INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)

INTERNATIONAL JOURNAL OF MANAGEMENT (IJM) Proceedings of the 2 nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 ISSN 0976-6502 (Print) ISSN 0976-6510 (Online) Volume 5, Issue 8, August (2014), pp. 107-114 IAEME: http://www.iaeme.com/ijm.asp Journal Impact Factor (2014): 7.2230 (Calculated by GISI) www.jifactor.com IJM I A E M E ECONOMIC INDICATORS AND STOCK MARKET PERFORMANCE - AN EMPIRICAL CASE OF INDIA Kantesha Sanningammanavara 1, Kiran Kumar K V 2 1, 2 Asst. Professor, Department of MBA, Vidyavardhaka College of Engineering, Gokulam 3 rd Stage, Mysore-570002, India ABSTRACT This study attempts Movements in the stock market can be quite volatile and sometimes movements in share prices can seem divorced from economic factors. However, there are certain underlying factors which have a strong influence over the movement of share prices and the stock market in general. Within the framework of a Correlation Coefficient Model, the paper examines whether a number of macroeconomic variables influence stock prices in Indian Stock Market. A Correlation and regression analysis is applied in order to model the long-term relationship between GDP, Exchange rates, Inflation Rate, Gross Domestic Savings, Capital formation/investment and SENSEX in the Indian Capital market. The researchers found that except GDP, GCF and GDS no other indicators have positive influence on the SENSEX performance. They found r square is at 77.20% that means the stock market performance is explained by the said variables to the extent of 77.2% which is good to model the same. Keywords: BSE-Sensex, Exchange Rate, GDP, Inflation, Multiple Regressions. I. INTRODUCTION Volatility is the main worry for any investor in the stock market as their returns depend on various functions in the economy system. We know that the fundamental analysis it he part of any investment decision and in that the main part is economy analysis. More often the stock market performance reflects the economy of that country and other countries economy that it is associated with. The present study mainly covers prominent indicators of Indian economy and their influence on the stock market performance. It helps the most while taking part in the stock market that whether the investment analysis should really include the analysis of economy of that particular country and to what extent it matters on the stock market performance. 107

II. REVIEW OF LITERATURE Studies have shown that as a result of financial deregulation, the stock market becomes more receptive to domestic and external factors. It is evident from literature that the relationship between stocks returns and economic variables have received great attention over recent years in particular countries and economic conditions. The level of return achieved or expected from an investment is dependent on a variety of factors. The internal factors can be a type of investment vehicle, quality of management, type of financing etc., whereas those of external could include war, price controls, political events, interest rate, exchange rate and inflation among others. Geske and Roll (1983) found the linkage between macroeconomic variables and stock prices in USA but found it negative relationship between stock prices and inflation. Chen, Roll and Ross in 1986 found that the economic variables like industrial production index, change in risk premium and inflation have a systematic influence on stock return and showed the existence of a long run equilibrium relationship. However, they also found that oil prices and consumption did not have significant effect on stock prices. Mukherjee and Naka (1995) found that Japanese stock prices are linked to money supply, inflation, real economic activity, long term government bond rate, exchange rate and interest rate. Diamandis (2009) indicates that 4 selected Latin American stock markets including Argentina and the U.S. stock market exhibit 4 common permanent components, are partially integrated, and have relatively small benefits in the long run with international diversification due to very sluggish adjustments. Jawadi, Arouri and Nguyen (2010) find strong evidence that the Argentine and Mexican stock markets are influenced by the U.S. stock market in the short run whereas there are no linkages found in the long run. Hence, they conclude that stock markets in Argentina and Mexico are determined by the fundamentals in the long run. Asian Stock Markets have been studied by Fung and Lie (1990), Leigh (1997), Granger, Huang and Yang (1998), Kwon and Shin (1999), Muysami and Koh (2000). In a study by Nath and Samanta (2003), he was found that the stock market and exchange rate were not generally co integrated in India and some amount of casual effect could be noticed only late in 1990s. In another study,nath and Samanta (2003), examined the changing pattern in extent of integration between foreign exchange and capital markets in India using daily data and found that in value at risk framework empirical results do not point much impressive causal relationship between returns except in some specific years. III. RESEARCH GAP The above extensive literature is about how the stock market is predicted with only two or three variables, however that gives us an opportunity to test the performance of stock market considering various economic indicators and also those literature is about all the advanced economies and this gives researcher to conduct research in the same area in emerging countries like India. The main research gap between present and existing research lies on the dimensions of number of economic indicators considered and time period of data. IV. OBJECTIVES OF THE STUDY The Following are the objectives of the study 1. To analyse the relationship between economic indicators on the stock market performance 2. To study what extent the economic indicators do influence the stock market performance 3. To propose a model for stock market performance 108

V. SCOPE OF THE STUDY This study covers the identification of major economic indicators in India and their effect on the stock market performance for a period of sixteen years. Based on their influence on the stock market performance, a model has been set to explain how economic indicators influence the stock market performance. This would definitely assist investors to understand the effect of Macroeconomic variables on stock indices and to plan their investment portfolio. Study will also help the companies to know their share prices fluctuations. VI. LIMITATION OF THE STUDY The following are the limitations of the study 1. The stock market performance is measured only through BSE Sensex 2. The time period of study is only sixteen years and only eight economic indicators considered for the study VII. RESEARCH METHODOLOGY A descriptive research is conducted selecting samples using convenience sampling technique. Variables are defined as below: o Dependent Variable (01) BSE Sensex o Independent Variables (08) - GDP Growth rate, Inflation rate (WPI), Exchange rate (Rs/USD), Gross Domestic Savings as % of GDP, Gross Capital Formation as of GDP, Real Interest Rate, Unemployment Rate and Net FDI in US$ million Secondary Data is collected to study the relationship between the Stock market performance and selected economic indicators. Time period Yearly data of variables From April 1998 to March 2014 Alternative Hypothesis: H 1 : There is relationship between stock market performance and economic indicators Statistical Tools Used: Mean, Standard Deviation, Correlation, Coefficient of Determination and Multiple Regression VIII. RESULTS AND DISCUSSION Table-1 in Annexure-I shows the yearly fluctuation of BSE Sensex and other economic indicators from 1998-99 to 2013-14. Figure-1 presents a graphical summary of yearly fluctuation of BSE Sensex and other economic indicators from 1998-99 to 2013-14. Table-2 shows the descriptive statistics of all the variables. The table shows the Mean and Standard deviation for the selected dependent and independent variables. The highest mean is 47.2375 for Exchange rate and the least one is for Net FDI and the standard deviation is 7977.299928 for Net FDI which is very high and SD 0.32762 for Unemployment rate which is less volatile. Table-3 tabulates the correlation between BSE Sensex and Economic Indicators. The table shows the correlation between BSE Sensex and various economic indicators over a period of sixteen years. It is understood that except GDP, GCF and GDS no other indicators have positive influence on the Sensex performance. Gross Domestic Savings and Capital formation is an imperative task for the development of any capital market 109

Table-4 presents the summary of the regression model output obtained from SPSS. The variability in the stock market performance is caused by these selected economic indicators to the extent of 77.20% which indicates that the stock market is more dependent on the economic performance. Hence investors who buy or sell the stock should consider the economic status Table-5 presents the detailed analysis of the model. The analysis shows two models for stock market prediction as there significance value is less than 0.05 at 5% level of significance. However the second model is suggested because the independent variable, GDS and FDI have an impact on the dependent variable, BSE Sensex returns to the extent of 57.10% which is better than the first model. Table-6 presents details of test conducted for testing goodness of fit of the model. The above table helps the researcher to analyse the collinearity among the independent variable. This is one of the criteria for conducting the multiple regressions to have non-collinearity relationship among independent variables. For the same the ANOVA test conducted and it s been proved that the independent variables have non- collinearity relationship in both the models Table-7 provides the model coefficients for drafting the model. The model is presented below: Regression Model for Predicting the BSE Sensex Returns: Y = a + b1 X1 + b2x2 Where, Therefore, Y = BSE Sensex Returns a = Intercept of Y which is constant b1 and b2 = Beta coefficients of X1 and X2 respectively X1 = Gross Domestic Savings as a percentage of GDP X2 = Net FDI in USD Millions BSE Sensex Returns = -112.047 + 4.871GDS + -.002 FDI Hypothesis Results The researches failed in accepting the null hypothesis at 5% level of significance as the results of multiple regression analysis shows the significance value for the both the models are below 0.05 it means that there is relationship between the stock market performance and the selected economic indicators. IX. CONCLUSION The study examines the relationship between various economic indicators and the Indian stock market represented by BSE Sensex. During the past 16 years the performance of Indian stock market was not good and also foreign portfolio investment patterns, consequent upon several changes affecting the Indian economy, like the technology slowdown, common wealth scam and political instability to name a few dragged investors to perform not sufficiently. This study helped to understand clearly that which factors influence the stock market performance and to what extent they are being affected by those factors. Researchers using the sixteen years data found that the market performance is dependent on the eight selected independent variables to the extent of 77.20%, this means investors while making investment decisions should consider these economic indicators which play important role in the market. The authors also set up model to explain the stock market performance using regression model. The model contains gross domestic savings and FDI as predicators of stock market performance. 110

X. ANNEXURES Table 1: Showing Yearly Fluctuation of BSE Sensex and Economic Indicators from 1998-99 to 2013-14 Year Sensex GDP Inflation Fx Rate GDS GI I-Rate Unemployment FDI 1998-99 -13.57 6.68 5.90 44.90 23.19 23.51 7.83 3.8 2,821 1999-00 41.40 8.00 3.30 45.90 25.69 26.97 8.87 3.9 3,557 2000-01 -8.35 4.15 7.10 45.70 23.77 24.21 9.15 4.3 4,029 2001-02 -21.96 5.39 3.60 47.70 24.93 25.65 7.16 3.9 4,322 2002-03 -3.77 3.88 3.40 48.40 25.93 25.02 5.89 4.3 5,035 2003-04 40.11 7.97 5.50 45.90 29.03 26.17 4.62 4.1 6,130 2004-05 27.80 7.05 6.50 45.00 32.41 32.45 4.65 3.9 3,712 2005-06 44.23 4.48 4.40 44.30 33.44 34.28 5.60 4.4 3,769 2006-07 48.28 9.57 6.50 45.20 34.60 35.87 7.22 4.3 7,693 2007-08 34.96 9.32 4.80 40.20 36.82 38.03 6.07 3.9 15,891 2008-09 -25.37 6.72 8.00 46.00 32.02 35.53 7.06 4.2 22,343 2009-10 26.04 8.59 3.60 47.40 33.69 36.30 3.24 3.9 17,965 2010-11 19.38 8.91 9.60 45.60 33.68 36.53 5.75 3.5 11,305 2011-12 -6.35 6.69 8.80 48.10 31.35 36.39 8.12 3.4 22,006 2012-13 4.47 4.47 7.40 54.00 30.09 34.70 4.00 3.4 19,819 2013-14 10.54 4.86 6.50 61.50 30.50 35.30 4.00 3.60 23,770 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00-10.00 Sensex GDP Inflation Rate Exchange Rate GDS GCF Interest Rate -20.00-30.00 Figure 1: Chart Showing Yearly Fluctuation of BSE Sensex and Economic Indicators from 1998-99 to 2013-14 111

Table 2: Shows the Descriptive statistics of all variables Descriptive Statistics Mean Std. Deviation N BSE Sensex 13.6150 24.84377 16 GDP 6.6706 1.93955 16 Inflation Rate 5.9312 1.97441 16 Exchange Rate 47.2375 4.72171 16 Gross Domestic Savings 30.0712 4.20736 16 Gross Capital Formation 31.6819 5.32378 16 Interest Rate 6.2019 1.80540 16 Unemployment Rate 3.9250.32762 16 Net FDI 1.0885E4 7975.29928 16 Table 3: Correlation between BSE Sensex and Economic Indicators BSE Sensex GDP Inflation rate Ex Rate GDS GCF Interest Rate Unemploy ment Rate FDI Pearson Correlation Sig. (2- tailed) 1.520 * -.254 -.248.530 *.309 -.294.188 -.218.039.343.354.035.244.269.486.417 N 16 16 16 16 16 16 16 16 16 Table 4: Model Summary Regression Analysis Model R R Square Adjusted R Square Std. Error of the Estimate 1.879 a.772.512 17.35815 Model R R Square Adjusted R Square Table 5: Stepwise Summary for Model Building Std. Error Change Statistics of R F the Square Change Estimate Change df1 df2 Sig. F Change 1.530 a.281.230 21.80497.281 5.472 1 14.035 2.756 b.571.505 17.47658.290 8.793 1 13.011 a. Predictors: (Constant), GDS b. Predictors: (Constant), GDS, FDI c. Dependent Variable: BSE Sensex 112

ANOVA c Table 6: Testing Goodness of Fit Model Sum of Squares Df Mean Square F Sig. 1 Regression 2601.798 1 2601.798 5.472.035 a Residual 6656.395 14 475.457 Total 9258.193 15 2 Regression 5287.592 2 2643.796 8.656.004 b Residual 3970.602 13 305.431 Total 9258.193 15 a. Predictors: (Constant), GDS b. Predictors: (Constant), GDS, FDI c. Dependent Variable: BSE Table 7: Coefficients of Model Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -80.516 40.607-1.983.067 GDS 3.130 1.338.530 2.339.035 2 (Constant) -112.047 34.239-3.272.006 GDS 4.871 1.223.825 3.984.002 FDI -.002.001 -.614-2.965.011 a. Dependent Variable: BSE Sensex XI. REFERENCES 1. Abdullah, D.A. & Hayworth, S. C, Macro-econometrics of stock price fluctuations. Quarterly Journal of Business and Economics, 32, 1993, 50 67. 2. Adrangi, B., Chatrath, A., Pamplin, R. B., & Sanvicente, A. Z, Inflation, output, and stock prices: Evidence from Brazil. Journal of Applied Business Research, 18, 2002, 61-77. 3. Beer, F., Rafiq, R.B., & Robbani, M.G, Stock market and Exchange rate dynamics: An empirical investigation on Brazil and US. Journal of International Business & Economics, 8, 2008, 115-122. 4. Chen Roll and S. Ross, Economic forces and the stock market, Journal of Business, 59, 1986, 383-403. 5. Dr. Mrs. Punithavathy Pandian and Dr. Sr. Queensly Jayanthi, Stock Market Volatility in Indian Stock Exchanges, 2009. 6. Geske, R and R. Roll, The fiscal and monetary linkage between stock market returns and Inflation, J. Finance, 38(1), 1983, 7-33. 7. Gjerde, Oystein and Frode Saettem, Casual Relations among Stock Returns and Macroeconomic variables in a Small, Open Economy, Journal of International Financila Markets, Institutions and Money, 9, 1999, 61-74. 8. Jay Shanken, Mark I, Weinstein, Economic forces and stock market revisited, Journal of Empirical Finance 13, 2006, 129-144. 113

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