MACROECONOMIC VARIABLE AS DETERMINANTS OF EQUITY PRICE MOVEMENT: IN INDIA

Transcription

1 MACROECONOMIC VARIABLE AS DETERMINANTS OF EQUITY PRICE MOVEMENT: IN INDIA Ashish Dhar Mishra 1 and Honey Gupta 2 Research Scholar, Dayalbagh Educational Institute, Agra, India 1 ashish.mishra774@gmail.com ABSTRACT In current scenario of Indian stock market each investors are required to be alert enough about aware about major factors affecting stock market. Macroeconomic variables (e.g. economic output, employment, and inflation) play a vital role in the economic performance of any country. In this paper it has been tried to find out major factors responsible for updown movement in Indian stock market. The objective of the study is to examine relation between Sensex and macroeconomic variables (IIP, WPI, Interest Rate and MSCII) during specified period (2006 to 2012).Multiple correlation and multiple regressions is used to analyze the relationship among variables. MSCII has a very high and positive correlation with Sensex and results are a significant happening in the market. It is very important for each and every investor to aware about macroeconomic variable. Keywords: BSE Sensex; WPI; IIP; Interest Rate; MSCII INTRODUCTION In recent time stock market is an important part of the economy of a country. Due to globalization very huge changes came into Indian economy. Stock market plays a very significant role in growth of Indian economy. On the basis of stakeholders point of view stock market is very important. Growth of the industry and commerce of country is also affected by stock market conditions. When stock market is on boom achievement and growth of industry is high and when stock market position is down achievement and growth is down. It is the reason that all stakeholders keep a close watch on the happenings of the stock market. If a company wants to raise their funds, they have to take credit loan from industrial banks or they have to issue share, debenture, bonds etc. through stock market. Issue of shares is primary source of any company by which they have raise funds for business activities. Investment is the commitment of funds to one or more assets that will be held over some future time period. Investment sometimes refers as investment process. Investment process is the process of decision making about parking our fund in different investment avenues. Investment decision involves the process of selecting best alternative(s) with respect to risk averseness and expected return of investor. The capital market is market for financial assets which have a long or indefinite maturity. Generally, it deals with long term securities which have a maturity period of above one year. 22

2 Followings are the importance of capital market. It is important source for the productive use of the economy s savings. It mobilizes the savings of the people for further investment and thus avoids their wastage in unproductive uses. It provides incentives to saving and facilitates capital formation by offering suitable rates of interest as the price of capital. It provides an avenue for investors, partially the household sector to invest in financial assets which are more productive than physical assets. It facilitates increase in production and productivity in the economy and thus, enhances the economic welfare of the society. Thus, it facilitates the movement of stream of command over capital to the point of highest yield towards those who can apply them productively and profitably to enhance the national income in the aggregate. Different institution takes initiatives for qualitative and quantitative flow of funds to increase the economic growth in the capital market and thus enhances their rational income. The roles of expert intermediaries are very important to promote the stability in values of securities representing capital funds. Moreover, it serves as an important source for technological up-gradation in the industrial sector by utilizing the funds invested by the public. REVIEW OF LITERATURE Vijay Kumar Varadi (2013): Determinants of Volatile Commodity Prices, They made an attempt to identify more determine factors for recent hike and fluctuations in global commodity prices, including, monetary policies, macroeconomic factors, financialization in commodity markets and impact of various other commodity prices. Empirical evidence is that there is a negative relationship existing with monetary policy, mixed evidence with macroeconomic indicators and positive impact of financialization of commodity markets. And various commodities such as crude oil and non-energy commodities are having significant effect on volatile commodity prices. {Source: ( Carole Comerton-Forde, Tālis J. Putniņš (2012): Stock Price Manipulation: Prevalence and Determinants, they empirically analyzed the prevalence and economic underpinnings of closing price manipulation and its detection. They estimated that approximately one percent of closing prices are manipulated, of which only a small fraction is detected and prosecuted. They found that stocks with high levels of information asymmetry and mid to low levels of liquidity are most likely to be manipulated. A significant proportion of manipulation occurs on month/ quarter-end days. Manipulation on these days is more likely in stocks with high levels of institutional ownership. Government regulatory budget has a strong effect on both manipulation and detection. NopphonTangjitprom (2012): Macroeconomic Factors of Emerging Stock Market: The Evidence from Thailand, This paper aims to examine the importance of macroeconomic factors to determine the performance in stock market. The regression analysis is used to 23

3 examine this relationship. They reveal that macroeconomic variables are less important to predict future stock return whereas stock return can be used to predict macroeconomic variables more. Finally, the variance decomposition technique reveals that interest rate is the most important macroeconomic variable to explain the variance in stock return. However, it is clearly noticed that all macroeconomic variables can explain only a little of variance in stock return. Jimoh Ezekiel Oseni (2009): Determinants of Equity Prices in the Stock Markets, This study examined the extent to which some information factors or market indices affect the stock price. A model defined by Al-Tamimi (2007) was used to redress the variables (stock prices, earnings per share, gross domestic product, and lending interest rate and foreign exchange rate) after testing for multicollinarity among the independent variables. The multicollinarity test revealed very strong correlation between gross domestic product and crude oil price, gross domestic product and foreign exchange rate, lending interest rate and inflation rate. William Breen, Laurie Simon Hodrick, Robert A. Korajczyk (1999): The Determinants of Equity Illiquidity, they examined the change in liquidity surrounding stock splits. It was commonly argued that stock splits are done precisely to enhance the liquidity of a stock, though the existing empirical support for this claim is mixed. They found that their measure of illiquidity increases by a statistically significant amount following a split, evidence that liquidity has been compromised, rather than improved, by the split. OBJECTIVE OF THE STUDY To examine relation between Sensex and macroeconomic variables (IIP, WPI, Interest Rate and MSCII) during specified period. SAMPLE DESIGN AND DATA Sample Size: Five variables named: 1. BSE Sensex 2. Index of Industrial Production (IIP) 3. Wholesale Price Index (WPI) 4. Interest Rate (Repo rate). 5. Morgan Stanley Capital International Index of India (MSCII). Duration of Study: 2006 to 2012 Data Description and Sources Variable Description Unit Data Source BSES Monthly average of Sensex Rupees IIP Monthly index Index Base WPI Monthly index Index Base IR Monthly rate Rate Handbook of statistic available on RBI website Monthly average of MSCII Morgan Stanley Capital International USD Index of India 24

4 HYPOTHESES OF THE STUDY H0: BSE Sensex and Macroeconomic variables (IIP, WPI, IR and MSCII) of India are independent during the specified period. TOOLS AND TECHNIQUES USED 1. Multiple Correlation 2. Multiple Regression 3. Probable Error ANALYSIS Table 1. Correlation between Selected variables Sensex Interest rate WPI IIP MSCI(INDIA) Sensex 1 IR WPI IIP MSCII In this analysis researcher observed that there is moderately positive correlation of WPI and IIP with Sensex but IR has very low positive correlation with Sensex. MSCII has very high and positive correlation with Sensex. Table 2. Multiple Regressions Data Regression Statistics Multiple R(r) R Square Adjusted R Square Observations 84 Here, researcher observed that there is very high correlation (0.99) between selected variables and Sensex. These variables can represent 98.16% change in the value of BSE Sensex. To check the significance of correlation, we use probable error (P.E) criteria.i.e. Here, 1. If Coefficients of Correlation (r) is less than the probable error(r < P.E), there is no evidence of correlation in two variables. 2. If Coefficients of Correlation (r) is more than six times the probable error (r >6 P.E), correlation will be considered significant. Probable error for Sensex and Macroeconomic Variables Probable error is less than the correlation coefficients. Test of Significance of Correlation: For Sensex and Macroeconomic Variables r > 6P.E. (.99 >.0081) 25

5 Hence, r is Significant and hypothesis is rejected. Table 3. Coefficients of Selected Macro economic Variables Coefficients Intercept Interest rate WPI IIP MSCI(INDIA) Equation for model (multiple regressions): Sensex(Y) = a + IR(X 1 ) + WPI(X 2 ) +IIP(X 3 ) + MSCII(X 4 ) Where, Y for Dependent and X for independent Y= X X X X 4 Table 4. Slope value of Macroeconomic variables under Simple Regression linear model Empirical Data: Slope(β) IR WPI IIP MSCI(INDIA) Source: and data given in table 5 Figure 1: Trend of Sensex 26

6 Source: and data given in table 5 Figure 2: Trend of IIP Source: and data given in table 5 Figure 3: Trend of WPI Source: Handbook of statistic available on RBI websiteand data given in table 5 Figure 4: Trend of IR 27

7 Source: and data given in table 5. Figure 5: Trend of MSCII Figure 6: Actual Sensex and Predicted Sensex by multiple regression equation Here, there is very much similarity under the movements of Actual Sensex and Predicted Sensex. FINDINGS In this study researcher has observed that- In table 1, the correlation between WPI and IIP with Sensex are moderately positive. It indicates the relationship between WPI and IIP with Sensex is significant moderate positive. The correlation between IR and Sensex is very low positive. It means relationship is very low significant. The correlation between MSCII and Sensex is very high & positive so relationship between MSCII and Sensex is highly significant. In table 2, the correlation between selected variable and Sensex is very high positive (0.99). These variables can represent 98.16% change in the value of BSE Sensex. 28

8 Researcher analyzed that there is very much similarity under the movements of Actual Sensex and Predicted Sensex. CONCLUSION This study is examined the relationship between Sensex and macroeconomic variables. The macroeconomic variable used in this study includes Index of Industrial Production (IIP), Wholesale Price Index (WPI), Interest Rate (IR), and Morgan Stanley Capital International Index of India (MSCII). On the basis of data researcher obtained during analysis it is obvious that the relationship between selected variable and Sensex is significant positive. In the selected variable MSCII and Sensex are very high positive correlation and other side WPI and IIP with Sensex are moderate positive so results are significant happenings in the market % changes in value of selected variables represent very high impact between selected variable and Sensex. APPENDIX Table 5: Data Summary Month Sensex Interest Predicted MSCI WPI IIP rate Sensex (INDIA) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr

9 Table 5: Data Summary (Contd.) Month Sensex Interest Predicted MSCI WPI IIP rate Sensex (INDIA) May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

10 Table 5: Data Summary (Contd.) Month Sensex Interest Predicted MSCI WPI IIP rate Sensex (INDIA) Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec REFERENCES 1. Chan, L. K., Karceski, J., &Lakonishok, J. (2000). New Paradigm or Same Old Hype in Equity Investing? Financial Analysts Journal, July/August, CAROLE COMERTON-FORDE,Putnins T. J. (October 4, 2012). Stock Price Manipulation: Prevalence and Determinants. Forthcoming, Review of Finance 3. Tangjitprom, N. (2012). Macroeconomic Factors of Emerging Stock Market:The Evidence from Thailand. International Journal of Financial Research 4. Oseni, J. E. (2009). Determinants of Equity Prices in the Stock Markets. SSRN 5. William J. Breen, Hodrick L. Simon, Korajczyk R. A (March 1999). The Determinants of Equity Illiquidity. SSRN Websites Referred