Economic indicators and stock market performance an empirical case of india

1. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)
17 – 19, July 2014, Mysore, Karnataka, India
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
107
IJM
© I A E M E
ECONOMIC INDICATORS AND STOCK MARKET PERFORMANCE - AN
EMPIRICAL CASE OF INDIA
Kantesha Sanningammanavara1, Kiran Kumar K V2
1, 2Asst. Professor, Department of MBA, Vidyavardhaka College of Engineering, Gokulam 3rd 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.

2. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
17 – 19, July 2014, Mysore, Karnataka, India
108
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

3. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
17 – 19, July 2014, Mysore, Karnataka, India
109
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: H1 : 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

4. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
17 – 19, July 2014, Mysore, Karnataka, India
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
110
Where, 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
Therefore, “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.

5. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
17 – 19, July 2014, Mysore, Karnataka, India
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
111
X. ANNEXURES
Table 1: Showing Yearly Fluctuation of BSE Sensex and Economic Indicators from 1998-99 to
2013-14
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
-10.00
-20.00
Figure 1: Chart Showing Yearly Fluctuation of BSE Sensex and Economic Indicators from
1998-99 to 2013-14
-30.00
Sensex
GDP
Inflation Rate
Exchange Rate
GDS
GCF
Interest Rate

6. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
17 – 19, July 2014, Mysore, Karnataka, India
Model R R Square Adjusted R Square Std. Error of the
112
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
1 .520* -.254 -.248 .530* .309 -.294 .188 -.218
Sig. (2-
tailed)
.039 .343 .354 .035 .244 .269 .486 .417
N 16 16 16 16 16 16 16 16 16
Table 4: Model Summary Regression Analysis
Table 5: Stepwise Summary for Model Building
Model R R Square Adjusted
R Square
Std. Error
of
the
Estimate
Change Statistics
R
Square
Change
F
Change
df1 df2 Sig. F
Change
1 .530a .281 .230 21.80497 .281 5.472 1 14 .035
2 .756b .571 .505 17.47658 .290 8.793 1 13 .011
a. Predictors: (Constant), GDS
b. Predictors: (Constant), GDS, FDI
c. Dependent Variable: BSE Sensex
Estimate
1 .879a .772 .512 17.35815

7. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
17 – 19, July 2014, Mysore, Karnataka, India
113
Table 6: Testing Goodness of Fit
ANOVAc
Model Sum of Squares Df Mean Square F Sig.
1 Regression 2601.798 1 2601.798 5.472 .035a
Residual 6656.395 14 475.457
Total 9258.193 15
2 Regression 5287.592 2 2643.796 8.656 .004b
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 Macro-economic
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.

8. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
17 – 19, July 2014, Mysore, Karnataka, India
114
9. Kwon, C S, T S Shin and F E Bacon, The effect of macroeconomic variables on stock market
returns in the developing markets, Multinational Business Rev. Fall, 5(2), 1997, 63-70.
10. Lee B S, Casual relations among Stock Returns, Interest Rates, Real Activity and Inflation,
Journal of Finance, 47, 1992, 1591-1603.
11. Mukherjee, T. K. Naka, A, Dynamic relations between macroeconomic variables and the
Japanese stock market: an application of a vector error correction model, The Journal of
Financial Research, 18, 1995, 223–237.
12. Nieh, C, C. Lee, C .F, Dynamic relationship between stock prices and exchange rates for
G-7 countries. Quarterly Review of Economics and Finance, 41, 2001, 477-490.
http://dx.doi.org/10.1016/S1062-9769(01)00085-0.