CC BY
104
DOI https://doi.org/10.18551/rjoas.2017-11.29
THE EFFECT OF MACROECONOMIC AND RISK FACTORS TOWARDS STOCK RETURN OF INDONESIA INDUSTRIAL SECTOR IN 2008 TO 2015
Gunawan Martin*, Tanusdjaja Hendang, Ruslim Herman
Faculty of Economics, Tarumanagara University, Jakarta, Indonesia *E-mail: mar gun 87@yahoo.com
ABSTRACT
The study about stock is to determine whether risk and macroeconomic factors can affect stock return in a population of all industrial sectors in Indonesia. The stock investment does not save money in a short-run, and then expect immediate return, but it is also a long-run investment which should be analyzed using good business model. However, behind the capital market development, people are still more interested in using money for operational activities than for an investment. Moreover, they think that it is more beneficial to invest for saving than for stock because the percentage of interest offered to customers is definitely higher than the return stock's. In this study, multiple regression method in Eviews 8 is used. Besides, the variables consisting of non-systematic risk variable involving beta stock and macroeconomic variable involving inflation, interest, and exchange rate are involved in the hypothesis model to answer whether there is an effect of the variables as a stock return estimator during 2008 to 2015. From 259 issuer samples in all sectors, it is found that the macroeconomic variable changes can simultaneously explain the fluctuation of stock return. The result of each specific sector shows that stock return can be predicted using exchange rate, inflation, and interest.
KEY WORDS
Macro-economy, risk, stock return, industrial sector.
Indonesia is a country which has adapted the capital market of Netherlands since 1912, but its condition and form of capital market are still young (Steven, 2013). The capital market products are able to give return from high investment which is not similar to other markets in Asia, America, and Europe (Jogiyanto, 2003); thus, the products of Indonesian capital market are more hunted and run by foreign investors than locals (Sulistio, 2016). In the twenty-fifth, Indonesia Stock Exchange (IDX) had showed investment's products in the capital market, such as portfolio, mutual fund, and bond. However, a problem appeared in the capital market was that when the products were launched in the exchange market, they were not fully understood by people who majority have low information about capital market (Merawati and Putri, 2016).
The main point is that a good investor will realize that stock investment does not save money in a short-run, and then expect immediate return, but it is a long-run investment which should be analyzed using good business model. As a funding feature and funding management, capital market has produced blue chip Company in its development. However, behind the capital market development, people are more interested in spending money for operational activities than for investment. Moreover, they think that saving investment is more beneficial than stock because the percentage of interest offered for customers is definitely higher than stock return (Kusmawati, 2011).
Besides those concepts, the quality of investors run in the capital market tend to be trader-like and follow people who analyze of negative price and short-run expectation which value is small but in a big quantity to be able to get stock return (Cooper, 2013). These investors prefer investing low price in stock split event, but they are placed in high-liquidity corporations as a hedging concept to protect their money while investing (Ahmad and Halim, 2014; Gomez and Yague, 2005).
There are a lot of studies conducted in Indonesia to find out any factors affecting the stock movement. Practitioners of fundamental and technical investor analysis have described some ways to predict the value of stock in certain period and pattern. Their analyses are: the
analysis of market reaction towards a portfolio in a form of hypothetical market and stock risk (Jemmy, 2012; Mutiara, 2012; Nurhayanto, 2011), the analysis of stock towards macroeconomic condition, events and its country development (Adtyara, 2012), and the progress of company's performance in generating stock return for its investors (Indayani and Yahya, 2013). They are some examples of stock analysis research which are conducted to find out predictors of stock movement. The book-to-market performance ratio can predict return and risk of cash flow uncertainty which can produce predictor return (Lewellen, 2000). The interest rates, the number of spread between high and low obligation, and dividend rate can predict time variation from expected return (Fama et al., 1977; Keim and Stambaugh, 1986; Fama et al., 1898; Kothari and Shanken, 1997)
The concept of this research is obtained by the writer from the various results of previous studies in predicting stock return in Indonesia. In 2004 to 2008, stock return was not affected by liquidity, profitability, and dividend in LQ45 index (Deitiana, 2011). In 2008 to 2013, the cash flow and profit development simultaneously affected stock returns in hundreds manufacture companies in Indonesia Stock Exchange (Uluipuli, 2007; Suhemi, 2015; Ginting, 2011). It is found that the cash flow of funding activities which affected stock abnormal return was on the manufacture population in 2008 to 2011 (Nelvianti, 2013). During 2011 to 2014, profitability affected return, whereas growth and liquidity did not affect the return of 116 companies of property and real estate sectors (Anggrahini and Priyadi, 2016).
Based on the results of previous studies, the writer was inspired to make this research which purpose is to answer problems obtained from difference findings using macroeconomic and risk variable. Besides, the writer wants to know whether macroeconomics and risk affect stock return in 2008 to 2015. It is expected that the benefits of this study can contribute knowledge relating to some factors which can predict the price of stock of industrial sectors in Indonesia investment.
METHODS OF RESEARCH
The characteristic used by the writer in this study is purposive sampling method with applied research design (Nasution and Usman, 2007), a kind of research used to answer problems, and then use the result of the study in the following implementation. Then, it is obvious that the explanation used in this study is qualitative and quantitative method (Nachrowi and Usman, 2006). The variables of this research are: 1) Stock return measured from the stock price in year one to the previous year; 2) Stock beta or systematic risk of company measured from the covariant and variant per issuer; 3) The rate of three-month interest rate from Jakarta Interchange Bank Offer Rate (JIBOR); 4) The median rates of Rupiah towards USD by Bank of Indonesia, and 5) The percentage of inflation measured from Consumer Price Index by Central Bureau Statistics. The analysis of financial report content is used to obtain index from the research variables.
The writer collected data population of dependent variables from 505 issuers registered from each Indonesian industrial sector. The scope of the years in this research is limited to information about interest rate from JIBOR which was available on www.bi.go.id in 2008 to 2015. The survived issuers during this research were 259 issuers or about 51.29% who was then used as the samples of this study. The framework of research variables and hypothesis about the relationship between variables and research models is figured and formulated as the following.
STPR = a + p1 BETA + p2INFL + p3EXCR + p1 INTR + e (1)
Where:
STPR = Stock return BETA = Stock beta INTR = Interest rate INFL = Inflation rate EXCR = Exchange rate
The writer uses Eview 8 with dated panel (Gujarati, 2004) as the test device and format of analysis from monthly data of monthly research variables. The analysis of multiple linear regression equation with least square model least and spurious-testing analysis are done in all research models. The data analysis are done to answer problems in which: 1) the regression on the model is to know that all variables simultaneously affect return in all industrial sectors; 2) the regression in each industrial sector model is done to know more details about the specificity and characteristics of the research variables in each sector.
RESULTS OF STUDY
Investing decision of an investor can be motivated by his understanding towards investment ranging from the type of investment, returns to be gained, risks encountered, to other matters related to the investment itself. Knowledge about investment can be obtained from anywhere, such as formal education including in college and non-formal education including training (Sharpe, 2005). Investors should know that stock investment can be done by knowing stock market information reflected by good corporate governance (Rahmawati and Handayani, 2017) and commitment from current funding sources by expecting greater future funding sources (Bodie et al, 2004) and to know macro and micro risk factors influencing stock, such as economic growth, inflation, exchange rate, capital structure, and asset levels (Maga et al, 2016).
Table 1 - Research Sectors
Sector Issuer Total Issuer Coverage
Trade, Service and Investment 53 126 58%
Finance 47 84 44%
Basic Industry and Chemistry 39 68 43%
Various Industry 29 38 24%
Consumption goods Industry 26 40 35%
Property and Real Estate 25 63 60%
Utilities and Transportation Infrastructure 20 60 67%
Mining 15 42 64%
Agriculture 5 15 67%
Total 259 536 52%
Based on the research samples in Table 1, the trade and service industrial sector from 2008 to 2015 (production and consumption goods, hotels, restaurants, and tourisms, and printings) and finance sector are industries with the largest entity in Indonesia and for the infrastructure, property, mining, and agriculture sector, they have the highest data coverage on Indonesia Stock Exchange in this research. From the data, retail sector or consumption goods industry is the industrial sector with the lowest number of issuer coverage in this study (surviving from 2008 to 2015).
However, in reality, the consumption goods sector, such as food and beverage, pharmacy, cosmetics and household goods, household appliances and tobacco dominate the stock market which indicates that the majority of every issuer is engaged in those industries because they are profitable, having high stock value, and the sectors are mostly demanded by business owners to establish business and by investors to invest their capital. The finance sector, such as banks, securities market and its financing is also a sector with the largest number of issuer companies although it is not a sector with the highest stock value.
An industrial sector in Indonesia having the highest stock return in exchange is consumption goods sector which the average growth of stock returns reaches 6.1 times of 2.455 becoming 17.465. In this sector, the developments of stock return are highly increase and steep from the increasing development as much as 6% up to 186% in 2008 to 2014. The in each industrial sector of Indonesia can be seen in table 2 above. The stock returns in industrial sectors in Indonesia have the development average which is increasing during the years of the research. The average of stock return development in each industrial sector in Indonesia can be seen in the Table 2.
Table 2 - The Average of Stocks of Each Industrial Sector in 2008 to 2015
Industrial sector 2008 2009 2010 2011 2012 2013 2014 2015
Consumption goods Industry 2,455 3,395 9,726 12,884 18,025 25,239 26,697 17,465
Agriculture 3,866 3,934 4,675 4,718 4,547 4,163 5,374 4,237
Mining 1,535 1,435 1,877 2,006 1,644 1,302 1,352 901
Utilities and Transportation Infrastructure 813 721 760 713 790 857 892 909
Finance 624 728 1,145 1,375 1,494 1,694 2,005 2,020
Basic Industry and Chemistry 611 633 883 1,084 1,225 1,392 1,378 1,186
Various Industry 428 405 719 1,132 1,358 1,380 1,368 1,157
Trade, Service and Investment 360 368 515 766 1,065 1,147 1,236 1,188
Properties and Real Estate 339 323 370 550 741 1,339 1,590 1,636
Average 832 935 1,796 2,305 2,951 3,791 4,062 3,033
Source: Researcher data (2017).
The writer's analysis about the rising of stock return of consumption goods sector is explained from the addition of retail outlets in Indonesia, either it is in whole seller or franchise and small retail located around housing and settlement which support the distribution of products and increasing company's financial performance in this sector, excluding the economic condition. The agricultural sector in the post-crisis in 2008 had received subvention from the government by adjusting the State Budget in 2009. In the finance sector, the slackening business activities and widespread termination of employment increase the bank of non-performing loan, and in the future, it will hold banks in disbursing credit (Tjahjono et. al., 2009).
The downward movement of the mining sector's stock return shows that Indonesia's mining sector consisting of coal, oil and gas, metals and minerals and other subsectors has declining stock price from 2012 to 2015. One of the explanations of the stock sector declining was caused by Constitution No. 4 in 2009 about minerals and coals without special treatment within 4 years which required each sector entrepreneur of mining to build mineral purification construction or smelter to produce processed-products before selling it to the international market (non-raw export).
The utility and transportation infrastructure sector with energy subsector have increased because of raising export, transportation subsector having raising stock return in 2012 to 2015; one of them is caused by technological advances in global positioning system increasing the needs of transportation. On the other hand, the real estate sector is the sector with the lowest stock return due to the fundamental factor of its industrial sector is the sector which tends to keep the solvability more than the liquidity, have capitalization and high expansion, and move in long-run context. From the nature of business, the stock of property industry is the lowest stock among all sectors.
Table 3 - Indonesia Inflation Rate in 2008 to 2015
Period
2008
2009
2010
2011
2012
2013
2014
2015
January
February
March
April
May
June
July
August
September
October
November
December
158.3% 159.3% 160.8% 161.7% 164.0% 110.1% 111.6% 112.2% 113.3% 113.8% 113.9% 113.9%
113.8% 114.0% 114.3% 113.9% 114.0% 114.1% 114.6% 115.3% 116.5% 116.7% 116.7% 117.0%
11 11 11 11 11
8.0% .4% 8.2% .4% .7% 119.9% 121.7% 122.7% 123.2% 123.3% 124.0% 125.2%
126.3% 126.5% 126.1% 125.7% 125.8% 126.5% 127.4% 128.5% 128.9% 128.7% 129.2% 129.9%
130.9% 131.0% 131.1% 131.3% 131.4% 132.2% 133.2% 134.4% 134.5% 134.7% 134.8% 135.5%
136.9% 137.9% 138.8% 138.6% 138.6% 140.0% 144.6% 146.3% 145.7% 145.9% 146.0% 146.8%
111.0% 111.3% 111.4% 111.4% 111.5% 112.0% 113.1% 113.6% 113.9% 114.4% 116.1% 119.0%
118.7% 118.3% 118.5% 118.9% 119.5% 120.1% 121.3% 121.7% 121.7% 121.6% 121.8% 123.0%
Average
132.73% 115.06% 120.97% 127.45% 132.90% 142.18% 113.22% 120.42%
Source: Central Bureau of Statistics: Percentage of Consumer Price Index 2008-2015.
The Indonesian inflation movement summarized in Table 3 resembles the wave which
increases to the point in May 2008 reaching 164.01%, decreases in the next month, and continue to increase to the highest peak in 2013 before declining in 2014. This inflation volatility was caused by the rising of world oil and fuel price. The rising inflation in 2008 was also caused by rising world food commodity price (Kompas, July 25, 2008) and raising volume of vehicles (Darmadi, 2011; Gunawan, 2014). The condition of global economic crisis in 2008 occurred in Indonesia was preceded by a subprime mortgage or crisis of low-quality housing loan in the United States, corporate bankruptcies, such as Lehman Brothers and AIG (Sugema, 2012).
In Indonesia, the inflation is triggered by the decline of the balance of trade due to the low rate of Indonesia exports. Inflation began to creep down to the lowest point in June 2008 to 2013. By the end of 2013, the highest inflation was 146.8% which was caused by the rising fuel and electricity price (Bagi, 2017). The decline in inflation after its peak in 2013 came after the government implemented an accelerated quota of imports from products with declining price, such as meat and spices (Jacobs, 2013).
The development of inflation is in line with the development of Indonesian exchange rate. The exchange rate of rupiah towards US dollar as the exchange rate becomes the benchmark of the majority of companies and economic trade in Indonesia. The average exchange rates which increased from January 2009 to 2013 were a form of currency stability protection towards the price of goods and services as well as the stability towards other currencies. The first aspect was reflected in the development of the inflation rate, while the second aspect was reflected in the development of the rupiah exchange rate towards other currencies.
Table 4 - The Rates of Rupiah Exchange Rate towards United States Dollar in 2008 to 2015
Period
2008
2009
2010
2011
2012
2013
2014
2015
January
February
March
April
May
June
July
August
September
October
November
December
9,406.35 9,181.15 9,184.94
9.208.64 9,290.80 9,295.71 9,163.45 9,149.25
9.340.65 10,048.35 11,711.15 11,324.84
11,167.21 11,852.75 11,849.55 11,025.10 10,392.65 10,206.64 10,11.,33 9,977.60
9.900.72
9.482.73 9,469.95 9,457.75
9,275.45 9,348.21 9,173.73 9,027.33 9,183.21 9,148.36 9,049.45 8,971.76 8,975.84 8,927.90 8,938.38 9,022.62
9,037.38 8,912.56 8,761.48 8,651.30 8,555.80 8,564.00 8,533.24 8,532.00 8,765.50 8,895.24 9,015.18 9,088.48
9,109.14 9,025.76 9,165.33 9,175.50 9,290.24 9,451.14 9,456.59 9,499.84 9,566.35 9,597.14 9,627.95 9,645.89
9,687.33
9,686.65
9,709.42
9,724.05
9,760.91
9,881.53
10,073.39
10,572.50
11,346.24
11,366.90
11,613.10
12,087.10
12,179.65 11,935.10
11.427.05 11,435.75 11,525.94 11,892.62
11.689.06 11,706.67 11,890.77 12,144.87 12,158.30 12,438.29
12,579.10 12,749.84 13,066.82 12,947.76 13,140.53 13,313.24 13,374.79 13,781.75 14,396.10 13,795.86 13,672.57 13,854,60
Average 9,692.11 10,407.83 9,086.85 8,776.01 9,384.24 10,459.09 11,868.67 13,389.41 Source: Bank of Indonesia: The average Rupiah Exchange Rate towards United States Dollar in 2008-2015.
Table 4 shows the interest rate of Bank of Indonesia in 2008 was the highest interest rate which average was 9.37%; it was a form of government policy to anticipate crisis and reflect actual credit condition. Its increase was the government response towards the economic crisis and high interest rates from other debt instruments. The decline of the highest interest rate after 2008 was government's policy to change the reference of loan savings in Indonesia.
In relation to the research, the interest rate which can be measured by interest rate of Bank of Indonesia, JIBOR, as well as the percentage of bond interest loan as a product of capital market is the fluctuated research variable (Mutiara, 2012; Pangemanan, 2013). The interest rate set by the government from Bank of Indonesia is macroeconomic variable described in Table 5 as a variable with high volatility, and then adjusted to the movement of loans and deposits based on the interest rate of Bank of Indonesia certificate.
Systematic risk of the industrial sectors in 2008 had an average value below one (average stock beta 0.45) indicating the company's defensive stock movement, and it did not follow the movement of Jakarta Composite Index (JCI) during the economic crisis. Companies were not responsive towards the JCI which began to rise up after the economic crisis in 2009 to 2011, especially agricultural sector with beta value above one. The measurement method of stock beta (Sarumaha, 2015) in the study is a variable in a company which can be affected by macroeconomic variable and corporate fundamentals.
Table 5 - The Movement of Interest Rate of Indonesia in 2008 to 2015
Period 2008 2009 2010 2011 2012 2013 2014 2015
Jan 7.99% 10.68% 6.71% 6.28% 4.46% 4.23% 6.63% 6.26%
Feb 7.97% 9.42% 6.69% 6.09% 4.14% 4.60% 7.82% 6.10%
Mar 7.98% 8.87% 6.67% 6.67% 3.80% 4.16% 7.53% 6.29%
Apr 8.00% 8.40% 6.57% 6.54% 3.80% 4.59% 7.22% 6.21%
May 8.21% 7.95% 6.48% 6.90% 3.72% 4.36% 6.48% 5.91%
Jun 8.66% 7.43% 6.51% 6.25% 4.42% 4.56% 7.84% 6.29%
Jul 9.25% 7.10% 6.50% 6.86% 4.52% 5.45% 7.35% 6.10%
Aug 9.54% 6.79% 6.50% 5.34% 3.84% 5.15% 7.67% 6.62%
Sep 10.36% 6.71% 6.47% 5.40% 4.63% 6.75% 7.44% 7.02%
Oct 11.26% 6.72% 6.41% 5.58% 4.41% 6.37% 7.03% 7.65%
Nov 11.70% 6.72% 6.30% 5.18% 4.18% 6.89% 6.79% 8.23%
Dec 11.49% 6.74% 6.24% 4.75% 3.97% 6.75% 6.05% 7.21%
Average 9.37% 7.79% 6.50% 5.99% 4.16% 5.32% 7.15% 6.66%
Source: Bank of Indonesia: JIBOR quarterly 2008-2015.
The stock beta of each industrial sector during 2008 to 2015 can be seen in Table 6.
Table 6 - Beta Stock of Indonesian Industrial Sector 2008 to 2015
Sector 2008 2009 2010 2011 2012 2013 2014 2015
Various Industry -0.49 0.99 0.55 0.78 0.17 0.02 1.15 -0.89
Consumption goods Industry -0.45 0.86 0.70 1.20 1.03 0.20 1.47 -0.68
Basic and Chemical Industry -0.34 0.91 0.61 0.68 0.51 -0.01 1.75 -0.65
Utilities and Transportation Infrastructure -0.41 0.56 0.48 0.50 0.53 -0.24 2.80 -1.18
Finance -0.49 0.94 1.03 0.73 0.78 0.00 2.67 -0.69
Trade, Service and Investment -0.49 0.99 0.76 0.83 0.67 0.05 1.10 -0.70
Mining -0.39 0.92 0.67 0.55 -0.03 0.19 0.69 -0.85
Agriculture -0.42 1.27 1.05 1.08 0.75 0.28 0.62 -0.19
Property and Real Estate -0.50 1.05 0.61 0.54 0.87 0.01 3.00 -0.66
Average -0.45 0.93 0.72 0.75 0.61 0.03 1.81 -0.74
Source: Bank of Indonesia: quarterly JIBOR from year 2008-2015.
The results of research model from all sectors are as the following:
Stock Return = -0.89183 + 0.063672 BETA - 1,544872 INFL - 8.0300005 EXCR + 19.24832 INTR + 3.765577
In all sectors, the significant relationship that affects stock return is beta in positive and inflation in negative. Research model on all sectors have Rsquare value as much as 44.29%, and based on F test, the value is.007148 showing that independent variable simultaneously and partially influence the stock return. From the result, there is a significant correlation between each inflation and systematic risk variable towards the stock return across all industrial sectors in 2008 to 2015. The research model has met the requirements as an estimator without spurious relationship in which Durbin Watson value obtained from the equation is 1.999 which is greater than the R-square.
The explanation of this result also mentions that the predictor of the stock return is 55.71% by other factors, such as company's financial performance, trading volume, cash flow, and other non-financial factors, such as corporate reputation, auditor, or public ownership. From the result of this study, it can be explained that macroeconomic and non-systematic risk factors can affect stock returns during 2008 to 2015. Macroeconomic factors, such as inflation, interest, exchange rates and systematic risk simultaneously affect the return of company's stock.
In specific sector test, the significance test of the research model (F test) and significant variable test (T test) show that in each industrial sector during 2008 to 2015, all independent variables in the model simultaneously affect stock return. The summary of equation test result in each sector is presented as the following.
Table 7 - All sector and Specific Sector Test Result
Sector
R-square F Test
Durbin Watson
Whole sector
Various Industry
Consumption goods Industry
Basic Industry and Chemistry
Utilities and Transportation Infrastructure
Finance
Trade, Service and Investment
Mining
Agriculture
Property and Real Estate_
44,29% 0.007148 BETA, INFL
38,96% 0.000934 EXCR
30,38% 0.000005 INTR
55,47% 0.000003 EXCR
31,01 % 0.004361 BETA
71,23% 0.005203 EXCR
30,68% 0.000036 EXCR
43,23% 0.000375 BETA
38,76% 0.000654 BETA
48,12% 0.000036 INTR
1.9983 1.8700 1.2383 1.2168 2.0027 1.9233 1.6092 1.9226 1.9914 1.9243
DISCUSSION OF RESULTS
Based on result of the regression of each industrial sector, it is found that systematic risk has significant influence in estimating stock return for agricultural, mining and infrastructure sector. Sectors that control public needs and have specific buyers (such as fisheries, agricultural products, and mining products) make them have characteristics in their respective businesses. Changes in composite stock price index and other non-systematic risk factors will make company's characteristics reflect their stock returns. Moreover, exchange rates have a significant effect on the basic industrial sectors of chemistry, various industry, financial and service trade, and investment sector. In these industrial sectors, raw material required doesn't come directly from the origin country of the company. The purchase of financial services, chemical and other industries for trade needs makes the currency influence the operation of these sectors' issuers. The interest rate has a significant effect on the industrial sector of consumption goods and real estate property. In these industrial sectors, interest is the driving force because these sectors are a type of sector requiring loan funds to expand or pay suppliers, so the performance of their stocks is influenced by the interest rate.
The findings of this study confirm the empirical test results of macroeconomic and systematic risk variable on stock returns. Simultaneously, this research shows that inflation, interest, and exchange rate variable significantly influence the composite stock price index (Dodi, 2014). Inflation is assumed that it has negative influence towards Indonesia Composite Index (Nyoman, 2014) because the rising price will cause Indonesia Composite Index declines in purchasing power and stock fluctuation. The existence of independent variable besides macroeconomic in research model also shows that inflation, deposit interest rate, and stock trading volume have positive effect to stock return (Mirza and Nasir, 2011; Sutrisno, 2017; Indriastuti and Nafiyah, 2017; Ikkoku and Hosseini, 2008; Oshaibat, 2016; Majid, 2010). However, the results of this study show different things from other studies (Linzzy, 2017; Arika and Soedarsa, 2016) showing that macro-economy in this research has no effect on stock returns.
The volume of stock trading in this study is recognized to be closely related to the stock return. Associated with the theory of market efficiency (Fama, Eugene and French, 1988), the demand for an issuer's stock will lead to demand that increases price and return the stock. From the volume of trade and theory of market efficiency, the positive relationship between stock return and beta is explained based on Capital Asset Pricing Model theory. In equilibrium condition, stock return increases along with the increasing constant of beta or non-systematic risk.
In each specific sector, non-systematic risk, inflation, exchange rate, and interest have influence on stock return. The effect of exchange rates on trade, service, and investment sector and basic chemical industrial sector is along with a research in one of specific example on hotels subsector in 2012 to 2013 (Artini et al, 2015; Tommy and Mahilo, 2015). In hotels subsector, exchange rates negatively affect returns, while company's profitability variable positively affects return. Moreover, the interest rate positively affects return in 28 banking corporates in 2006 to 2008 (Mirza and Nasir, 2011) because the rising interest rate becomes conventional instrument to determine the value of stock in the future. The level of investment will be higher if the interest rate is high because the rate of return expected by investors will
increase from the rising interest. Furthermore, other non-economic factors, such as market reaction towards a particular event can also be a reference in determining stock return of other macro and microeconomic variables (Barus and Christina, 2014).
CONCLUSION
Based on the effect of economic condition in Indonesia and on the data collected by the writer, it is found that macro economy measured using consumer price index inflation, exchange rate of Rupiah towards United States Dollar, JIBOR interest rate, and systematic risk or beta stock of a company simultaneously affect the company's stock return in all industrial sectors. This study shows that variety of industrial sectors reach its stock return which can be estimated about 44.29% by macroeconomic factors. Then, for future research, the writer suggests the future writers to use non-systematic risk and other variables to show research models, such as: 1) the risk of each industrial sector; 2) Non-economy variables, such as management and corporate governance involving public ownership and managerial participants, and 3) Financial ratio reflecting the characteristics of each company.
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