Chapter Four IMPACT OF MACRO- ECONOMIC FACTORS ON SHARE PRICES IN INDIA

Transcription

1 Chapter Four IMPACT OF MACRO- ECONOMIC FACTORS ON SHARE PRICES IN INDIA

2 Impact of Macro-Economic Factors on Share Prices of India 1 52 CHAPTER FOUR IMPACT OF MACRO-ECONOMIC FACTORS ON SHARE PRICES IN INDIA A number of studies conducted in developed markets provide substantial evidence that share returns fluctuate with changes in macroeconomic variables. Therefore, aggregate equity prices are expected to have strong relationship with macroeconomic variables. The argument suggests that the intrinsic value of equity shares depends on the present value of dividends which is distributed out of company earnings; these earnings are influenced by real economic activities and, therefore, there should be: a relationship between economic fundamentals and share prices. However, it remains to be observed whether the argument holds true in the context of emerging markets too. Compared to their developed counterparts, the emerging markets are smaller in size and relatively less liquid. Further, the investor perception in emerging markets may be different from those in developed markets and thus the behavior of market prices of equities may be driven by the speculative activities of irrational investors rather than economic fundamentals. Further, the existing literature on developed as well as emerging markets reveal that the role of macroeconomic factors in determining stock price returns has been studied largely using single composite stock market index. It is well known, a composite stock index includes stocks from different sectors and there is a possibility that macroeconomic variables may affect different sectors differently.

3 Impact ofmacro-economic Factors on Share Prices of India 153 Considering the two significant sectors of Indian economy viz. manufacturing and financial services sectors, the research addresses the following issues: (A) Does the long-run relationship exists between macroeconomic variables and stock prices in manufacturing and financial services sectors in emerging Indian market? (B) Is there any significant difference between macroeconomic factors affecting stock returns in manufacturing sector and those in financial services sector? (C) Is there any significant difference observed in relationship between share prices in subsectors of manufacturing sector and macroeconomic variables? The principal method employed to analyse impact of macroeconomic variables on sectoral indices is the Johansen's multivariate cointegration analysis developed in Johansen (1988) and applied in Johansen and Juselius (1990). This methodology has become a well established methodology to test the long-run relationships among variables. The first step in this process is to test for stationarity in the time series of variables being considered for examining longrun equilibrium relationship. The stationarity test provides the evidence on the order of integration of the variables. For this purpose, popular Augumented Dickey-Fuller (ADF) test for unit root is used. Once the order of integration is determined, cointegration analysis is undertaken to determine whether time series of indices and macroeconomic variables display a stationary process in a linear combination. For this purpose Johansen's (1991) method of multivariate cointegration is employed. A finding of cointegration implies existence of a longterm relationship between the market index and the macroeconomic variables.

4 Impact ofmacro-economic 'Factors on Share Prices of India 154 For this purpose there has to be at least one cointegrating relationship among the variables. 4.1 Results of Unit Root Test The results of the stationarity test are presented in Table 4.1. The first column displays the variables included for cointegration analysis; the second Table 4.1 Panel A: ADF Test Results for.selected Aggregate and Sectoral Indian Stock Market Indices Variable Intercept Trend & Intercept t-stat t-stat LNIFTY LCOSPIMFG LCOSPITEX LCOSPICHEM LCOSPITEL LCOSPIFB LCOSPIFINSERV ALNIFTY * * ALCOSPIMFG * * ALCOSPITEX * * ALCOSPICHEM * * ALCOSPITEL * * ALCOSPIFB * * ALCOSPIFINSERV * * Goa "University

5 Impact of Macro -Economic 'Factors on Share Prices of India 155 Table 4.1 Panel B: ADF Test Results for Selected Macroeconomic Variables in Indian Context Variable Intercept Intercept & Trend t-stat t-stat LIIP LM LCPI LER ** LINTOIL LFDI ALIIP *** ** ALM * * ALCPI * * ALER * * ALINTOIL * * ALFDI * ** Notes:(a) (b) MacKinnon (1996) values used for testing of unit root hypothesis. Crital values are -3.48, and at 1%, 5% and 10% respectively for test with intercept and -4.02, and at 1%, 5% and 10% respectively for test with trend and intercept. *, **, *** represents significance at 1%, 5% and 10% respectively. column reports the ADF test statistic when a constant (intercept) term is only included in the ADF model as a deterministic regressor while the third column shows the results when both a constant term (intercept) and a time trend are

6 Impact of gtlacro-'economic Eactors on Snare (Prices of India 156 incorporated in the model. All the index variables are found to be non-stationary at levels and stationary at first difference. Likewise, IIP, Money Supply, Inflation, International Oil Prices, and FDI are also found to be integrated of order one, 41). Exchange Rate is I(0) when only constant term is included as deterministic regressor in ADF model while it is I(1) when constant and trend is incorporated in ADF model. However, the AIC value is least in constant only model for ADF test and therefore it is considered that Excahnge Rate is I(0) variable. According to Hansen and Juselius (2002), to find cointegration between non-stationary variables, at least two variables of all the variables included in the cointegration system have to be 41). The findings of ADF test are consistent with this requirement. Therefore all the variables are ideal for testing for long-run equilibrium using Johansen's Cointegration test. The final vector of variables to be included is: Xt = (LNIFTYt LIIPt LM3t LCPIt LERt LINTOILt LFDIt) for the model examining the cointegration relationship between aggregate stock market index and macroeconomic variables; Xt = (LCOSPIMFGt LIIPt LM3t LCPIt LERt LINTOILt LFDIt) for the model examining the cointegration relationship between manufacturing sector index and macroeconomic variables; Xt = (LCOSPITEXt LIIP t LM3t LCPIt LERt LINTOILt LFDIt) for the model examining the cointegration relationship between textile sector index and macroeconomic variables; Xt = (LCOSPICHEMt LIIPt LM3t LCPIt LERt LINTOILt LFDIt) Goa university

7 Impact ofmacro-economic Factors on Share T./ices of India 157 for the model examining the cointegration relationship between chemical sector index and macroeconomic variables; Xt = (LCOSPITELt LIIPt LM3t LCPIt LER t LINTOILt LFDIt) for the model examining the cointegration relationship between telecom sector index and macroeconomic variables ; Xt = (LCOSPIFBt LIIPt LM3t LCPI t LERt LINTOILt LFDIt) for the model examining the cointegration relationship between food and beverage sector index and macroeconomic variables and; Xt = (LCOSPIFINSERV t LIIPt LM3t LCPIt LERt LINTOILt LFDIt) for the model examining the cointegration relationship between financial services sector index and macroeconomic variables. 4.2 Results of Johansen's Cointegration test The results of both trace test and maximum eigenvalue test for macroeconomic variables and stock price indices are presented in Table 4.2 through Table 4.8. The results for cointegration test are based on lag of 3 as suggested by AIC criterion. Further, inclusion of too many lags in cointegration analysis reduces the power of test due to estimation of additional parameters and loss of degrees of freedom.

8 Impact of 911acro-Economic Factors on Share Prices of India 158 Table 4.2 Cointegration test results for LNIFTY (Composite Index) and Macroeconomic Variables Eigenvalue Trace None ** At most At most At most At most At most At most Trace test indicates 1 cointegrating equation(s) at both 5% and 1% levels Eigenvalue Max-Eigen None ** At most At most At most At most At most At most Max-eigenvalue test indicates,1 cointegrating equation(s) at both 5% and 1% levels

9 Impact of Macro-Economic Factors on Share Prices of India 159 Table 4.3 Cointegration test results for LCOSPIMFG (Manufacturing Sector Index) and Macroeconomic Variables Eigenvalue Trace None ** At most At most At most At most At most At most Trace test indicates 1 cointegrating equation(s) at both 5% and 1% levels Eigenvalue Max-Eigen None ** At most At most At most At most At most At most Max-eigenvalue test indicates 1 cointegrating equation(s) at both 5% and 1% levels

10 Impact of Macro -Economic Factors on Share Prices of India 160 Table 4.4 Cointegration test results for LCOSPITEX (Textile Sector Index) and Macroeconomic Variables Eigenvalue Trace None ** At most 1 * At most At most At most At most At most Trace test indicates 2 cointegrating equation(s) at the 5% level Trace test indicates 1 cointegrating equation(s) at the 1% level Eigenvalue Max-Eigen None ** At most At most At most At most At most At most 6 * Max-eigenvalue test indicates 1 cointegrating equation(s) at both 5% and 1% levels

11 Impact of Macro -`Economic 'Factors on Share Prices of India 161 Table 4.5 Cointegration test results for LCOSPICHEM (Chemical Sector Index) and Macroeconomic Variables Eigenvalue Trace None ** At most At most At most At most At most At most Trace test indicates 1 cointegrating equation(s) at both 5% and 1% levels Eigenvalue Max-Eigen None ** At most At most At most At most At most At most Max-eigenvalue test indicates 1 cointegrating equation(s) at both 5% and 1% levels

12 Impact of Macro-Economic Tactors on Share 'Prices of India 162 Table 4.6 Cointegration test results for LCOSPITEL (Telecom Sector Index) and Macroeconomic Variables Eigenvalue Trace None ** At most At most At most At most At most At most Trace test indicates 1 cointegrating equation(s) at both 5% and 1% levels Eigenvalue Max-Eigen None ** At most At most At most At most At most At most Max-eigenvalue test indicates 1 cointegrating equation(s) at both 5% and 1% levels

13 Impact of Micro -Economic Factors on Share Prices of India 163 Table 4.7 Cointegration test results for LCOSPIFB (Food and Beverage Sector Index) and Macroeconomic Variables Eigenvalue Trace None ** At most At most At most At most At most At most Trace test indicates 1 cointegrating equation(s) at both 5% and 1% levels Eigenvalue Max-Eigen None ** At most At most At most At most At most At most Max-eigenvalue test indicates 1 cointegrating equation(s) at both 5% and 1% levels

14 Impact of (Macro-Economic Factors on Snare Prices of India 164 Table 4.8 Cointegration test results for LCOSPIFINSERV (Financial Services Sector Index) and Macroeconomic Variables Eigenvalue Trace None ** At most 1 * At most At most At most At most At most Trace test indicates 2 cointegrating equation(s) at the 5% level Trace test indicates 1 cointegrating equation(s) at the 1% level Eigenvalue Max-Eigen None ** At most 1 * At most At most At most At most At most Max-eigenvalue test indicates 2 cointegrating equation(s) at the 5% level Max-eigenvalue test indicates 1 cointegrating equation(s) at the 1% level Goa university

15 Impact of Macro-Economic cfactors on Share Prices of India 165 Following are the important findings from cointegration test: (i) The results of Johansen's Cointegration analysis indicate that there exists long run relationship between macroeconomic factors and stock prices in India. Both trace test as well as maximum eigenvalue test indicate existence of at least one cointegrating vector in the relationship between macroeconomic variables and stock price indices. (ii) Normalized coefficients of cointegrating vector are presented in Table 4.9 below. The results of normalized coefficients indicate that industrial Table 4.9 Normalised Coefficients of Cointegrating Relationship Between Macro- Economic Factors and Indian Stock Prices NIFTY: Aggregate Nifty Index Normalized cointegrating coefficients (standard error in parentheses) LNIFTY LIIP LM3 LCPI LEX LINTOIL LFDI ( ) ( ) ( ) ( ) ( ) ( ) [ ] [4.1329] [3.0280] [ ] [ ] [1.4552] COSPIMFG: Aggregate Manufacturing Sector Index Normalized cointegrating coefficients (standard error in parentheses) LMFG LIIP LM3 LCPI LEX LINTOIL LFDI ( ) ( ) ( ) ( ) ( ) ( ) [9.0031] [2.2362] [4.5317] [4.7770] [0.9326] [0.9493] COSPITEX: Textile Sector Index r Normalized cointegrating coefficients (standard error in parentheses) Note: a) Figures in parenthesis represents standard error. b) Figures in brackets represents t-statistics.

16 Impact ofmacro-economic Factors on Share Prices of India 166 Table 4.9 cont... LTEXTILE LIIP LM3 LCPI LEX LINTOIL LFDI ( ) ( ) ( ) ( ) ( ) ( ) [8.2788] [1.8210] [4.9674] [3.2024] [1.7042] [0.3210] COSPICHEM: Chemical Sector Index Normalized cointegrating coefficients (standard error in parentheses) LCHEMICAL LIIP LM3 LCPI LEX LINTOIL LFDI ( ) ( ) ( ) ( ) ( ) ( ) [9.1970] [2.7315] [4.2675] [5.1742] [1.4690] [0.8813] COSPITEL: Telecom Sector Index Normalized cointegrating coefficients (standard error in parentheses) LTELECOM LIIP LM3 LCPI LEX LINTOIL LFDI ( ) ( ) ( ) ( ) ( ) ( ) [8.8979] [3.4661] [3.2145] [4.9529] [1.6799] [1.6240] COSPIFB: Food and Beverage Sector Index Normalized cointegrating coefficients (standard error in parentheses) LFB LIIP LM3 LCPI LEX LINTOIL LFDI ( ) ( ) ( ) ( ) ( ) ( ) [8.4991] [2.7106] [4.3927] [6.1287] [2.1380] [1.0830] COSPIFINSERV: Financial Services Sector Index Normalized cointegrating coefficients (standard error in parentheses) LFINSERV LIIP LM3 LCPI LEX LINTOIL LFDI ( ) ( ) ( ) ( ) ( ) ( ) [9.8774] [0.3356] [6.2207] [0.1713] [1.7871] [0.2226] Note: a) Figures in parenthesis represents standard error. b) Figures in brackets represents t-statistics. Goa university

17 Impact of,icicro-economic Tactors on Share Trices of India 167 production and exchange rate are significant positive determinant of stock prices in India while money supply and inflation are the significant _ L negative determinants. Positive relationship between manufacturing index and IIP indicate investor expectation of impact of changing productive activity on expected dividends which is subsequently factored in stock returns as suggested by Mayasami and Koh (2000). Positive relationship between manufacturing sector index and exchange rate is consistent with the economic theory. Depreciating Rupee besides curbing imports helps in boosting exports thereby increasing cash flows into the country assuming that demand for exports is fairly elastic. Increased volume of output and export earnings is perceived by investors as an indicator of booming economy thus the demand and thereby price of the IP'--- shares increases [Dimitrova (2005)]. The findings are also consistent with Ray (2008). The findings of negative relationship between inflation and stock prices are consistent with that of Chen, Roll and Ross (1986) and Mukherjee and Naka (1995). Further money supply is also found to have negative relationship with manufacturing index given the fact that money supply results in inflation and thus increases discount rate thereby reducing stock prices as suggested by Fama (1981). (iii) The share prices in financial services sector are found to have significant positive long-run relationship with index of industrial production. The positive and significant long-run relationship between real activity and financial services sector index indicates stimulus provided by real activity

18 Impact of Macro-Economic Tactors on Share Trices of India 168 to finance companies in terms of demand for credit and other financial services. Besides, a significant negative relationship is observed with respect to inflation and financial services sector. Boyd, Levine and Smith (2001) and Naceur and Ghazouani (2005) opine that an increase in inflation lowers the real rate of return on money as well as assets in general thereby lowering the incentive to financial intermediaries to lend. The implied reduction in real returns exacerbates credit market frictions. Since these market frictions lead to the rationing of credit, credit rationing becomes more severe as inflation rises. As a result, the financial sector makes fewer loans, resource allocation is less efficient, and intermediary activity diminishes with adverse implications for capital investment. The aggregate effect thus is seen on stock price performances. (iv) There is a positive relationship between money supply and financial sector index and these findings are consistent with that of Mayasami, Howe and Hamzah (2004). The increasing amount of money supply indicates rising flow of credit from financial sector and creates expectation of its positive impact on profitability of financial services companies through high interest income. However, it is found that the impact of changes in money supply to the finance sector is statistically insignificant. (v) The examination of long-run relationship between macroeconomic factors and sectoral indices (Table 4.10) indicate that all the sub-sectors of manufacturing sector under study (textile, chemical, telecom and food Goa university

19 Impact of Macro-'Economic 'Factors on Share 'Prices of India 169 and beverage) get significantly affected largely by same set of macroeconomic variables and the direction of impact is also the same for stock prices in all the sub-sectors. The real economic activity and exchange rates are found to have significant positive relationship with sectoral indices while money supply and inflation are again found to have significant negative relationship with all the sub-sectors of manufacturing sector in India. (vi) International oil prices are found to have significant negative relationship only with textile sector and food and beverage sector although the magnitude of its impact on stock prices in these sectors is found to be much less. The findings are consistent with Maghyereh, A. (2004) who provides evidence that oil market is very weak in influencing stock markets in emerging economies and emerging markets are inefficient in transmitting innovations/shocks in the oil markets. (vii) Share prices in none of the sector are found to have any significant long run relationship with FDI. The main findings of cointegration analysis, thus, reveal that there is a long run equilibrium relationship between stock prices and macroeconomic variables in emerging Indian stock market. This is true for general index as well as sectoral indices. The presence of cointegrating relationship between stock prices and macroeconomic variables repudiates the conclusion of efficient market hypothesis (EMH). Principally, the behavior of stock market may be

20 Impact of Macro -Economic Factors on Share Trices of India 1 70 predicted and therefore the policy makers in emerging markets need to implement macroeconomic policies carefuly if they do not desire to impact the Table 4.10 Cointegrating Relationship Between Macroceconomic Factors and Indian Stock Prices Index IIP Money Inflation Exch. Int. Oil FDI Supply Rate Prices Nifty Composite * * * Index Manufacturing Sector * ** Textile Sector * *** * * *** Chemical Sector * * * Telecom Sector * * * * F&B Sector * * * ** Financial Services * Sector Note: *, " and *' represents significance at 1%, 5% and 10% respectively.

21 Impact of Wacro-Economic 'Factors on Share dices of India 171 stock markets significantly. Further, the findings reveal that there does not exist much scope for earning superior returns based on stock selection from specific sector as the information on macroeconomic variables is made available. This is because the sectoral share prices are affected largely by same set of factors and in the same manner. Some sectoral diversification benefits are however available between manufacturing and financial services sectors given that the share prices in financial services sector in Indian market do not get significantly impacted by exchange rate and international oil prices and money supply. Likewise, equities in textile and food and beverage sector may be avoided during rising international oil prices.