DETERMINANTS OF MACRO VARIABLES AND BANKING CHARACTERISTICS VERSUS RETURNS OF BANKING
SHARES
Tia Ichwani1, Nurul Hilmiyah2*, M. Nuruddin Subhan3
1,2,3Fakultas Ekonomi dan Bisnis Universitas Pancasila
*Corresponding Author: nurulhilmiyah@univpancasila.ac.id
Accepted: 20 February 2020 | Published: 29 February 2020
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Abstract: This article is aimed at unveiling whether or not macro variables, market returns and characteristics of banking industries influence returns of banking shares. This research is historical quantitative one that used macro variables data such as inflation rate, BI 7 day repo rate, the exchange rate of Indonesian Rp/US $, the amount of currency in circulation as well as return on the IHSG and banking credit variables during the research period of August 2016 to November 2018. Macro policies set by the government do not significantly affect banking shares. It is IHSG, inflation rate and credit variables only that have an influence on or relevance to returns of banking shares.
Keywords: Banking Stock Returns, CSPI, Market Returns, and Macro Variables
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1. Introduction
Indonesia is one of South-east Asia’s potential investment markets. Until the first quarter of January–March 2018, investment in Indonesia has reached an amount of Rp185,3 trillions which means that Indonesian target of Rp765 trillions in investment until that time has been reached (BKPM, 2018). There is an increase of about 4,3% in investment during January- September period of 2018 with respect to the same period of 2017 (kominfo, 2018).
Indonesia is referred to as the wolrd’s best second country for investment in 2018 after a hard effort of ensuring the world that Indonesia is a safe place for domestic as well as foreign investments. If climate for investment in a country is safe, what the investor candidates should consider next are macroeconomic variables such as interest rate, exchange rate, inflation rate, tax rate, currency being in circulation and economy cycle (Samsul, 2008). If economy condition in the destinated country of investment deteriorates, the investors will immediately respond to by taking their shares out. The investors are able to forecast the economy condition of an enterprise in which they will invest.
Monetary policy set by Bank Indonesia in the form of increasing interest rate will make a huge amount of society’s money flow to the banks in the form of saving so the amount of money being in circulation decreases. The decrease of money in circulation results in a bad growth of domestic economy which in turn causes the decrease in or absence of investment (Haruman & Komariah, 2009). Due to the decrease in investment, price of the shares will
10 decrease (Adisetiawan,2009). High rate of interest will increase company’s cost of capital and rate of return set by the investors (Kewal, 2010).
Rate of inflation influences as well the growth of shares prices. The higher the rate of inflation, the higher the prices of goods and the lower the society’s power of purchase. If the society’s power of purchase decreases, the prices of company shares decrease (Adisetiawan, 2009).
Banking industry is a main element of monetary sector. For relatively inconventional Indonesian economic system with respect to those of the developing countries, bank is an important agent for economic growth. Due to the important role of a bank in national economy, the relation between macroeconomic variables and performance of banking shares is of great interest to discuss and scrutinize.
As having been cited earlier, central tenet of this research is to unveil whether or not macro variables, shares rate of return and characteristics of industries affect banking shares in Indonesia. The data used in this research were those related to banking credits in Indonesia and to samples of return banking shares registered in LQ 45 during 2016-2018 period. The data are as follows.
2. Literature Review
Banking Characteristic
Banks are mediating monetary institution which operates by receiving society’s belongings in the form of savings, deposits, save deposit boxes, and giros and then convey them to the society in the form of loan for business or valuable papers.
Banks have specific functions that are different from those of other monetary institution (Kreiner, Noga Collins,.et all, 2007).
a. As trusted institution in which people save their money in safe condition, banks create money and payment system mechanism (Bank Indonesia).
b. As mediating monetary institution, bank conveys funds or savings to the society or enterprises for their business.
c. Banks are agents for financial assets investment and financial market improvement, particularly domestic and foreign financial markets.
Based on the three specified functions cited above, banking system has important micro and macro function. With its micro function, banking industry serves as a trusted institution in which people save their valuable belongings and from which they get loan for their small scale-business. With its macro function, banking system secures the stability of payment system and national economy either domestically or internationally by issuing payment means such as currencies and valuable papers.
Shares return
High risk high return. This motto, meaning the higher the risk the larger the profit an investor will earn, is a guide for investor in investment.
Shares rate of return is the main factor the investors seek in investment. It is the profit percentage an investor earns with respect to the capital she or he has invested in an investment (Hartono, 2017).
According to Chong’s (Chong & Goh, 2003) research, shares rate of return is an indication of macroenonomy condition of a country. In developing countries, rate of return fluctuates due to macroecomic factors such as rate of inflation, BI 7 Repo Rate and currency (Sundoro, 2018).
IHSG (Joint Shares Price Index)
Shares prices index consists of Individual Shares Price Index and Joint Shares Price Index.
Joint Shares Price Index is a reflection of shares prices movement in stock exchange. IHSG is used as reference or a barometer of economy condition of a country, mainly market condition. The better the movement of IHSG, the better the market condition of the country.
IHSG is a value used to evaluate the performance of shares in Indonesia Stock Exchange within a specified period (Hermuningsih, 2012). Research by other reseachers (Fitriyani, 2005;Putri, 2016) reveals that IHSG has a significant influence on shares rate of return, i.e., if IHSG increases, shares rate of return will increase, too.
Rate of Exchange
Rate of exchange, in addition to rate of inflation and rate of interest, is one of macroeconomic variables that affects volatility of shares price.
Besides the change in prices of imported and exported goods, IDR rate of exchange is influenced as well by other factors such as a change of people’s desire for goods, rate of interest and economy growth (Sukirno, 2011).
Research by Herdiningsih shows that rate of exchange has negative influence on shares rate of return (Hardiningsih et.al, 2002; Joseph, 2002). This is quite different from research carried out by another researcher which showed that the increase of rate of exchange in this case has positive influence on shares rate of return (Suciwati, 2002;Utami & Rahayu, 2003;
Saadah, 2016). It is concluded from the latter that if the rate of exchange increases, shares rate of return increases, too.
BI 7 Repo rate of interest
On August 19, 2016 Bank Indonesia (BI) publicized the change of BI rate of interest into BI 7 Day Reserve Repo Rate. BI adopts BI 7 Repo as new rate of interest. At the time, the price of banking shares falls because the investors are not sure of the effectivity of the new rate of interest and worry about the effect that possibly occurs owing to the change.
The movement of banking shares is closely similar to that of IHSG. The close similarity is due to the fact that most of banking shares have dominant influence on IHSG so they can dictate IHSG (Rahma, 2018). The change of the rate of return gives positive effect to the banking shares return, i.e., if the BI 7 Day Reserve Repo Rate decreases, the banking shares return will increase (Sundoro, 2018).
12 Rate of Inflation
Inflation refers to a continuous and common increase of prices in an economy (Sukirno, 2011; Nopirin, 1990).
The increase in prices in short times and discontinuous is not classified as inflation. There are three requisites for inflation to take place.
a. The increase in prices.
b. The increase of prices covers prices of all commodities consumed by society in all regions.
c. The increase of prices continuously takes place in a long period.
Inflation can be triggered as well by the increase of demand for gold, jewelleries and commodities related to infrastructures, the increase in electricity price, and teresterial, marine as well as air transportation cost. The increase in prices of education, staff and staple is another impetus of inflation . Research by (Ichwani et.all, 2017) shows that the decrease in rate of inflation is followed by the decrease in BI rate of interest. Research by another researcher shows as well that inflation has significant influnce on shares return (Hardiningsih et all, 2002;Boudoukh et. all, 1993;Titman, 1989). Research by Nurdin (Nurdin, 1999) reveals that inflation has negative influence on shares return.
Hypothesis
H0,1 = Market Performance (IHSG) influences the return of shares of banking industry.
H0,2 = Inflation influences of banking shares H0,3 = Banking credit influences of banking shares H0,4 = Rate of exchange influences of banking shares H0,5 = M2 influences of banking shares
H0,6 = BI 7 Day Reserve Repo Rate influences of banking shares.
3. Methodology
This research is a quantitative one and based on its function this research is historical
research using e-views statistical testing tool. Dependent variables in this research are return of banking shares (Y) and independent variables are IHSG (X1), rate of inflation (X2), credits (X3), rate of exchange (X4), M2 (X5) and BI 7 Day Reserve Repo Rate (X6).
The length of research period is 28 months, i.e., since August 2016 until November 2018.
Sampling is carried out using purposive sampling method and treated based on banking system data provided in LQ 45 list during research period.
The return of banking stocks is the return generated by banking stocks during the observation period, which is registered at IDX. The formula used is:
Ra,b,c,d,... =
Ra,b,c,d,... = banking stock returns Pt = Index value at time t Pt-1 = Index value at time t-1
4. Result
Normality Test of the Data
Parameters used for normality test of the data are jarque-berra test, skewness and curtosis.
Data are considered normal if skewness value approaches zero whereas its cutosis approaches three. In addition, normality of the data can be seen more immediately and accurately using their probability. The higher the value of the jarque-berra test, or if its probability < 0,05, hypothesis is rejeced or considered not normally distributed (Gujarati & Porter, 2010).
Table 1. Normality of the Return of Banking Shares and Indipendent Variability
St. Dev Skewness Kurtosis Prob J-Berra N
rBBCA 969,43 -0,05 2,25 0,72 0,65 27
rBBNI 641,94 0,14 4,20 0,43 1,68 27
rBBRI 192,41 0,06 3,32 0,94 0,12 27
rBBTN 309,05 -0,64 3,04 0,41 1,79 27
rBJBR 450,05 2,07 12,33 0,00 117,26 27
rBMRI 1341,99 -3,85 18,67 0,00 342,90 27
St. Dev Skewness Kurtosis Prob J-Berra N
rIHSG 52,12 -0,20 2,54 0,82 0,41 27
rInflasi 166,82 -0,41 3,79 0,48 1,47 27
rKredit 233,76 -0,92 6,36 0,00 16,56 27
rKurs 0,28 -0,13 2,36 0,77 0,53 27
rM2 52968,1 -0,73 3,77 0,22 3,03 27
rBI REPO 0,19 0,93 4,19 0,06 5,51 27
Source: E-views data processing.
Based on Table 1, there are four shares normally distributed, i.e., BBCA, BBRI, BBNI and BBTN shares. All indipendent variables are normaly distributed except banking credit variable. Data which are not normally distributed could be treated by one of the following three treatments, i.e., cut , discarded or left intact. In this research, data that are not normaly distributed are left intact as they are.
Multicolinearity test is intended to verify whether there is a correlation or not between independent variables used in research. The multicolinearity can be verified by arranging correlation matrice for each model of independent variables. This test uses the t-test due to a slew of data whose number is less than 30. Data whose number is more than 30 are tested using z-test.
Table 2. Correlation matrice of independent variables in model
rIHSG rInflasi rKredit rKurs rM2 rBIRepo rIHSG 1,00 0,223 0,147 0,392 0,438 0,163 rInflasi 0,223 1,00 0,001 0,173 0,236 0,073 rKredit 0,147 0,001 1,00 0,164 0,686 0,002 rKurs 0,392 0,173 0,163 1,00 0,104 0,661
rM2 0,438 0,235 0,686 0,104 1,00 0,150
rBIRepo 0,163 0,072 0,002 0,661 0,150 1,00 Source: E-views data processing
It can be seen in Table 2 that correlation coefficient between independent variables is relatively low. Correlation coefficient being more than 20% means significant whilst below 20% means insignificant. Plus-minus sign preceeding the correlation coefficient indicates positive/negative correlation between the tested variables. Variables that show positive
14 correlation are CREDIT versus M2 (0,686), SBI versus KURS (rate of exchange; 0,661) and M2 versus IHSG (0,438). Variables correlating insignificantly are also included in regression model as suggested by Gujarati. The pairs of variables cited later are CREDITS vs IHSG, BI Repo vs IHSG, CREDIT vs INFLATION, KURS vs INFLATION, BI Repo vs INFLATION, CREDITS vs KURS, KURS vs M2, and M2 vs BI Repo. All the eight pairs of variables have correlation coefficient less than 20%.
Stationary test is conducted to verify whether the data have already not been influenced by trend or follow random pattern that cannot be estimated. Test for this verification is Augmented Dickey Fuller Test (ADF).
Parameter used for confirmation is ADF absolute value with critical value of 1%. Data have been stationary when the absolute value is greater than critical value. This means that the data should not necessarily be transformed further and they can be used. If the data have not been stationary, they should be transformed by means of differential process until the absolute value ADF reaches a value greater than its critical value. Data that have been stationary can be easily seen from probabilities that are less than 0,0.
Table 3. Result of Stationary Rest (ADF Test)
No Variables ADF Critical Values (1%) Prob
1 rBBCA -5,01 -3,72 0,00
2 rBBNI -5,34 -3,72 0,00
3 rBBRI -3,61 -3,72 0,00
4 rBBTN -4,79 -3,72 0,00
5 rBJBR -4,83 -3,72 0,00
6 rBMRI -4,96 -3,72 0,00
Variables ADF Critical Values (1%) Prob
1 rIHSG -4,05 -3,72 0,00
2 rInflasi -6,06 -3,72 0,00
3 rKredit -5,49 -3,72 0,00
4 rKurs -4,39 -3,72 0,00
5 rM2 -1,02 -3,78 0,72
6 rBIRepo -0,81 -3,76 0,79
Source: E-views Data Processing
Table 3 show that most of the data have been stationary because their ADF absolute values are greater than their critical ones, respectively. Probabilities of 0 indicate that the data have been stationary, too. However, there are two data that are not stationary, i.e., M2 and BI 7 Day Reserve Repo. Data that are not stationary are neither transformed nor changed but left intact to see the interrelationship between dependent variables and independent ones as having been cited earlier. All data that will be used have therefore meet stationary condition.
Regression of Shares Return and Banking Shares Return
Table 4. Result of Market Shares and Banking Shares Return Regression Test
Intercept IHSG Adj Prob
No Emiten Koefisien Prob
(T-Stat) Koefisien Prob
(T-Stat) R
Squared (F – Stat)
1 rBBCA 303,44 0,03 4,18 0,00 0,52 0,00
2 rBBNI 28,78 0,74 2,76 0,00 0,51 0,00
3 rBBRI 25,03 0,29 0,91 0,00 0,62 0,00
4 rBBTN 1,09 0,98 0,94 0,00 0,23 0,00
5 rBJBR 4,85 0,95 0,40 0,45 -0,02 0,45
6 rBMRI -185,77 0,48 1,77 0,26 0,01 0,26
Source: E-views Data Processin
Based on calculation, banks whose return levels are affected by market returns are BBCA (0,00), BBNI (0,00), BBRI (0,00) and BBTN (0,00), respectively. Table 4 shows that most of market returns (IHSG) positively influence returns of banking shares, except BJBR and BMRI shares.
Accuration of the model in representing the shares return level is various as depicted by its respective adjusted squared R(s), i.e., -0,02 (BJBR) as the least value and 0,62 as the greatest one (BBRI). This indicates that liquidity of shares transaction at stock markets influences as well the selected model. Models that have been selected are substantially significant for four shares, i.e., BBCA (0,00), BBNI (0,00), BBRI (0,00) and BBTN (0,00).
Regression of Macrovariables and Banking Shares Return
Table 5. Result of Test of Influence of Macrovariables and Banking Shares Return No Emiten Intercep
t
rIHSG rINFLA SI
rKRE DIT
rKUR S
rM2 rBIRepo Adj R.
Squar ed
Prob (F- Stat)
Durbin Watson
1 rBBCA 286,19 3,84 -121,33 0,00 -1,06 -8,05 -197,63 0,56 0,00 2,28
Prob t-stat 0,43 0,00 0,79 0,03 0,11 0,05 0,78
2 rBBNI -32,81 2,81 91,37 0,00 2,74 -3,98 -113,68 0,46 0,00 2,09
Prob t-stat 0,78 0,00 0,78 0,09 0,51 0,21 0,83
3 rBBRI 5,24 0,76 64,44 0,00 -0,30 0,66 -33,88 0,68 0,00 1,92
Prob t-stat 0,84 0,00 0,41 0,66 0,01 0,35 0,78
4 rBBTN 11,43 0,68 18,77 0,00 -0,42 -0,15 -153,95 0,15 0,15 2,42
Prob t-stat 0,87 0,00 0,76 0,76 0,15 0,93 0,63
5 rBJBR -111,22 0,01 -702,96 -0,00 -0,56 5,33 -370,34 0,42 0,00 2,58
Prob t-stat 0,20 0,98 0,01 0,88 0,11 0,03 0,35
6 rBMRI -189,89 0,89 200 -0,00 -1,38 9,32 268,01 -0,02 0,50 2,08
Prob t-stat 0,58 0,63 0,83 0,36 0,33 0,30 0,09
Source: E-views Data processing
16 Equations of Multiple Linear Regression derived from Table 5 are given in the following Table 6.
Table 6. Multiple Linear Regression of Test of Influence of Macrovariables and Banking Shares Return.
BBCA Y = 286,19 + 3,84 X1 – 121,33 X2 + 0,0 X3 – 1,06 X4 – 8,05 X5 – 197,63 X6 BBNI Y = -32,81 + 2,81 X1 + 91,37 X2 + 0,0 X3 + 2,74 X4 – 3,98 X5 – 113,68 X6 BBRI Y = 5,24 + 0,76 X1 + 64,44 X2 + 0,0 X3 – 0,30 X4 + 0,66 X5 – 33,88 X6 BBTN Y = 11,43 + 0,68 X1 – 18,77 X2 + 0,0 X3 – 0,42 X4 – 0,15 X5 – 153,95 X6 BJBR Y = -111,22 + 0,01 X1 – 702,96 X2 - 0,0 X3 – 0,56 X4 + 5,33 X5 – 370,34 X6 BMRI Y = - 189,89 + 0,89 X1 + 200 X2 - 0,0 X3 – 1,38 X4 + 9,32 X5 + 268,01 X6
Source: E-views Data Processing
Based on Table 6, there are four shares whose independent variables affect significantly the dependent variables. Models that significantly explain the influence of independent variables on returns of banking shares are BBCA (0,00), BBNI (0,00), BBRI (0,00) and BJBR (0,00) models. Accuration of models is depicted by the adjusted squared r of each model which is the least for BMRI (-0,02) and the largest for BBRI (0,68).
5. Discussion
Table 5 shows that market return (IHSG) positively influences four banking shares and negatively influences banking shares of BJBR and BMRI . This is in line with the expected hypothesis that market return will positively affect return of banking shares.
H0,1 : H0 is accepted, market performance (IHSG) influences return of banking shares.
INFLATION variable positively influences four banks and negatively influences two banks.
This means that in general the inflation positively influences the performance of the banking shares return. As explanation, the inflation will lower people’s purchase power so they borrow money from the banks for their life. Increasing demand for consumptive credit portion through banks is a proof of this.
H0,2 : H0 is accepted, inflation influences banking shares.
CREDIT variables positively influence four returns of banking shares and negatively influence the rest. CREDIT influences significantly one banking share only, i.e., BBCA. This fact is in line with the hypothesis that credit will positively influence returns of banking shares because banks earn profit by lending professionally credits to the customers.
H0,3 : H0 is accepted, credit influences of banking shares.
KURS (the exchange rate) variables negatively influence five banking shares. This means that Indonesian rupiah strengthens with respect to US dollar. In other word, the strengthening of rupiah gives a positive effect to profit earned by the banking system. However, KURS variable gives no significant influence to any banking shares in this research. It can therefore be estimated that KURS variables do not affect performance of the returns of banking shares.
Bank Indonesia itself applies strict regulation as to Nett Foreign Exchange Position that can be extracted by the banks for the purpose of limiting the opportunity of a bank to earn profit through foreign exchange speculation. Neither increase or decrease of rate of exchange affects the performance of banking system.
H0,4 : H0 is rejected, KURS (rate of exchange) does not influence the returns of banking shares.
M2 variables, i.e., the amount of currency in circulation, negatively influence three banking shares but negatively influence three others. As the variables are significant only for one banking share, i.e., BBRI, it canbe concluded that M2 variables do not significantly affect the profit of the banking system.
H0,5 : H0 is rejected, M2 variables do not influence the return of banking shares.
BI 7 Day Reserve Repo variables positively influence one banking share but negatively influence five other banking shares. The variables are not significant for any bank. Due to the high market rate of interest set by BI Repo, the spread of banking cost along with its interest profit tends to narrow.
H0,6 : H0 is rejected, BI 7 Day Reserve Repo does not influence the return of banking shares.
6. Conclusion
In general, model of the research result can not sufficiently show significance level of the influence of independent variables on the return of banking shares. This is probably an indication of inefficient management of Indonesian Stock Exchange so that a lot of other variables that belong to it do not influence the performance of the return of banking shares.
The addition of macrovariables as independent variables into the model can not show significance in affecting the return of banking shares. This can be seen from the fact that there are only some shares whose returns are affected by the macrovariables. It can be concluded from the tested macrovariables that it is IHSG, inflation and credit only that have relation with the returns of banking shares; the rests, i.e., KURS variables, M2 and BI Repo Rate do not have any relation with the return of banking shares.
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