependence of society on the internet, especially during this pandemic, has resulted in the view that the telecommunications sub-sector is considered to be a sector that is not negatively affected.

Based on this phenomenon, the market is considered to be able to react to existing information.

This is because an efficient market will react quickly to the information that occurs. To be able to see this, it can be proven from the difference in abnormal returns and trading volume activity before and after the event.

2. Literature Review

According to Prameswari & Wirakusuma (2018), the capital market is an economic instrument that cannot be separated from information, investors will make an assessment and become a consideration in making decisions so that the capital market is strongly influenced by information content. A market can be said to be efficient when the traded securities can reflect when there is information content that occurs quickly and accurately (Mar'ati, 2012).

To be able to see the capital market's reaction to information, it can be done by looking at the abnormal return and trading volume activity (TVA). Abnormal return is the change in value to the return of a stock, when an event occurs, if it contains information, there will be an abnormal return. Conversely, if the event does not contain information, there will be no abnormal return (Dewi & Putra, 2013). Furthermore, by looking at trading volume activity (TVA), trading volume activity is the development of the amount or at least the volume of stock trading can show whether an event affects trading in the capital market (Budiyanto, Ismani, & Ngadirin, 2006).

There is previous research that discusses several events related to COVID-19 affecting the capital market. Putri (2020) has research on the effect of rupiah fluctuations due to the COVID- 19 pandemic on shares listed in LQ45. The results of this study show that there is a significant difference in the average abnormal return and trading volume of these stocks so that the fluctuation of the rupiah due to the COVID-19 pandemic is considered to have affected the capital market.

Zulfitra & Tumanggor (2020) research with other methods to see the capital market's reaction to the COVID-19 Pandemic, namely by using the Least Square Regression method. The result of the research is that the COVID-19 pandemic event has a significant impact on stock prices.

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3. Methodology

The capital market is said to be efficient when it can react quickly if there is information content when an event occurs. So that the type of research used in this research is an event study, by looking at the market reaction to an event, namely the announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia.

In this study, the population used was all companies in the Infrastructure, Utilities, and Transportation sectors with the telecommunications sub-sector listed on the Indonesia Stock Exchange in 2020, namely 6 companies. The data used in this research are stock price data and daily stock sales. In this study, data collection was obtained through the Indonesia Stock Exchange website (www.idx.co.id) and Yahoo Finance (www.finance.yahoo.com).

In this study, data processing was carried out for further analysis of the data. The data processing steps in this study were as follows:

1) Calculating the actual return. The actual return can be calculated using stock price data for each company. The actual return itself can be calculated with the following formula (Hartono, 2017: 667):

𝑅_𝑖,𝑡 =(𝑃_𝑖,𝑡− 𝑃_{𝑖,𝑡−1}) 𝑃_{𝑖,𝑡−1}

𝑅_𝑖,𝑡 = the actual return that occurs on securities i on day t 𝑃_𝑖,𝑡 = the daily share price of the security i on day t

𝑃_{𝑖,𝑡−1} = the daily share price of securities i on the day before day t

2) Calculate the expected return. The market-adjusted model technique is used to calculate the expected return, which requires daily data on the stock index used, namely telecommunication companies. In this study, the expected return is the same as the market return on the event day or t-0.

3) Calculating the abnormal return. Seeing the market reaction to an event can be shown by measuring the abnormal return. The abnormal return technique used in this study is a market-adjusted return. This technique is used to calculate abnormal returns by eliminating the market's influence on the daily return of securities so that in this technique the estimated return of the securities is the same as the current stock index return. Abnormal return is calculated by reducing the stock return on the announcement day with the current stock return, the formula is as follows (Tandelilin, 2010: 225):

𝐴𝑅_𝑖,𝑡 = 𝑅_𝑖,𝑡− 𝑅_𝑀,𝑡 𝐴𝑅_𝑖,𝑡 = Abnormal return of security i on day t 𝑅_𝑖,𝑡 = Actual return of securities i on day t 𝑅_𝑀,𝑡 = Market return on day t

4) Calculating trading volume activity. To see if there is a surge or decrease in stock sales, it is calculated by trading volume activity. The data used is the number of shares sold and the number of shares outstanding. The results of the TVA calculation will reflect that there is a movement in the sale of shares at a certain time, TVA can be measured by the following formulation (Husnan, 2015):

𝑇𝑉𝐴 =∑ 𝐶𝑜𝑚𝑝𝑎𝑛𝑦 𝑗 𝑠ℎ𝑎𝑟𝑒𝑠 𝑡ℎ𝑎𝑡 𝑎𝑟𝑒 𝑡𝑟𝑎𝑑𝑒𝑑 𝑎𝑡 𝑡𝑖𝑚𝑒 𝑡

∑ 𝐶𝑜𝑚𝑝𝑎𝑛𝑦 𝑗 𝑠ℎ𝑎𝑟𝑒𝑠 𝑜𝑢𝑡𝑠𝑡𝑎𝑛𝑑𝑖𝑛𝑔 𝑎𝑡 𝑡𝑖𝑚𝑒 𝑡

After processing the data, data analysis will be carried out. The steps taken are determining the level of significance, the level of significance chosen in this study is 0.05 (α = 0.05) with a confidence level of 95%. Next is to test the normality of the data using the Kolmogorov

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Smirnov, in this test the data will be considered normally distributed if the Asym value. Sig is more than 5% (sig> 0.05), if (sig <0.05) then the data is not normally distributed. After carrying out the normality test, it can be continued by conducting statistical tests, if the data is normally distributed, the statistical test used is the Paired Samples t-test or paired t-test difference, if the data is not normally distributed, the Wilcoxon test will be carried out.

4. Discussion & Conclusion

The period of the event pliers used in this study was 5 days before the event and 5 days after the event. The announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia occurred on March 2, 2020. Thus, the research period is 24 February 2020 to 9 March 2020 (excluding stock holidays).

The samples in this study were companies in the telecommunications sub-sector listed on the Indonesia Stock Exchange with the criteria of having complete and consistent company data in the telecommunications sub-sector and not carrying out corporate actions during the study period.

Table 1: Sample of Telecommunication Sub-Sector Companies

No Stock Code Name of The Issuer

1 EXCL XL Axiata Tbk

2 FREN Smartfren Telecom Tbk

3 ISAT Indosat Tbk

4 JAST Jasnita Telekomindo Tbk

5 TLKM Telekomunikasi Indonesia

Table 2: Average Abnormal Return of Shares in Sub Sector Telecommunication

Day N Before After

1 5 -0.00785338 -0.01544778

2 5 0.00630493 -0.00859463

3 5 0.00274359 -0.00421630

4 5 0.00798840 -0.01592227

5 5 -0.00656916 -0.01338142

Table 3: Average Trading Volume Activity of Shares in Sub Sector Telecommunication

Day N Before After

1 5 0.00226276 0.00166287

2 5 0.00193190 0.00251827

3 5 0.00197278 0.00071236

4 5 0.00140960 0.00234073

5 5 0.00148903 0.00400040

The results of the normality test using the Kolmogorov Smirnov test during the testing period are as follows:

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Table 4: Normality Test

One-Sample Kolmogorov-Smirnov Test Abnormal Return Before After

N 5 5

Normal Parameters^a,b Mean .00052288 -.01151248 Std. Deviation .007323872 .005004345

Most Extreme Differences Absolute .234 .246

Positive .234 .246

Negative -.219 -.189

Test Statistic .234 .246

Asymp. Sig. (2-tailed) .200^c,d .200^c,d

One-Sample Kolmogorov-Smirnov Test Trading Volume Activity Before After

N 5 5

Normal Parameters^a,b Mean .00181321 .00224693 Std. Deviation .000356945 .001209660

Most Extreme Differences Absolute .230 .211

Positive .218 .211

Negative -.230 -.131

Test Statistic .230 .211

Asymp. Sig. (2-tailed) .200^c,d .200^c,d

Based on the results of data normality testing, the average abnormal return and trading volume activity is 0.200, where the probability of significance is greater than 0.05, meaning that the two data are normally distributed. Because the two data are normally distributed, testing will be continued using the paired sample t-test.

Table 4: Comparative Test

Paired Samples Statistics for Abnormal Return

Mean N Std. Deviation Std. Error Mean Pair 1 Before .00052288 5 .007323877 .003275338

After -.01151249 5 .005004345 .002238011

Paired Samples Test for Abnormal Return Paired Differences

t df Mean

Std.

Deviation

Std. Error Mean

95% Confidence Interval

of the Difference Sig. (2-

tailed) Lower Upper

Pair 1 Before

- After .012035363 .007117332 .003182967 .003198028 .020872697 3.781 4 .019

Paired Samples Statistics for Trading Volume Activity

Mean N Std. Deviation Std. Error Mean Pair 1 Before .00181321 5 .000356945 .000159631

After .00224693 5 .001209661 .000540977

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Paired Samples Test for Trading Volume Activity Paired Differences

t df Sig.

(2- tailed) Mean

Std.

Deviation

Std. Error Mean

95% Confidence Interval of the Difference Lower Upper Pair 1 Before

- After -.000433711 .001128498 .000504680 -.001834926 .000967504 -.859 4 .439

Based on the test results on the output of paired sample statistics, which shows that there is a decrease in the average abnormal return after the event compared to before the event. This can be seen from the average value of abnormal returns before the event of 0.00052288 to - 0.01151249 after the event. In the second output, the paired sample test shows the difference in the average abnormal return after the event compared to before the event. The time before and after the announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia occurred, the sig value (0.019) <0.05. This means that statistically there is a significant difference in abnormal returns from before and after the announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia in telecommunications sub-sector companies listed on the IDX. This result is also in line with research conducted by Putri (2020) that the fluctuating value of the Rupiah due to COVID-19 has a significant difference in abnormal returns.

As for the trading volume activity test results, the test results on the output of paired sample statistics show that there is an increase in the average trading volume after the event compared to before the event. This can be seen from the average value of trading volume before the event of 0.00181321 to 0.00224693 after the event. In the second output, the paired sample test shows the sig value (0.439)> 0.05. This means that statistically there is no significant difference in trading volume activity from before and after the announcement of the first COVID-19 case in Indonesia by the President of the Republic of Indonesia in telecommunications sub-sector companies listed on the IDX.

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