POOJA
Resource Person in Commerce,
Sir Chhotu Ram Govt. College for Women,
Sampla, Rohtak (Haryana)
Abstract: Mobilization of savings, investment and expenditure has been regarded as important macro-economic variable factors in stock market development. The aim of this study was to analyze the impact of savings, investment and expenditure on Indian Stock Market Index from 2001 to 2014. Data for the study was gathered from Handbook of Statistics on Indian Economy and www.nseindia. With the help of Linear Regression Model, found that savings, investment and expenditure have significant and positive impact on the stock market index in India.
Keywords: Savings, Investment, Expenditure, Stock Market Index, NSE, Macro Economics.
Introduction: The economic development of any country depends upon the existence of a well organized financial system and stock market is one of the most important parts of organized financial system. The stock market occupies a pivotal position in the financial system. It performs several economic functions and renders invaluable services to the investors, companies, and to the whole economy. The stock market includes some important points which play an important role in the economic development like:
· By boosting-up investment
· By mobilizing surplus savings
· Ready market for securities
· By ensuring liquidity of capital
A stock market index is one which indicates the pattern of movements of the price of a group of securities which are considered to be the representative of the stock market. The stock market index is an invaluable guide to study the trend of growth patterns in the economy, to analyze as well as forecast business cycles and also to correlate stock market index (S&P CNX Nifty) to various macro-economic variables (savings, investment and expenditure). S&P CNX Nifty is a popular index of NSE introduced in April, 1996 with 1996 as the base year. It comprises of a well-diversified 50 stock index accounting for 23 sectors of the economy. An effort is made in this paper to investigate the nexus of different macro-economic variables with stock market index in India for the period 2001 to 2014.
Review of Literature:
R. Karthik and Dr. N. Kannan (July 2011) investigates the impact of FDI on the Indian stock market development. The study also examines the other major contributing factors towards the stock market development. An ARDL bounding testing approach is used for long run relationship among macro-variables and the error correction model is used for short run dynamics. The results support the complementary role of FDI in the stock market development of India.
Bashir Ahmad Joo and Zahoor Ahmad Mir (2014) the study is conducted using monthly time series on NIFTY, SENSEX and FIIs activity for a period of fifteen years from 1999 to 2013. To check the non-stationarity of the time series the Augmented Dickey-Fuller unit root test is applied and the study reveals that there is a significant relationship between FIIs capital flows and stock market volatility. Moreover, FIIs investment has statistically significant influence on volatility of NIFTY and SENSEX, used as proxy to Indian stock market.
Biswal and Kamaiah (2001) evaluated the behavior of stock market development indicators like market size, liquidity and volatility and examined the presence of trend break in these indicators since liberalization in India and the study suggested that stock market has become larger and more liquid in the post liberalization period. In respect of volatility, however, there was no significant change.
Objectives:
· To study the impact of Macro-Economic Variables on Indian Stock Market from the period 2001 to 2014.
· To identify the degree of relationship between Investment, Expenditure and Savings on Indian Stock Market with the help of Multiple Regression Method.
Research Methodology:
· Data collection: This study is based on the secondary data collected on yearly basis from 2001 to 2014. The data is related to Savings, Investment, Expenditure and CNX Nifty. It is collected from various like Handbook of Statistics on Indian Economy and www.nseindiarespectively.
· Statistical Tools and Techniques: In order to analyze the collected data, the statistical tool Multiple Regression Method is used. In the present study, the linear relationship between dependent variable (CNX Nifty) and independent variable (savings, investment and expenditure) is established. This study is made to analyze the impact of independent variables on dependent variable.
· Analysis and Interpretation:
Ø Regression Analysis of Savings, Investments and Expenditure on CNX Nifty.
Ø Independent Variable - Savings, Investments and Expenditure
Ø Dependent Variable - CNX Nifty
Table1: Descriptive Statistics
| | Mean | Std. Deviation | N |
| CNX Nifty | 3629.2857 | 1981.45904 | 14 |
| Saving | 8851.2129 | 5860.75603 | 14 |
| Investment | 7004.2679 | 4441.18367 | 14 |
| Expenditure | 8037.3973 | 4229.31522 | 14 |
The table 1 represents the Descriptive Statistics for the variables used in our estimation. Mean value of dependent variable is 3629.28 and S.D. is 1981.46 which show high fluctuations in this variable. But in case of independent variables, the fluctuations are higher.
Table2: Correlations
| Pearson Correlation | CNX Nifty | Saving | Investment | Expenditure |
| CNX Nifty | 1.000 | .927 | .932 | .912 |
| Saving | .927 | 1.000 | .998 | .995 |
| Investment | .932 | .998 | 1.000 | .996 |
| Expenditure | .912 | .995 | .996 | 1.000 |
The table 2 shows, Correlation of CNX Nifty with savings is .927 showing that CNX Nifty has positive high degree of correlation with savings. Correlation of CNX Nifty with investment is .932 showing positive high degree of correlation. Correlation between CNX Nifty and expenditure is .912 which also shows the positive high degree of correlation between these two. We can also conclude that there is a positive relationship between theses four macro-economic variables with the help of Karl Pearson Correlation Method.
Table3: Model Summaryd
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | Change Statistics | |||||
| R Square Change | F Change | df1 | df2 | Sig. F Change | Durbin- Watson | |||||
| 1 | .927a | .859 | .848 | 773.53946 | .859 | 73.300 | 1 | 12 | .000 | |
| 2 | .935b | .873 | .850 | 766.47129 | .014 | 1.222 | 1 | 11 | .292 | |
| 3 | .951c | .904 | .875 | 701.18870 | .030 | 3.144 | 1 | 10 | .107 | 1.917 |
| a. Predictors: (Constant), Saving |
| b. Predictors: (Constant), Saving, Investment |
| c. Predictors: (Constant), Saving, Investment, Expenditure |
| d. Dependent Variable: CNX Nifty |
In table 3, Savings coefficient of correlation is .927. It shows positive high degree of correlation between Savings and CNX Nifty. R2 indicate that 85.9% Savings has relation with CNX Nifty. Savings and Investment coefficient of correlation is .935. It also shows positive high degree of correlation between Savings, Investment and CNX Nifty. R2 indicate that 87.3% Savings and Investment has relation with CNX Nifty. Savings, Investments and Expenditures coefficient of correlation is .951 and it also shows positive high degree of correlation. R2indicate that 90.4% Saving, Investment and Expenditure has relation with CNX Nifty. R2Coefficient of determination is a statistical measure of how well the regression line estimates the real data. The Durbin-Watson is used for multicollinearity of the data. The value of Durbin-Watson is 1.917, so that the data can be used for the analysis.
Table4: ANOVAa Table
| Model | | Sum of Squares | df | Mean Square | F | Sig. |
| 1 | Regression | 43859979.388 | 1 | 43859979.388 | 73.300 | .000b |
| Residual | 7180359.469 | 12 | 598363.289 | | | |
| Total | 51040338.857 | 13 | | | | |
| 2 | Regression | 44578078.161 | 2 | 22289039.081 | 37.940 | .000c |
| Residual | 6462260.696 | 11 | 587478.245 | | | |
| Total | 51040338.857 | 13 | | | | |
| 3 | Regression | 46123682.910 | 3 | 15374560.970 | 31.270 | .000d |
| Residual | 4916655.947 | 10 | 491665.595 | | | |
| Total | 51040338.857 | 13 | | | |
| a. Dependent Variable: CNX Nifty |
| b. Predictors: (Constant), Saving |
| c. Predictors: (Constant), Saving, Investment |
| d. Predictors: (Constant), Saving, Investment, Expenditure |
The above ANOVA Table 4 presents ANOVA ANALYSIS. In case of model 1, the F-Ratio is 73.3 and in case of model 2, the F-Ratio is 37.94 and F-Ratio in model 3 is 31.27. But F-Ratio of model 1 is more as compared to model 2 and model 3 so, we can conclude that the model 1 is more significant in predicting the output of macro-variables.
Table5: Coefficientsa
| Model | | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |
| 1 | B | Std. Error | Beta | |||
| (Constant) | 855.252 | 384.348 | | 2.225 | .046 | |
| Saving | .313 | .037 | .927 | 8.562 | .000 | |
| (Constant) | 576.062 | 456.952 | | 1.261 | .234 | |
| 2 | Saving | -.371 | .620 | -1.098 | -.599 | .562 |
| Investment | .905 | .819 | 2.029 | 1.106 | .292 | |
| (Constant) | 1904.127 | 857.795 | | 2.220 | .051 | |
| 3 | Saving | -.206 | .575 | -.609 | -.358 | .728 |
| Investment | 1.548 | .832 | 3.469 | 1.860 | .092 | |
| Expenditure | -.907 | .512 | -1.937 | -1.773 | .107 | |
a. Dependent Variable: CNX Nifty
The analytical Table5 exhibits that the estimates of B values (Unstandardized Coefficients) which explicate the individual contribution of each independent variable to the model. The B value also explains to what degree each predictor affects the outcome variable, if the effects of other predictor are held constant. If we replace the B values in equation, we can define the model as follows:
Model 1: CNX Nifty = b0 + b1 (Saving) + b2 (Investment) + b3 (Expenditure)
= (1904.127) - 0.206 (Saving) + 1.548 (Investment) - 0.907 (Expenditure)
The standardized beta value exposed through the table, indicate that the volume of change in standard deviation outcome (Dependent Variable) due to 1 standard deviation change in the independent variables. These values observed that saving (5860.75603) increases by 1 SD, CNX Nifty decreases by -0.609. The SD for CNX Nifty is 1981.45904 so, this constitutes a change of -1206.71 [1981.45904 x (-0.609)]. CNX Nifty increases by 3.469. The SD for CNX Nifty is 1981.45904 so, this constitutes a change of 6873.68 (1981.45904 x 3.469). CNX Nifty decreases by -1.937. The SD for CNX Nifty is 1981.45904 so, this constitutes a change of -3838.086 [1981.45904 x (-1.937)]. This interpretation is true only if the effects of other variable held constant.
Conclusion: An effort has been made in this paper to identify the relationship between macro-economic variables with stock market index. 14 years data was collected. The Linear Regression Method was used. The study of this paper concludes that the correlation of CNX Nifty with savings is .927 showing that CNX Nifty has positive high degree of correlation with savings. Correlation of CNX Nifty with investment is .932 showing positive high degree of correlation. Correlation between CNX Nifty and expenditure is .912 which also shows the positive high degree of correlation between these two. Results suggest positive impact of all macro-economic variables on the stock market index. If these macro-economic variables are targeted by the government, then it will boost the stock market development.
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