Share price Valuation model of Automotive Company in Indonesia

— Stock price valuation is a common thing done by a public company that sells its shares on the Stock Exchange or a company that will conduct mergers and acquisitions. This study aims to build a valuation model for automotive companies in Indonesia that trade their shares on the Indonesia Stock Exchange. The design of this study uses proposed sampling data of automotive companies on the Indonesia Stock Exchange. The results of the multivariate price to earnings ratio model showed that return on assets (P = 0.0081 <0.5%) had a significant effect on price to earnings ratio while the other four variables dividend pay out ratio, cost of debt, debt to equity ratio, and risk (beta) the effect on the price to earnings ratio for automotive companies is less significant. The result of the determination test shows the R-square value = 0.1603 or around 16.03% the stock price is determined by the independent variable used in the study and the rest (83.97%) is determined by other factors this is because the variable used in this study is still purposed sampling of the financial historical data, so that researchers can then do valuations using variables other than those used in this study.


INTRODUCTION
The automotive market in Indonesia still has a growing potential because motorization rate is still low at level 82 compared to the global average condition which has reached 187 car units per 1,000 population (OICA: Organization Internationale des Consturctuerus d ' Automobiles, 2015). Table 1. Growth of Automotive Market (OICA, 2017) This condition makes many brands of vehicles enter to Indonesia market to get the opportunity to enjoy the growth of the automotive market in Indonesia. According to (Joyce per capita also has a relationship with an increase in the number of vehicles (Joyce Dargay, 2015) when income the per capita income is between $ 3,000, --$ 10,000, -the growth of vehicles is almost 2 times the growth of income while income per capita is $ 10,000 -$ 20,000 -growth is relatively the same as GDP growth.
Most of the companies on the Indonesia Stock Exchange (around 72%) offer their shares in a condition that is undervalued or lower than its intrinsic value (Paramitha et al., 2014) but other studies (Daljono, 2000), consider that company owners to avoid undervalued because of this will result in the transfer of wealth from the owner to the investor. This research will be interesting because it builds a model that will be used to assess the stock prices of automotive companies both those already on the Indonesia Stock Exchange and those that will make an initial public offering.

Location and Research Design
This research was conducted in companies listed on the Indonesia Stock Exchange. For this study begins with an analysis of the financial statements of 10 selected companies which are used as samples to determine the variables that will be used in the company's analysis to determine the intrinsic value of shares of automotive companies in the Indonesia Stock Exchange.

Table 2. Automotive Company in Indonesia Stock Exchange
The valuation model used is the valuation of the multivariate regression model of price to earnings ratio (PE) by using 5 independent variables calculated from the financial ratios of 10 automotive companies on the Indonesia Stock Exchange namely proxy risk (BETA), debt to equity ratio, cost of debt, dividend pay-out ratio and operation-return on assets.

Population and Sample
The population is 10 automotive sector companies ( Table  2) which are already on the Indonesia Stock Exchange which have automotive related business units both manufacturing, distribution and dealers. The method used is purposive sampling / non probability sampling method, which means that the selection of 10 companies is done by ignoring the principles of probability, and only looking at the desired elements of existing data and with specific intentions. The selected company is a company that has made an initial offer (IPO) before December 31, 2005 to obtain sample adequacy on valuation using a multivariate regression model.
Data collection for fundamental top down approach analysis is done by retrieving the data of the website of the institution and department related to the automotive industry.  In addition to the financial statements of the related companies researchers also took stock price data at the end of each month from December 2005 to December 2016 (133 data) for each company from https://finace.yahoo.com. Financial report data and stock prices that have been collected are then processed using Microsoft excels software to obtain financial ratios used for multivariate regression analysis, namely price to earnings ratio (PE), risk proxy (BETA), debt to equity ratio (DER), interest rate (I_R), dividend pay-out ratio (POR) and operation return on assets (ROA). Characteristics of samples and to assess the relationship of independent variables with PE were processed using Microsoft excels and EViews® 10+. As a comparison, the application of the model was chosen by two automotive companies in the Indonesia Stock Exchange that conducted IPOs in 2015 for the manufacturing sector, namely PT. Garuda Metalindo, Tbk (BOLT) and PT. Bintraco Dharma, Tbk (CARS) for the trade sector.

Sample Characteristics
The sample data period from 2006-2016 passed several economic conditions including the global financial crisis in 2008, commodity price boom between 2010-2012 and the decline in commodity prices in 2014. Conditions resulted in some stock returns and earnings being negative during the global financial crisis and when a significant decline in commodity prices. In this condition the researcher eliminated all that resulted in negative price to earnings ratio (PE) from the sample, so that out of 110 samples (10 companies x 11 years) were reduced to 70 samples.
Proxy Risk (BETA) is calculated based on the slope of the value of market return on stock returns of each company based on monthly data in a particular year (Table  9), debt to equity is obtained based on debt and equity data in the year-end balance sheet, the interest rate is calculated based on the interest rate on loans paid in a certain year (in the income statement) to the value of the debt at the end of the year, dividend pay out ratio is obtained from the dividend value paid for a given year (cash flow statement) to the value of earnings (income statement) and operation return on assets is calculated from EBIT value compare to total assets based on the annual report of each company.

IV. DISCUSSION
The results of this study are in line with previous studies which stated that most of the companies on the Indonesia Stock Exchange (around 72%) offered their shares in an undervalued or lower than their intrinsic value (Paramitha et al. 2014). According to the efficient market hypothesis that a valuation can effectively explain the stock price on the exchange if the stock is included in an efficient market. This was explained by Fama (1970) that an efficient exchange is if the value of an asset or stock has reflected all available information, including information that is private.

Valuation of multivariate regression models
The valuation model with multivariate regression is estimated using data from 10 automotive sector public companies on the Indonesia Stock Exchange (Table 1) and the resulting equation must be tested for classical assumptions before being declared feasible to be used as a model for the stock price valuation of automotive companies on the Indonesia Stock Exchange. The results of classical assumptions (linearity, multicollinearity, autocorrelation, normalization, heteroscedasticity) are all fulfilled. Table 8 shows the results of the linearity-Ramsay Reset Test test showing that the Prob F value (0.1389) is greater than the 0.05 alpha level (5%) so the regression model meets linearity assumptions.

Table 9. Multicolinierty test -VIF
Because the value of the VIF of the variable does not exist more than 10, it can be said that there is no multicolinerality in the independent variable.

International Journal of Advanced Engineering Research and Science (IJAERS)
[   Prob value. F count is greater than alpha level 0.05 (5%), so that based on hypothesis testing, H0 is accepted which means there is no autocorrelation. Table 11. NormalityJarque-Bera (JB) The results of the normality test using the JB (Jarque-Bera) method obtained a probability value of 0.879796 with a value of more than 0.05 (5%) meaning that the residuals were normally distributed. The last classic assumption test is heteroscedasticity test to find out whether the residuals and predictive values have a relationship or not, the results of testing using the Heteroskedacity test of Breusch-Pagan Godfrey, Prob value. F-statistic (F count) 0.2160 means that it is greater than the alpha level of 0.05 (5%) then H0 is accepted which means that heteroscedasticity does not occur.

International Journal of Advanced Engineering Research and Science (IJAERS)
[   (Table 7) shows the prob value. (F-statistic) 0.043592 is smaller than the error rate / error (alpha) 0.05 it can be said that the estimated regression model is feasible. Second, the t test in multiple linear regression is intended to test whether the parameters (regression coefficients and constants) that are supposed to estimate the equation / multiple linear regression model have been the right parameters or not. Right here is the parameter capable of explaining the behavior of independent variables in influencing the dependent variable. The results of the t test are seen in the prob value. t count for ROA 0.0081 <0.05 means that ROA has a significant effect on the PE value of the automotive industry at 95% confidence level while for other variables prob. t counts greater than 0.05 means that the effect is less significant. Finally, the coefficient of determination explains the variation in the effect of independent variables on the dependent variable. Or it can also be said as a proportion of the influence of all independent variables on the dependent variable. In this study because it uses R-Squared and Adjusted R-Squared to determine the coefficient of determination, it can be seen that the values of R-Square = 0.16028 and Adjusted R-Squared = 0.094513 means the independent variable [risk (BETA) free variable, Debt to Equity Ratio (DER), Interest Rate (I_R), Dividend Payout Ratio (POR) and Operation-Return on Assets (ROA)] affect the price to earnings ratio of 16.03% and the remaining 84.97% is influenced by other variables not in the regression variable.
Based on the classical assumption testing and also the reliability test of the multivariate regression valuation model, PE estimation equations obtained can be applied to the valuation of automotive companies in the Indonesia Stock Exchange. For this reason, researchers applied the model obtained to assess the initial stock price of two automotive companies that were IPOs in 2015 and 2017. The selected companies represented automotive companies from the manufacturing and trading sectors, namely PT. Garuda Metalindo, Tbk for the manufacturing sector which conducted IPOs on July 7, 2015 and PT. Bintraco Dharma, Tbk for the trade sector which conducted an IPO on April 10, 2017.   The implementation of the model in the valuation of stock prices in two automotive companies both in the manufacturing and trading sectors showed that both were undervalued, in line with previous studies (Paramitha et al., 2014). Empirical data also shows that stock prices have an increasing trend compared to the value of their initial share price when hold in the long term ( Figure 1 and Figure 2) in accordance with efficient market theory where share prices will follow the information available on the market.

V. CONCLUSIONS AND RECOMMENDATIONS
Researchers concluded that the model obtained in this study could be applied in the valuation of automotive companies in the Indonesia Stock Exchange, both automotive company in the manufacturing sector and also the trade sector, because they had met the classical assumption test and the determination test. Based on the independent variables that the researcher uses in this research shows that the level of influence on the estimated value is still relatively low, because the variables used in this study focus on financial statement variables that are influenced by various past factors, so that further researchers can develop using different variables not only variables obtained from financial statements but also external factors that can affect stock prices.