Do Leading Macroeconomic Factors Impact on Optimal Portfolio Return in Indonesia ?

There were two objectives in this research. Those were to construct an optimal portfolio and to analyze the impact of inflation, Bank of Indonesia (BI rate), and Rupiah to US Dollars exchange rate to the optimal portfolio return in Indonesia. The constant correlation portfolio model and ordinary least square regression method were implemented. This research used the stocks from the consistently selected stocks in the Bisnis-27 Index from 2012 to 2016. Microsoft Excel 2010 was used to construct an optimal portfolio. Meanwhile, to compute the regression and statistical analysis, SPSS version 20 was utilized. The obtained results show that only the stocks from PT Telekomunikasi Indonesia, PT Kalbe Farma, PT Charoen Pokphand Indonesia, PT Bank Rakyat Indonesia, PT Bank Central Asia, and PT Bank Negara Indonesia are included in the optimal portfolio. In addition, from the three leading macroeconomic indicators, only exchange rate change (Rupiah to US Dollars rate of change) impacts the return of the constant correlation model portfolio in Bisnis-27 Index significantly and negatively.


INTRODUCTION
The Indonesian Stock Market has been showing growth in the past few years.As reported from The Indonesian Stock Market official website, Indeks Harga Saham Gabungan (IHSG -IDX Composite Index or formerly known as Jakarta Composite Index) had an increased rate of 15,32% in 2016 (Rachman, 2016).The average of the daily transaction in 2016 was valued around Rp7,5 trillion (Masyrafina, 2017).Meanwhile, Quddus and Indrastiti (2016) said it was only valued about Rp5,76 trillion in 2015.In fact, Indonesian Stock Market had the highest IHSG value in the Indonesian capital market history in the first half of the year 2017 which was at 5.910 (Melani, 2017).
Comparing to investing in time deposits and bonds, Indonesian Stock Market offers better returns.In 2016, the average returns of time deposits and government bonds were roughly 7% yearly (Kusuma, 2016).However, the Indonesian Stock Market had 15% of the return (Rachman, 2016).In 2016, Indonesian Stock Market returns were the fifth highest in the world and the highest in the Asia Pacific (Rachman, 2016).Based on the statistics, it is highly likely that investing in Indonesian Stock Market is very profitable.
There are so many stocks traded on Indonesia Stock Exchange.It will not be efficient and effective to buy all the stocks traded.It is also not optimal if the traders buy only one stock.An optimal portfolio by investing in a group of stocks is required to gain positive return and to get diversification (Septyanto & Kertopati, 2014).
The correlation model is used for constructing optimal portfolio.Elton et al. (2014) stated that this model relied on excess return to standard deviation (ERS) ratio.The excess return is the difference between the average return of stocks.It is with the return of risk-free rate.The basic assumption for this model is that the correlations between stocks are constant.This research constructed an optimal portfolio based on the Bisnis-27 Index.It is because the stocks within the Bisnis-27 Index are expected to have a positive return.It can be seen in the research by Mulyono (2015).The result indicated that Bisnis-27 Index return was highly and positively related to IHSG.Moreover, Bisnis-27 Index is one of the indexes in Indonesian Stock Market that consists of 27 selected stocks from various public companies.This index is managed by Harian Bisnis Indonesia in cooperation with PT Bursa Efek Indonesia (Rifaldy & Sedana, 2016).The stocks within the index are rearranged every six months.The new list of the stocks is published at the end of April and October every year.Moreover, the index can be seen at Indonesian Stock Market official website, www.idx.co.id,.
There are many researches about portfolio construction in Indonesia.Single Index Model, Constant Correlation Model and Markowitz Model are mainly used for the construction of optimal stock portfolio in Indonesia.For example, Septyanto and Kertopati (2014) found that banking stocks namely Bank Central Asia, Bank Negara Indonesia, and BMRI were included in the optimal portfolio.Meanwhile, Pratiwi and Yunita (2013) also found that banking stocks such as Bank Negara Indonesia, Bank Central Asia, and Bank Rakyat Indonesia were chosen in the optimal portfolio.Similarly, the findings in Paramitha and Anggono (2013), Kewal (2013), and Darmawan and Purnawati (2015) showed that at least one banking stock was selected in the optimal portfolio.In addition, Pratiwi, Dzulkirom, and Azizah (2014) found that PT Unilever Indonesia Tbk (UNVR) had the largest proportion in the optimal portfolio in Jakarta Islamic Index.Recently, Rifaldy and Sedana (2016) constructed an optimal portfolio in Bisnis-27 Index using Markowitz model.They concluded that the Bisnis-27 Index stocks could produce positive return above the market or IHSG.
Macroeconomic factors empirically can affect stock returns.It is as indicated by Artaya, Purbawangsa, and Artini (2014).This research will use leading macroeconomic variables in Indonesia such as inflation, Bank of Indonesia (BI rate), and Rupiah to US Dollars exchange rate (Kalra, 2012).The researchers want to analyze the impact of those factors on optimal portfolio return.However, the researchers cannot find similar research when the researchers use onesearch.idas a search engine.As a result, the researchers use the research that analyzes the impact of macroeconomic factors on stocks indexes in Indonesia.It will be the comparisons for testing the hypotheses.
The interest rate is an important indicator of the macroeconomic condition in a country.The interest rate released and announced by Bank of Indonesia or BI rate is a benchmark rate.It reflects a monetary policy of a country (Rachmawati & Laila, 2015).It is also called as risk-free rate since it is formally released by a government or a country.Thus, it cannot go bankrupt theoretically (Brigham & Houston, 2015).In 2016, the average BI rate was relatively stable around 6%, although it was relatively low (Kusuma, 2016).Baird in Dwivedi (2010) indicated that an increase in interest rate lessened investments but added savings.Moreover, Rachmawati and Laila (2015) found that the risk-free rate did not have significant influence on Indeks Saham Syariah Indonesia (ISSI -Indonesia Sharia Stock Index).Meanwhile, Mulyani (2014) concluded that BI Rate had the negative and significant effect to Jakarta Islamic Index.Based on the explanation, the first hypothesis used is as follows.
H 1 = BI rate affects the portfolio return negatively.
The other important factor that reflects a macroeconomic condition of a country is an exchange rate especially Rupiah to US Dollar exchange rate changes.High depreciation of Rupiah to US Dollars exchange rate negatively affects company's earnings capabilities.It means it takes more Rupiah to buy one Dollar.Some of the negative effects of such high depreciation are the high transportation cost since the majority of fuel supplies in Indonesia are still imported, and high production costs.Thus, it also makes imports more expensive.Then, high depreciation of Rupiah to US Dollars exchange rate affects the financial performance of a company and its stock returns (Kewal, 2012).Moreover, Murtianingsih (2012) indicated that Rupiah to US Dollar exchange rate had the significant and positive effect on IHSG.However, Kewal (2012) suggested that the exchange rate affected IHSG negatively and significantly.Thus, the second hypothesis is as follows.
H 2 = Exchange rate changes affect the portfolio return negatively.
In addition, high inflation is not an ideal macroeconomic condition in a country.It means that prices of domestic goods are going up rapidly.High inflation creates uncertainty for business and increases investment risk.According to Biro Pusat statistik (BPS) or Indonesian Central Bureau of Statistics (Deny, 2017), the inflation rate was 3,02% in 2016.It was the lowest inflation rate in the past five years.The acceptable level rate of inflation is 2-3% annually in developed countries and 4-5% in developing countries (Dwivedi, 2010).There are some negative effects of high inflation on companies' earnings capabilities.The volume of production may decline due to the decreased level of capital inflow from foreign capital.The foreign investment is less profitable because of rising costs.Moreover, it may also prevent businessmen from taking opportunities (Kennedy, 2011).Kewal (2012) found that inflation did not significantly IHSG.However, Haanurat (2013) agreed that inflation significantly and negatively affected the return of sharia stocks.Thus, the last hypothesis used is as follows.
H 3 = Inflation affects the portfolio return negatively.

METHODS
This research implements quantitative methods namely the constant correlation model for constructing optimal portfolio.Moreover, the researchers use secondary data from 2012 to 2016.The purposive sampling method is also implemented.All the data are acquired from finance.yahoo.com,www.idx.co.id, and www.bi.go.id.The data used are the stocks that are consistently selected in the Bisnis-27 Index from 2012 to 2016.It can be seen in Table 1.The data are the adjusted monthly close prices of the selected stocks from 2012 to 2016, IHSG from 2012 to 2016, the monthly interest rate of Bank Indonesia (BI Rate) from 2012 to 2016, the monthly inflation rate from 2012 to 2016, and the monthly Rupiah to US Dollars closing exchange rate from 2012 to 2016.To construct an optimal portfolio, the researchers use Microsoft Excel 2010.Meanwhile, to compute the regression and statistical analysis, SPSS version 20 is used.The research model can be seen in Figure 1.The optimal portfolio is the dependent variable, while exchange rate, inflation rate, and risk-free interest rate are the independent variables.(1) is the average monthly return of each stock, and P t is the price of the stock at the time (t).
Then, E(R m ) is the average monthly return of the market or IHSG.Moreover, σ i is the standard deviation of each stock.Meanwhile, σ m is the standard deviation of IHSG returns, and σ 2 m is the variance of IHSG returns.Next, βi is the beta of each stock, and αi is the difference between the average return of each stock and beta of each stocks times the average return of the market or IHSG.Lastly, σ 2 ei is a variance of αi.Second, after those parameters are calculated, the researchers compute ERS.ERS ratio is calculated by the following formula.
is the expected return of the stock.Moreover, R f is the risk-free rate (Bank of Indonesia), and σ i is the standard deviation of the stock.
(9) Third, after finding the ratio, the unique cut-off rate or C* and C i are obtained.The calculation for the C i in the constant correlation model uses the following formula. (10) The ρ ̅ is the correlation between stocks that is assumed to be constant.Then, the ρ ̅ is calculated as follows. (11) The recommended stocks to be invested are the stocks that have higher C i values than their respective ERS ratios.The unique cut-off rate or C* is the highest C i value.Fourth, after finding the C i and unique cutoff rate or C*, the researchers try to find the weight of each stock or W i depending on the total weights of the portfolio.The total portfolio weight is always 100%.Then, the W i for the constant correlation model is calculated with this formula.
(12) (13) Last, it is to compute the expected portfolio return and standard deviation.The expected return calculation for the constant correlation model used the following formula.
The description is: As stated in Levine, Stephan, and Szabat (2014), the overall F-test will be implemented.It is to check whether the relationship between the dependent variable and the entire set of independent variables exist.The null and alternative hypotheses are as follows.
There is no linear relationship between the dependent variables and the independent variables) H 1 : At least one β j ≠ 0, j = 1, 2, …, k (There is a linear relationship between the dependent variables and at least one of the independent variables) H 0 is rejected at the α level of significance if It can be stated that H 0 is rejected at the α level of significance of F STAT > F α .If it is the other way around, it does not reject H 0 .

RESULTS AND DISCUSSIONS
This portfolio model relies heavily on the ERS ranking as the stocks selection process.Table 2 shows that three stocks have negative ERS values.Thus, UNTR, INTP, and SMGR stocks will be omitted.Only 11 stocks out of 14 stocks will be included in the next calculation to construct an optimal portfolio because they have positive ERS values.The portfolio model is constructed based on the assumption of constant correlation between each stock.Table 3 shows that the values of ρ ̅ are 2,3125.
Table 6 shows the descriptive statistics of this research.Based on the data, the average optimal portfolio returns from 2012 to 2016 is 2,47% monthly.It is with the maximum value at 29,1%.Meanwhile, the minimum optimal portfolio return is -11,49 % a month.It means that this portfolio can be expected to yield around 29,6% yearly.Furthermore, the average monthly BI rate is 0,5656% or 6,78% yearly, while the minimum of BI Rate is 0,48% or 5,76% yearly.The average monthly inflation rate is 0,4455% or 5,3% yearly.This result conforms with the theory stated by Dwivedi ( 2010).The acceptable level rate of inflation is 2-3% annually in developed countries and 4-5% in developing countries.Moreover, the average monthly depreciation of Rupiah to US Dollars is 0,6893% or 8,27% yearly.Based on this statistics, the research is conducted in the relatively stable macroeconomic condition in Indonesia.The result of linearity, independence of errors, the normality of errors, and equal variance tests of the regression model is in Table 7.The Durbin-Watson test shows that the D value is 2,419, while the Du from the Durbin Watson is 1,69 (Levine, Stephan, & Szabat, 2014).This regression model conforms with the independence of errors assumption since the D > Du.The table also shows the result of VIF calculation.All calculated VIF values from BI Rate, exchange rate changes, and inflation variables are below 5. Thus, this model is in line with the linearity assumption.Moreover, The Glejser test shows that the significance values of all independent variables are above the ∝ value which is 5%.It means that the model is in accordance with the equal variances assumption.Lastly, the one-sample Kolmogorov-Smirnov test shows that the Asymp.significance (2-tailed) value (0,329) is also above the ∝ value which is 5%.It implies that the model conforms with the assumption whose residuals are normally distributed.The regression equation result is as follows.
The result of regression analysis can be seen in Table 8.Using 0,05 level of significance, the critical value of the F distribution with 3 and 56 degrees of freedom is approximately 2,84 (Levine, Stephan, & Szabat, 2014) The result also shows that the BI rate affects the portfolio return negatively.However, the negative effect of BI rate on the portfolio return is not significant.It is based on its p-value (0,1053).It is higher than the confidence level of 5%.Thus, H 1 is rejected.This result is not in line with findings by Mulyani (2014), Nugroho andTrinandari (2017), andSilim (2013).They concluded that risk-free rate had the negative and significant effect.
Then, the variable of exchange rate changes affects the portfolio return significantly and negatively.It is based on its p-value (0,0068).It is significantly lower than the confidence level of 5%.Thus, H 2 is accepted.This result is consistent with finding by Nugroho and Trinandari (2017).They analyzed the effect of Rupiah on US Dollars exchange rate changes, BI rate, and inflation rate to the optimal portfolio return of Jakarta Islamic Index Stocks in 2012-2016.Additionally, Kewal (2012), Silim (2013), and Rachmawati and Naila (2015) also indicated that the exchange rate changes affected IHSG negatively and significantly.However, it contradicts with Murtianingsih (2012) who suggested that Rupiah to US Dollar exchange rate had a significant and positive effect on IHSG.
Moreover, the inflation factor has a positive effect on the portfolio return.However, it is not significant that its p-value is 0,2162.It is significantly higher than the confidence level of 5%.Thus, H 3 is rejected.This result is not in line with Haanurat (2013).Haanurat (2013) said that inflation affected the return of sharia stocks significantly and negatively.Nevertheless, this result is similar to Murtianingsih (2012) who stated that inflation had the positive and insignificant effect to IHSG.

Figure 1
Figure 1 Research Model standard deviation for the constant correlation model is calculated with the following formula.(15) After constructing the efficient portfolio based on the model, the next step is to analyze the effect of macroeconomic factors on the model.Three leading macroeconomic indicators are used.Those are BI rate, Rupiah to US Dollar exchange rate, and inflation.This research uses the ordinary least squares model.Levine, Stephan, and Szabat (2014) stated that the necessary assumptions for this regression are linearity, independence of errors, the normality of errors, and equal variance.Moreover, Ghozali (2013) stated several methods to test the assumptions.The methods could be the Durbin-Watson test, Glejser test, variance inflation test, and one-sample Kolmogorov-Smirnov test.The ordinary least square regression model of this research was as follows: portfolio of 60 monthly returns from 2012 -2016 β 0 = Constant β 1 to β 3 = Regression coefficients from the first to the third independent variables X 1 = Monthly risk-free interest rate (BI Rate) from 2012 to 2016 X 2 = Monthly changes in Rupiah to US Dollar exchange rate from 2012 to 2016 X 3 = Monthly inflation rate from 2012 to 2016 e i = Residuals

Table 1
The Bisnis-27 Stocks Used As A Sample

Table 4 C
i Values with Constant Correlation Model

Table 5
Portfolio Weights, Expected Return, & Standard Deviation of the Model

Table 6
Descriptive Statistics . From Table 8, the F STAT test statistic in the ANOVA summary table is 3,89.Since 3,89 > 2,84 or the p-value is 0,0135 < 0,05, the H 0 is rejected.Do Leading Macroeconomic Factors Impact.....(Bayu Adi Nugroho et al.) can be said that at least one of the independent variables (BI rate, exchange rate changes, inflation) is related to portfolio return.The adjusted R-Square is only 12,82%.It means that approximately 77% of other variables are affecting the portfolio returns.
b. Calculated from data.It

Table 8
Regression Statistics