Stock Market And Macroeconomic Variables In India - Free Essay Example

ABSTRACT The present paper is aimed at studying the nature of the causal relationship between stock prices and macroeconomic aggregates in India, if any. By applying the techniques of unità ¢Ã¢â€š ¬Ã¢â‚¬Å"root tests, cointegration and the Granger test the causal relationships between the NSE Index à ¢Ã¢â€š ¬Ã‹Å"Niftyà ¢Ã¢â€š ¬Ã¢â€ž ¢ and the macroeconomic variables, viz., Real effective economic rate (REER), Foreign Exchange Reserve (FER), and Balance of Trade (BoT), Foreign Direct Investment (FDI), Index of industrial production (IIP), Wholesale price index (WPI) using monthly data for the period 1st April 2006 to 31st March 2010 have been studied. The major findings of the study are (i) there is no cointegration between Nifty and all other variables except Wholesale price index (WPI) as per Johansen Cointegration test. Therefore causal relationship between such macro economic variables having no cointegration with nifty is not established. (ii) Nifty does not Granger Cause WPI and WPI also does not Granger Cause Nifty. Key Words: Granger Causality, Macroeconomic Variables, Cointegration, Stock Prices JEL Classification: G1, E4 Introduction The movement of stock indices is highly disposed to the changes in rudiments of the economy and to the changes in future prospects expectations. These expectations are influenced by the micro and macro fundamentals which may be formed either logically or adaptively on economic fundamentals, as well as by many subjective factors which are unpredictable and also non quantifiable. It is believed that domestic economic fundamentals play seminal role in the performance of stock market. However, in the era of globalisation and integration of world economies, domestic economic variables are also subject to change due to the policies adopted and expected to be adopted by other countries or some global events. The common external factors influencing the stock return are stock prices in global economy, the interest rate, foreign investment and the exchange rate. For illustration, capital inflows and outflows are not determined by domestic interest rate alone but also by the changes in the inte rest rate by major economies in the world. Recently, it is experienced that contagion from the US sub prime crisis has played significant movement in the capital markets across the world as foreign hedge funds unwind their positions in various markets. Other burning example in India is the appreciation of Indian currency due to increased inflow of foreign exchange. It has resulted in a decline in the stock prices of major export oriented companies especially in Information technology and textile sectors. The modern financial theory concentrates upon systematic factors as sources of risk and contemplates that the long run return on an individual asset must replicate the changes in such systematic factors. This implies that securities market has an important relationship with real and financial sectors of the economy. This relationship is generally viewed in two ways. The first relationship considers the stock market as a leading indicator of the economic activity in the country, wher eas the second relationship focuses on the possible impact the stock market might have on aggregate demand, predominantly through aggregate consumption and investment. The first case states that stock market leads economic activity, whereas the second case suggests that it follows economic activity. Knowledge of the sensitivity of stock market to macro economic behaviour of key variables and vice-versa is important in many areas of investments and finance. This research may be helpful to comprehend this relationship. Since the decade of 1990 in India, a number of measures have been adopted for economic liberalization of the country. Coupled with this various other steps have also been taken to strengthen the stock market such as opening of the stock markets to international investors, increase in the regulatory power of SEBI, reforms in the capital markets, trading in derivatives, etc. These measures have resulted in noteworthy improvements in the size and depth of stock markets in India and they are beginning to play their due role. Presently, the movement in stock market in our country is viewed and analysed carefully by a large number of global players. An understanding of the macro dynamics of Indian stock market can be valuable for traders, investors and also for the policy makers of the country. Results of the study may help in diagnosing whether the movement of stock market is the result of some other variables or it is one of the causes of movement in other macro variable in the economy. The study also expects to explore whether the movement of stock market is associated with the economy. In this context, the purpose of this paper is to explore such causal relations for India for the period of 2006 to 2010. The complete paper is organised in the four sections. Section I provides review of selected literature on the causal relationship between stock prices and macro economic variables. Section II discusses the data and explains the methodology for testing the stationarity, the existence of cointegration, and the direction of causality if any. Section III reports the results and their interpretation. Finally, Section IV deals with the concluding remarks. I. Review of Literature Many empirical studies have been conducted to study the causal relationship between stock market and macro economic variables. In retrospect of the literature, a number of hypotheses support the existence of a causal relation between stock prices and economic variables. Ma and Kao [1990] unearthed that a currency appreciation has a negative effect on the domestic stock market for an export-dominant country and a favourable effect on the domestic stock market for an import-dominant country, which appears to be consistent with the goods market theory. Bahmani and Sohrabian [1992] establish a bi-directional causality between stock prices (Standard Poors 500 index) and the effective exchange rate of the dollar in the short period of time. However, co-integration analysis did not reveal any long run relationship between the two variables. Abdalla and Murinde [1996] in their research study the relationship between exchange rates and stock prices in the emerging financial markets of India, Korea, Pakistan and the Philippines. As per their study granger causality tests results show uni-directional causality from exchange rates to stock prices in all the sample countries, except Philippines. Ajayi and Mougoue [1996], show significant interactions between foreign exchange and stock markets by using daily data for eight countries, while Abdalla and Murinde [1996] document that a countryà ¢Ã¢â€š ¬Ã¢â€ž ¢s monthly exchange rates tends to lead its stock prices but not the other way around. Pan, et al. [1999] examined the causal relationship between stock prices and exchange rates with the help of daily market data and found that the exchange rates Granger-cause stock prices with less significant causal relations from stock prices to exchange rate. They also find that the causal relationship has been stronger in the aftermath of the Asian crisis. Malliaris and Urrutia [1991] observed that the performance of the stock market might be used as a leading indicator for real economic activities in the United States. For the United Kingdom, Thornton [1993] also found that stock returns tend to lead real income. In related work and Chang and Pinegar [1989] also concluded that there is a close relationship between stock market and the domestic economic activity. Chen, Roll, and Ross [1986], Bodie [1976], Fama [1981], Geske and Roll [1983], Pearce and Roley [1983], Pearce [1985], James et. al. [1985], and Stulz [1986] and many papers have tried to show empirical associations between macroeconomic variables and security returns. Bodie [1976], Fama [1981], Geske and Roll [1983], Pearce and Roley [1983] and Pearce [1985] document that inflation and money growth has an inverse impact on equity market. Many experts however believe that positive effects will outweigh the negative effects and stock prices will eventually rise due to growth of money supply [Mukherjee and Naka, 1995]. Mukherjee and Naka [1995] reveal in their study that cointegration relation existed and positive relationship was found between the Japanese industrial production and stock return. However, Cutler, Poterba, and Summers [1989] (CPS) find that Industrial Production growth is significantly positively correlated with real stock returns over the period from 1926 to 1986, except the 1946- 85 sub-period. In context of developing countries Mustafa, K et al. [2007] have done a study to investigate the empirical relationship between the stock market and real economy in Pakistan economy by taking up various variables like per capita GDP, output growth to represent the Real economy and stock market liquidity, size of stock market representing the Stock Market. Cointegration and Error Correction Model Technique has been adopted to establish the empirical relation, if any between the two from the time period 1980- 2004. Husain, F. [2006] examined the causal relationship between stock price and real sector variables of Pakistan economy, using annual data from 1959-60 to 2004-05. It studied the causal relationship between them using various econometric techniques like ECM, Engle-Granger co integrating regressions and Augmented Dickey Fuller (ADF) Unit Root tests. The study indicates the presence of a long run relationship between the stock prices and real sector variables. More recently, Humpe, A., et al. [2009] have tried to relate the macro economic variables with long term stock market movements in US and Japan within the framework of a standard discounted value model by using monthly data over 40 years. A cointegration analysis has been applied to model the long term relationship between the industrial production, money supply, the consumer price index, long term interest rates and stock prices in US and Japan. The authors have found a significant relation between the macro economic variables and stock market in the long run. In Indian context, Abhay Pethe and Ajit Karnik [2000] has investigated the inter à ¢Ã¢â€š ¬Ã¢â‚¬Å" relationships between stock prices and important macroeconomic variables, viz., exchange rate of rupee vis-ÃÆ'  -vis the dollar, prime lending rate, narrow money supply, and index of industrial production. The analysis and discussion are situated in the context of macroeconomic changes, especially in the financial sector, that have been taking place in India since the early 1990s. Chakradhara Panda, et al. [2001] explored the causal relations and vibrant interactions among monetary policy, real activity, expected inflation and stock market returns in the post liberalization period by using a vectorà ¢Ã¢â€š ¬Ã¢â‚¬Å"autoregression (VAR) approach. The major findings of their study are (i) expected inflation and real activity do affect stock returns, (ii) monetary policy loses its explanatory power for stock returns when expected inflation and real activity are present in the system, ( iii) the relationships of monetary policy, expected inflation and real activity with stock returns lack consistency, (iv) there is no causal linkage between expected inflation and real activity. Bhattacharya and Mukherjee [2002] studied the nature of the causal relationship between stock prices and macro aggregates for the period of 1992-93 to 2000- 2001. The results of their study show that there is no causal relationship between stock price and macro economic variables like national income, money supply, and interest rate but there exists a two way causation between stock price and rate of inflation. Their result further points that index of industrial production lead the stock price. Kanakaraj, A. et al. [2008] have examined the trend of stock prices and various macro economic variables between the time periods 1997-2007. They have tried to explore upon and answer that if the recent stock market boom can be explained in the terms of macro economic fundamentals and have concluded by recommending a strong relationship between the two. As per the review of the literature there is no unanimity with regard to the causal relationship between key macro between key macro economic variables and stock prices. This relationship is different in different stock markets and time horizons in the literature. This paper makes an attempt to add to the existing literature by providing robust result which is based on more than one technique, about causal links for a period of 4 years monthly data. II. Empirical Methodology and Data For drawing useful inferences time series analysis must be based on stationary data series. Generally a data series is said to be stationary if its mean and variance are constant (non-changing) over a given period of time and the value of covariance between two time periods depends only on the distance or lag amid the two time periods and not on the actual time at which the covariance is computed. The correlation between a series and its lagged values are assumed to depend only on the length of the lag and not when the series started. This property is known as stationarity and any series obeying this is called a stationary time series. To test the stationarity of a series three unit root tests have been applied. Stationarity of the time series has been tested by using Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests. [Dickey and Fuller (1979, 1981), Gujarati (2003), Phillips and Perron (1988), Enders (1995)]. For testing null hypothesis of stationarity, KPSS test has also been applied for robustness [Kwiatkowski, Phillips, Schmidt. and Shin (1992)]. Augmented Dickey Fuller (ADF) Test Augmented Dickey-Fuller (ADF) test has been carried out which is the modified version of Dickey Fuller (DF) test. ADF makes a parametric correction in the original DF test for higher-order correlation by assuming that the series follows an AR (p) process. The ADF approach controls for higher-order correlation by adding lagged difference terms of the dependent variable to the right-hand side of the regression. The Augmented Dickey-Fuller test specification used here is as given below: p à ¢Ã‹â€ Ã¢â‚¬  yt = ÃŽÂ ±0 + ÃŽÂ »yt-1+ ÃŽÂ £ÃƒÅ½Ã‚ ³ià ¢Ã‹â€ Ã¢â‚¬  yt-i +ut (I) i=1 Phillips-Perron (PP) Test Phillips and Perron (1988) adopt a nonparametric method for controlling higher-order serial correlation in a series. The test regression for the Phillips-Perron (PP) test is the AR (1) process. The ADF test amends for higher order serial correlation by adding lagged differenced terms on the right-hand side and the PP test makes a correction to the t-statistic of the coefficient from the AR(1) regression to adjust the serial correlation in ut. The correction is nonparametric in nature. The important plus of Phillips-Perron test is that it is free from parametric errors. Phillips-Perron test allows the disturbances to be weakly dependent and heterogeneously distributed. In view of this, PP values have also been checked for stationarity. KPSS Test A major criticism of the ADF unit root testing procedure is that it cannot differentiate between unit root and near unit root processes especially when using short samples of data. This prompted the use of the KPSS test, where the null is of stationarity against the alternative of a unit root. This guarantees that the alternative will be accepted (null rejected) only when there is strong evidence for (against) it [Kwiatkowski, Phillips, Schmidt. and Shin (1992)]. Co-integration Test Using non-stationary series, cointegration analysis has been used to examine whether there is any long run equilibrium relationship. For instance, when non-stationary series are used in regression analysis, one as a dependent variable and another as an independent variable, statistical inference become tricky [Granger and Newbold, 1974]. If two variables are cointegrated, they would on average, not drift apart over a period of time this concept provides insight into the long-run relationship between the two variables and testing for the cointegration between two variables. In the present case, Johansenà ¢Ã¢â€š ¬Ã¢â€ž ¢s Maximum Likelihood procedure for Cointegration has been applied. Granger Causality Test The dynamic linkage is examined using the concept of Grangerà ¢Ã¢â€š ¬Ã¢â€ž ¢s causality test (1969, 1988). Granger causality test is applied on a stationary series. This test analyses the fact that between two given factors which one is the causing one and which factor is getting affected by another. The test is based on following two regression equations: n n Yt = ÃŽÂ £ ÃŽÂ ±i Xt-i+ ÃŽÂ £ ÃŽÂ ²j Yt-j+ u1t __________________________________ (II) i=1 j=1 n n Xt = ÃŽÂ £ ÃŽÂ »i Xt-i+ ÃŽÂ £ ÃŽÂ ´j Yt-j+ u2t __________________________________ (III) i=1 j=1 In the two equations given above it has been assumed that disturbances u1t and u2t are not correlated with each other. Equation (II) postulates that current Y is related to its own past values as that of X and next equation (III) postulates a similar behaviour of X. There are following four possibilities of cause and effect: Unidirectional causality from X to Y is indicated if the estimated coefficients on the lagged X in equation (II) are statistically different from Zero as a group (i.e. ÃŽÂ £ÃƒÅ½Ã‚ ±i à ¢Ã¢â‚¬ °Ã‚   0) and the set of estimated coefficients on the lagged Y in equation (II) is not statistically different from zero (i.e. ÃŽÂ £ÃƒÅ½Ã‚ ´j à ¢Ã¢â‚¬ °Ã‚   0). Unidirectional causality from Y to X is indicated if the estimated coefficients on the lagged X in equation (III) are statistically different from Zero as a group (i.e. ÃŽÂ £ÃƒÅ½Ã‚ ±i à ¢Ã¢â‚¬ °Ã‚   0) and the set of estimated coefficients on the lagged Y in equation (III) is statistically different from zero (i.e. ÃŽÂ £ÃƒÅ½Ã‚ ´j à ¢Ã¢â‚¬ °Ã‚   0). Feedback, or bilateral causality is suggested when the sets of X and Y coefficients are statistically significant different from zero in both the regression equations. Independence is suggested when the sets of X and Y coefficients are not statistically significant in both the cases. Lag-Length Criteria Determination of the lag length of an autoregressive process is one of the most difficult tasks in applying econometrics techniques. To overcome this difficulty various lag length selection criteria (Akaike Information Criterion, Schwarz Information Criterion, Hannan-Quinn Criterion, Final Prediction Error, Corrected version of AIC) have been proposed in the literature. Asghar and Irum have compared Akaike Information Criterion, Schwarz Information Criterion, Hannan-Quinn Criterion, Final Prediction Error, Corrected version of AIC for lag length selection for three different cases that is under normal errors, under non-normal errors and under structural break by using Monte Carlo simulation. The study shows that the performance of all these criteria improves with an increase in the sample size. For sample size of 30, although AIC and FPE have the highest probability of correct estimation but all other criteria also perform very well. For sample size equal to 60, probability of correct estimation for HQC is highest but AIC and SIC also has probability of correct estimation close to that of HQC. For large sample size (120 or greater) performance of SIC is the best. This shows that AIC and FPE are efficient but not asymptotically consistent where as SIC, AIC and HQC are asymptotically consistent criteria. Liew and Khim [2004] have carried out this stud y for both normal and non-normal errors. They found that HQC is the best for large samples. In the present study lag length is determined on the basis of Hannan-Quinn Information Criteria. III. Empirical Analysis The descriptive statistics for all four variables are calculated and presented in table 1. These variables are Real Effective Economic Rate, Balance of Trade, Foreign Exchange Reserve and NSE Nifty. The skewness coefficient, in excess of unity is taken to be fairly extreme [Chou 1969]. High or low kurtosis value indicates extreme leptokurtic or extreme platy-kurtic [Parkinson 1987]. Generally values for zero skewness and kurtosis at 3 represents that the observed distribution is normally distributed. It is seen that the frequency distribution of the above mentioned variables are not normal. Jarque-Bera statistics also indicates that the frequency distribution of the underlying series does not fit normal distribution. Further, the coefficient of variance indicates that the Foreign Direct Investment, Balance of Trade, Foreign Exchange Rate and Nifty are relatively more volatile in comparison to Index of Industrial Production, Wholesale Price Index and Real Effective Exchange Rate. Table 1: Descriptive Statistics BOT FDI FER IIP NIFTY_CL REER WPI   Mean -33750.19   8658.104   1046881.   273.6208   4205.306   97.51708   224.6375   Median -29714.00   7836.500   1166866.   269.2500   4305.400   97.56500   226.5500   Maximum -15376.00   22529.00   1301645.   347.3000   6144.350   106.0900   250.5000   Minimum -69925.00   2405.000   690730.0   225.2000   2674.600   87.48000   199.0000   Std. Dev.   14217.27   4646.714   214050.1   26.96276   872.2687   5.679449   15.35988   Skewness -0.759591   0.869245 -0.452362   0.620278   0.098875 -0.074652   0.116621 Co-eff. of Variance -42.125 53.66896 20.44646 9.854061 20.7421 5.824056 6.83763   Kurtosis   2.751454   3.416896   1.530345   3.330791   2.359419   1.856711   1.689008   Jarque-Bera   4.739378   6.392298   5.956823   3.296808   0.898900   2.658803   3.546204   Probability   0.093510   0.040919   0.050874   0.192357   0.637979   0.264636   0.169805   Sum -1620009.   415589.0   50250309   13133.80   201854.7   4680.820   10782.60   Sum Sq. Dev.   9.50E+09   1.01E+09   2.15E+12   34168.56   35760076   1516.039   11088.51   Observations   48   48   48   48   48   48   48 The first and simplest type of test one can apply to check for stationarity is to actually plot the time series and look for evidence of trend in mean, variance, autocorrelation and seasonality. If any such patterns are present then these are signs of non-stationarity. The seven time series displayed in figure-1 exhibit different such patterns. Foreign Exchange Reserve, Index of Industrial Production and Wholesale Price Index seem to exhibit a trend in the mean since they have a clear upward slope. In fact, sustained upward or downward sloping patterns (linear or non-linear) are signs of a non-constant mean. The time series on Balance of Trade, Nifty and Real Effective Economic Rate in the figure contain an obvious trend in both mean and variance. This is a sign of non-stationarity. Figure 1: Dataset Graph Apart from visual inspection, formal test for stationarity is essential to opt for appropriate methodological structure. As a first step, we tested all the variables (Balance of Trade, Foreign Exchange Reserve, Foreign Direct Investment, Nifty, Real Effective Economic Rate, Index of Industrial Production and Wholesale price index) for stationarity by applying ADF, PP unit root test and KPSS stationarity test. The result of ADF, PP and KPSS statistics are given in table-2. On the basis of ADF statistics and PP test, all the series are found to be non-stationary at levels except Foreign Direct Investment which is significant at one percent. Further, ADF statistics and PP test rejects null hypotheses of unit root in case of first differences for all the variables. In the end, KPSS test is also applied which has a null hypothesis that series is stationarity. In this case, all variables are non stationary in levels (except nifty) and stationary in first differences. Assuming all the varia bles are non-stationary at levels and stationary at first differences on the basis of ADF, PP, KPSS tests and visual inspections, Johansenà ¢Ã¢â€š ¬Ã¢â€ž ¢s approach of cointegration and Granger causality test have been applied. Table 2: Unit Root Test Variables Null Hypothesis: Variable is non-stationary Null Hypothesis: Variable is non-stationary Null Hypothesis: Variable is stationary Augmented Dicky Fuller Test Statistic Phillips-Perron Test Statistic Kwiatkowski-Phillips- Schmidt-Shin test statistic Level First Difference Level First Difference Level First Difference t- statistic p-value t- statistic p-value t- statistic p-value t- statistic p-value LM-Stat. LM-Stat. BOT -2.389654    0.1500 -7.779047* 0.0000* -2.389654    0.1500 -7.724768* 0.0000* 0.515649** 0.043815 FER -1.795759 0.3781   -5.191802* 0.0001* -1.651677    0.4488 -5.360630* 0.0000* 0.759324* 0.341829 NIFTY_CL -1.638304    0.4554 -6.201501* 0.0000* -1.727747    0.4110 -6.205292* 0.0000* 0.145549 0.086579 REER -0.958878    0.7602 -5.515513* 0.0000* -1.236302 0.6510 -5.591141* 0.0000* 0.422529*** 0.184626 IIP 0.234639 0.9719 -8.117466* 0.0000* -1.213731 0.6609 -13.32941* 0.0000* 0.823505* 0.133640 WPI -0.812230 0.8061 -3.547469** 0.0109** -0.756054 0.8220 -3.643894* 0.0085* 0.860559* 0.046077 FDI -3.962301 0.0035* -10.05718* 0.0000* -3.955949 0.0035* -10.26543* 0.0000* 0.378648*** 0.065507 Asymptotic critical values*: 1% Level -3.48 -3.48 0.74 5% Level -2.88 -2.88 0.46 10% Level -2.57 -2.57 0.35 Figure 2: Dataset Graph To explore whether there is any long-run relationship between Indian stock markets and macro economic variables such as exports, exchange rate, index of industrial production, foreign direct investment, interest rate and money supply, Johansenà ¢Ã¢â€š ¬Ã¢â€ž ¢s cointegration test has been applied. The number of lags in cointegration analysis is chosen on the basis of Hannan-Quinn Information Criterion. Before discussing the results, it is important to discuss what it implies when two variables are cointegrated and when they are not. When two variables are cointegrated, it implies that the two time series cannot wander off in opposite directions for very long without coming back to a mean distance eventually. But it does not mean that on a daily basis the two series have to move in synchrony at all. When two series are not cointegrated it implies that the two time series can wander off in opposite directions for very long without coming back to a mean distance eventually. As is concluded by unit root tests that all the variables considered except the Foreign Direct Investment (FDI) are I(1), while the FDI is I(0). So for the testing of cointegration among the variables, the FDI is dropped from the further analysis. Results indicate that Nifty and Wholesale Price Index may be cointegrated in the long run as the results vary depending on the varying assumption about trend and intercept. However, all other variables and Nifty are not cointegrated in the long run under all assumptions. In case of Balance of Trade Nifty, Foreign Exchange Reserve Nifty, Real Effective Exchange Rate Nifty and Index of Industrial production à ¢Ã¢â€š ¬Ã¢â‚¬Å" Nifty, there is no evidence of co-integration. (See table-3). Table 3: Johansen Co-Integration Test: Nifty and Other Macro Variables (Number of Cointegrating Relations by Model) Data Trend: None None Linear Linear Quadratic Test Type No Intercept Intercept Intercept Intercept Intercept No Trend No Trend No Trend Trend Trend NIFTY_CL à ¢Ã¢â€š ¬Ã¢â‚¬Å" BOT(1) Trace Max Eig 0 0 0 0 0 0 0 0 0 0 NIFTY_CL à ¢Ã¢â€š ¬Ã¢â‚¬Å" FER(1) Trace Max Eig 0 0 0 0 0 0 0 0 0 0 NIFTY_CL à ¢Ã¢â€š ¬Ã¢â‚¬Å" REER(1) Trace Max Eig 0 0 0 0 0 0 0 0 0 0 NIFTY_CL à ¢Ã¢â€š ¬Ã¢â‚¬Å" IIP(2) Trace Max Eig 0 0 0 0 0 0 0 0 0 0 NIFTY_CL à ¢Ã¢â€š ¬Ã¢â‚¬Å" WPI(2) Trace Max Eig 0 0 0 0 0 0 1 1 2 2*Critical values based on MacKinnon-Haug-Michelis (1999) **Appropriate lag is given in parentheses on the basis of Hannan-Quinn Information Criteria Table 4: Pairwise Granger Causality Tests Lags: 2   Null Hypothesis: Obs F-Statistic Prob.     D(WPI) does not Granger Cause D(NIFTY_CL)   45   0.38604 0.6822   D(NIFTY_CL) does not Granger Cause D(WPI)   0.99976 0.3770 Since there is no evidence of cointegration in the macro economic variables and Nifty series the test of Granger Causality is not applied between Nifty and such variables except Wholesale Price Index which is cointegrated with Nifty under the model of Linear Trend Intercept and Quadratic Trend Intercept. The test results in table 4 suggest that we fail to reject the null hypothesis of Granger non-causality from WPI to NIFTY_CL as well as the null hypothesis of Granger non-causality from NIFTY_CL to WPI. The results suggest that the NSE Index Nifty neither leads Wholesale Price Index nor Wholesale Price Index lead the Nifty. This implies that the stock market cannot be used as a leading indicator for future growth in wholesale price index in India. IV. Concluding Remarks The purpose of the present study is to explore the relationships between stock prices and the key macro variables representing real and financial sector of the Indian economy. These variables are the index of industrial production, foreign exchange reserves, foreign direct investment, balance of trade, real effective exchange rate, wholesale price index and NSE Nifty. The present analysis is based on monthly data from April, 2006 to March, 2010. Although there seems to be a significant relationship between macro economic variables and stock market but results of our study show that stock market boom is not much supported by the real economic fundamentals. Even there is no sign of causality between the variables which are integrated of same order which further concretizes the issue that stock markets in India are in their childhood phase as their impact on real economic variables is less as that in developed countries and moreover effect of real economic variables is almost nil on stock market index in case of causality. To solve this problem monthly data was used from April 2006 to March 2010 and the basic and believed to be à ¢Ã¢â€š ¬Ã…“indicatorà ¢Ã¢â€š ¬? variables were used and studied and analysed by first applying the basic statistical and analytical tools such as unit root test, cointegration and finally Granger causality. The results shows that series of variables used are not stationary at levels but at first difference. Further, there is no evidence of cointegration among the economic indicators chosen and Indian stock market except with inflation (Wholesale Price Index). Granger Causality test was applied between the two variables found integrated of same level I(1) i.e. Nifty and WPI. The analysis pointed that there are no sign of causality between the two variables and neither Nifty Granger causes WPI nor WPI causes Nifty. Thus implying that real sector is not causing the vibes in stock market and even the volatility in it is due to some other external factors and not these real economic factors. Adding to it, is one more reason that just 2 to 3% of the Indian population invests in stock market which makes it not so good representative of the Indian financial health.

Essay on David Fletcher Case - 910 Words

This case explores the problems managers face when assembling a team. David Fletcher, is an overworked portfolio manager of the Emerging Growth Fund at Jenkins, Fletcher Partners (JFP), an investment management firm in New York. As an individual, his superior performance throughout his career has earned him an outstanding reputation. Starting out as a clerk, he rose through the ranks of Wall Street to eventually manage the two most aggressive mutual funds at a major investment firm. Success at this firm only added to his reputation and lead to his current role at JFP, a smaller firm with an informal culture. At JFP, Fletcher is challenged with the new responsibility of managing a team, in addition to managing his portfolio. Despite†¦show more content†¦Though Fletcher has enjoyed long-term success as a portfolio manager, he stumbles as a team manager. One example is in his relationship with Stephanie Whitney. Though he described is as a â€Å"mentor-protà ©gà ©Ã¢â‚¬  relationship, he admits to having little time to train her. While he provided her with general career guidance, he explains that it was her own resourcefulness and initiative that allowed her to ascend from an administrative assistant position to the role of analyst. This transition, as noted by one of her colleagues, was difficult for Whitney and she struggled with establishing her identity as an aspiring portfolio manager. Because of Fletcher’s hands-off approach to managing people, Whitney’s growth was stifled under his management, which was a contributing factor to her eventual resignation. Hiring Brian Doyle without considering how he would get along with Whitney was another mistake Fletcher made in assembling his team. A seasoned financial consultant to high-technology firms in Silicon Valley, Doyle had frequent contact with Fletcher over the years and offered valuable industry knowledge. However, he did not meet Whitney prior to joining the team and it soon became evident to Fletcher that tension existed between the two. It isn’t surprising that Fletcher failed to consider their compatibility. Being a task-oriented person, he only values a person’s performance; gettingShow MoreRelatedDavid Fletcher Case Study711 Words   |  3 PagesCase Study: David Fletcher 1. What are David’s greatest strengths as a team leader? Greatest developmental needs? How did these strengths and weaknesses affect David’s ability to build a successful team the first time around? Points for Class Discussion: Greatest Strengths: * David is focused on the objective of the team and he is well aware of the function of the team once assembled. * David is also good in building mutual connection with his team members as exemplified by hisRead MoreDavid Fletcher Case Study Paper1697 Words   |  7 PagesDavid Fletcher Case Study Paper David Fletcher, a successful investment portfolio manager with Jenkins, Fletcher Partners or â€Å"JFP†, has been having problems with building and maintaining his team of research analysts. David is described by his peers as being calm under pressure, having a natural instinct to pick investments, and self-motivated. The intense workload David is managing has required him to put together a team to handle the time consuming aspect of obtaining and sifting through largeRead MoreDavid Fletcher Case Essay example2226 Words   |  9 Pages Jenkins, Fletcher Partners (JFP) has the potential to thrive and succeed in the financial service industry with stimulated, productive, and satisfied employees. However, there are small and large issues to be addressed in order to carry that in action. In this specific case analysis, we analyze the issues hindering JFP from further development, and suggest respective and appropriate suggestions to resolve those problems. First, a thorough evaluation of JFP shed light on a number of issues: TheRead MoreDavid Fletcher Case Study Essay1959 Words   |  8 Pagesand events of the case including the critical issues leading to the departure of Stephanie Whitney. David Fletcher is a portfolio manager with many years of experience and success under his belt. He currently is a limited partner managing an Emerging Growth Fund for Jenkins Fletcher Partnership or JFP. The company was small when David started and consisted of a CEO, Paul Jenkins, CFO, 2 financial assistance, 4 research analyses, 1 research assistant and a receptionist. David first started withRead MoreDavid Fletcher Case Study Essay1603 Words   |  7 Pagesenvironment for portfolio management changed and as Fletcher began being overwhelmed with research, he sought to create a team of analysts that could assist him with his work. Fletcher failed to build this team on his first attempt as a result of several causes. There were multiple mistakes that Fletcher made that can be seen in his interactions with people. The first was his assistant Whitley which he had a close relationship with. Before Fletcher hired Doyle, he did it hastily without consultingRead MoreFletcher Case Study Essay1288 Words   |  6 Pages653: Fletcher Case Study This study analyzes and discusses three shortcomings that prevented investment portfolio manager David Fletcher of Jenkins, Fletcher Partners (JFP) from realizing his team oriented operational expectations. His failures were attributed to poor personnel management, the inability to effectively select or establish team structure, and the failure to devise the appropriate incentives to motivate and reward employees. After careful review it is recommended that Fletcher mustRead MoreProtection Of Individual Property Rights1689 Words   |  7 Pagesmajor cases that have gone through the United States Supreme Court have made an influence on how laws and amendments of the United States Constitution are construed. Protection of individual property rights is a controversial topic in the political spectrum and it has advanced with different visions of values that should be protected in American Society. The Fifth Amendment due process and clause jurisprudence reflects the notion of property. The following four U.S Supreme Court cases, Fletcher v. PeckRead More A Reasonable Approach to Euthanasia Essays1566 Words   |  7 PagesVoluntary but indirect euthanasia is chosen in advance. Direct but involuntary euthanasia is done for the patient without his or her request. Indirect and involuntary euthanasia occurs when a hospital decides that it is time to remove life support (Fletcher 42-3).    Euthanasia can be traced as far back as to the ancient Greek and Roman civilizations. It was sometimes allowed in these civilizations to help others die. Voluntary euthanasia was approved in these ancient societies. As time passedRead MoreEthical Nursing1709 Words   |  7 Pagesthat she undergo a hysterectomy to which she agreed because she was in severe pain. While reading the informed consent papers before theatre, Carol made an explicit request that she should not be transfused with blood or blood products even in the case of extensive blood loss following surgery. Her reasons for this were that she belonged to a group of Jehovah’s witnesses, and it was simply against her beliefs. Ethics can be defined as the philosophical study of the moral value of human conductRead MoreThe Los Angeles County Federation Of Labor Essay1702 Words   |  7 Pageslabor bodies use their political influence to lobby for regulations that are favorable to their workers(Ness, 2011). For example, there is an ongoing court case involving the Los Angeles County Federation of Labor representing an illegal immigrant who found himself in trouble for raising the problem of exploitation in terms of wages. The case resonates with the President Obama’s Executive Order on Illegal Immigrants. Therefore, the similarities between the two factions and the ability of the labor

A Process of Decision Making by Caregivers of Family...

Article review Sanford, J., Townsend-Rocchicciolli, J., Horigan, A., Hall, P. (2011). A process of decision making by caregivers of family members with heart failure. Research Theory for Nursing Practice, 25(1), 55-70. Q1. What is the purpose of this research? The purpose of this research is to better understand how caregivers of patients with heart failure make decisions about patient care. Q2. What is the research question (or questions)? This may be implicit or explicit. Can a generalized, stage-based approach to decision-making for caregivers of patients with heart failure be constructed (similar to that of the stages of grief rubric)? Q3. What theories, frameworks, models or concepts may have influenced the researchers choice of a research design? If this is not stated specifically, list any that are implied. The explicitly stated theoretical approach was one of grounded theory, or the discovery of a theory pertaining to specific circumstances based upon the analysis of data. This is rooted in an idea that nursing research should be grounded in practice. Theory should be governed by facts, not vice versa. Q4. How do the authors describe the design of this study? Because caregivers must often assume control over the care of a patient with heart failure, the design of the study was to examine the decision-making processes caregivers of patients with heart failure go through by talking to a representative sampling of the population. The stagesShow MoreRelatedA Process of Decision Making by Caregivers of Family Members with Heart Failure3389 Words   |  14 PagesAn Analysis of Standford et al.’s Study 1|P a ge An Analysis of Sanford, Townsend-Rocchicciolli, Horigan, Hall’s Study A Process of Decision Making by Caregivers of Family Members With Heart Failure A research critique submitted by Thelma Augustin, Melody Alexander, Ashley Breaux, Nissa Fisher, Kamaria Harris, Thao Huynh, Jeris Jensen, Leslie King, and Susan Livengood, Master of Science in Nursing Research College of Nursing 2012 An Analysis of Standford et al.’s Study 2|P a ge Read MoreChronic Diseases Are The Leading Cause Of Death And Disability1586 Words   |  7 Pagespersonal and social factors. Uncertainty can increase stress, anxiety and loss of control. An illness rather than a disease approach to chronic and complex illness is essential as nurses are not only required to address the pathophysiological disease process, but must also be able to understand people’s individual experiences and recognize their specific needs in order to provide appropriate care and achieve better health outcomes. According to Larsen et al (2013, p4) ‘the terms disease and illnessRead MoreThe Use Of The Theory Transactional Model Of Stress And Coping1727 Words   |  7 Pagesappraisal period the person is evaluating coping options to best deal with the changes and undesirable conditions that may have an impact on their well-being after identifying whether they do or do not have a stake in the encounter. They are making decisions on whether to use internal options of coping such as power and inner strength; or whether to use external options such as peer support or professional help. This time period is where resources are evaluated to decide how to create a more positiveRead MoreThe Aging Population Of America9973 Words   |  40 Pagespast resulted in a decreased life expectancy. In addition to needing more medical care, the elderly often relies on an informal network of friends and family to help them with their daily needs. Unfortunately, the number of unofficial caregivers is also expected to decline. In 2010, researchers estimated that there were seven potential caregivers for every elderly adult over age 80. This ratio will drop to four to one by 2030 and eventually fall to three to one by 2050, because baby boomers areRead MoreNVQ level 58726 Words   |  35 Pagesworkers need to get to know the person beyond the diagnosis and build relationships with patients and carers. SHARING OF POWER AND RESPONSIBILITY - respecting preferences and treating patients as partners in setting goals, planning care and making decisions about care, treatment or outcomes. ACCESSIBILITY AND FLEXIBILITY - meeting patients individual needs by being sensitive to values, preferences and expressed needs. Giving patients choice by providing timely, complete and accurate informationRead MoreEquipped for Efficiency: Improving Nursing Care Through Technology12192 Words   |  49 Pagesnurses: control and influence over their workday, workload, and workflows that enable them to be productive and efficient; an ability to deliver high-quality care and do their best for patients; and collaboration with fellow care providers in making decisions.1, 2 Nurses’ high job satisfaction also influences patient satisfaction. In one study, nursing care was the primary factor in how patients viewed their hospital stay. The more satisfied patients were with their nurses, the more satisfied theyRead MoreStigma And Discrimination Face By People Living With Hiv / Aids2558 Words   |  11 Pagesorientation, drug use/abuse and death. Once stigmatised, the person is discredited as an acceptable member of society, hence the term â€Å"spoiled identity† coined by Pearson et al., (2009) to describe the separation of the stigmatised person from â€Å"normal† members of society. Once labelled as an â€Å"other,† the stigmatised individual is then subjected to discrimination, the action following the cognitive process of stigmatised. LO1: Identify characteristics of Quantitative and Qualitative research methodsRead MoreUnethical Behaviour12228 Words   |  49 PagesSenator from North Carolina; and Archbishop Bernard Law of the Boston Roman Catholic Diocese bring to mind those whose previous success ended in humiliation. As a result, several sobering questions arise including how leaders made such poor ethical decisions, what factors contributed to their ethical/moral meltdowns, and how leaders can avoid â€Å"the perfect storm† of leadership demise in the future. Therefore, this paper provides (a) a brief overview of definitional terms, (b) a conceptual framework forRead MoreCaring for People with Additional Needs11935 Words   |  48 Pagesexplanation with great content of the effects on people who are in need of these services due to their additional needs. Finally, I intend to record in depth and show understanding of each stage of the care management process and evaluate how it is used to access, pla n, implement, monitor and review individual care plans. Definition of disability â€Å"A physical or mental impairment, which has a substantial and long-term adverse effect on a person s ability to carry out normal day-to-dayRead MoreAdvancing Effective Communicationcommunication, Cultural Competence, and Patient- and Family-Centered Care Quality Safety Equity53293 Words   |  214 PagesAdvancing Effective Communication, Cultural Competence, and Patient- and Family-Centered Care A Roadmap for Hospitals Quality Safety Equity A Roadmap for Hospitals Project Staff Amy Wilson-Stronks, M.P.P., Project Director, Health Disparities, Division of Quality Measurement and Research, The Joint Commission. Paul Schyve, M.D., Senior Vice President, The Joint Commission Christina L. Cordero, Ph.D., M.P.H., Associate Project Director, Division of Standards and Survey Methods, The Joint

Competitive Strategy vs Value Innovation free essay sample

From the last few decades, the emphasis of strategy has been on the competitive advantage (as laid down by Michel Porter in 1980). This is evident from the cut throat competition amongst the various industrial sectors, be it at domestic or global level. Every company or firm in their respective industries strives hard to grab a bigger market share than its peers. The motive is to surpass the profits/revenues of the latter. But in the recent times, the scenario has been a strayed. Instead of following the cliche notion of competitive advantage, the present day firms have gathered a new perspective of profit making i. e. Value innovation’. I am going to take a look at both of them and eventually try to compare and contrast the two perspectives. STRUCTURE Before going into the details of two scenarios, there is a need to understand that what strategy actually implies. Different businessmen have their own way of explaining strategy. According to (Hitt, Ireland Hoskisson, 2009 p. ) ,A strategy is an integrated and coordinated set of commitments and actions designed to exploit the core competencies and gain a competitive advantage. Michael Porter (1996) defines strategy in terms of competitive strategy. He asserts that the notion of strategy lies in being at a competitive position and adding value through a combination of activities that are different from that of competitors. Strategy is a pattern of the fundamental goals of the walk and planned the distribution of resources and the organization of interaction with the market, competitors and factor-environmental factors. -John A. Byrne So the selected strategy lays down the dos and don’t’s of an organization. From quite a long time, competitiveness has been in vogue. The firms in a particular industry try to imitate each other. Any firm enjoys the competitive advantage when its rivals are not able to emulate the profits that it makes. So competition comes out to be the most essential factor here. But this happens for a transient period of time. In order to sustain themselves in the value creating strategy, the firms imitate each other. It is where the competitive advantage fails. According to (Porter 1980, p. 12) the basic unit of analysis and business are industry and product respectively. Thus analysis of industrial structure holds utmost significance in forming a competitive strategy. A set of five forces define an industry structure and hence shape the competitive in an industry. These forces are a means of understanding an industrys current profitability as well as effective positioning. In other words they depict whether an industry is attractive or unattractive in the market place. Thus these vary from industry to industry. The five forces according to ( J. H. M. de Jonge 2011) are as follows. The entry is guided by the some of these barriers like when the company in question enjoys economies of scale, product differentiation and the entrants need capital requirements and switching cost and strict government policies thus making it difficult for the newcomers to enter the industry. COMPETITORS: There are a number of factors that guide the rivalry between the competitors. These include numerous equally balanced competitors, insufficient industry growth, high storage costs to name a few. The substitutes are the products that have quite the same function as companys own products. e. g. Plastic for aluminum. If there is high threat from the substitutes, then the industrys profitability and growth potential suffer. For e. g. With the advent of Skype, telephone services have experienced a major setback.The bargaining power of suppliers is more when they are more concentrated, not dependent upon revenues and pose a threat of forward integration. The bargaining power of buyers is high when buyers buy in bulk, have little consideration for quality and may threaten to integrate backwards. After having discussed the five factors that form an essential tool in laying down the industrial structure, now I am going to discuss the three main generic strategies that are required to position a company in the market place. It is said that the five forces measure the companys attractiveness which is indeed the primary factor and the secondary factor is its position in the market, this is guided by the generic strategies. Porters 1980 generic strategies model (Antony Michail, 2011) Â  According to (Antony Michail, 2011) in order to be following the strategy of cost leadership, a firm needs to be the low cost producer (Porter, 1980). It can gain the cost advantage by means of economies of scale, innovative technology, cheap raw materials, etc. They can do so by grabbing bigger market share through lowering their own prices or by maintaining average prices, thus increasing profitability (Porter, 1980). For e. g. Wal-Mart has been utilizing this strategy. It is successful because of its large scale and efficient supply chain, thus allowing their items at low prices and to profit off thin margins at a high volume (Antony Michail, 2011) This incorporates development in product or services such that it offers unique quality and is valued by the customers (Porter 1980). The added value enables the firms to charge premium price for it. They have the resources and core competencies. They have skilled production team and efficient sales network. The drawback is that they can be a t loss if their competitors imitate the product design or there is decline in demanded consequent to changing customers taste. e. g Apple computers have been profiting by implementing the differentiation strategy. By differentiating their product because they get desired value. Owing to lesser number of substitutes they are the market leaders and it launches its product only when they have enough resources to sustain themselves in the market for long. This is what confers them a competitive advantage. Unlike the other two, it focuses on narrow market segment and thus practices both differentiation and low cost. Here the firms set out to serve the niche markets. Ferrari and Rolls Royce are perfect examples of niche players in the automobile industry. These two companies have a niche of premium products available at a premium price and they occupy a small percentage of worldwide market (Drypen, 2010) These are the primary and secondary factors that help company achieve competitive advantage and sustain itself in the market place. According to Porter(1980. 985) the competitive strategy is related to economics concept where long term competition and imitation are the main factors. This creates the path to yield superior growth and profitability in the future. Blue ocean focuses on venturing into the untapped market place by means of Value Innovation which forms the corner stone of this strategy. According to (Kim Mauborgne 2005) although the term seems to be newer, yet the blue oceans have always existed in the past as well. If we look back like 100 years from now, we’d realize that the industries which are quite common in the present times were totally nonexistent for e. g. Internet industry, the automobiles industry, the telecommunications, the biotechnology industry, pharmaceuticals, fast food chains etc. So this means that every industry is borne with an idea of introducing something new for the people and thus demand is created with the advent of such industries. At the same time we dont know how things are going to be in another 50 years. According to (Kim Mauborgne 2005) we might get to see certain new industries which are not even thought of at present times. It is likely that blue oceans are going to serve as the growth engines. The red oceans are decreasing because the technological innovations are progressing in leaps and bounds. No industry wishes to be a bystander instead it works on its products and thus seeks to accomplish value innovation. (Kim Mauborgne 2005) lay down that the incumbents can create blue oceans within their core businesses for e. g. In the movie theatre industry, AMC theatre have a reputed name. They began as multiplexes in 1960s and later evolved into megaplexes in 1995. Thus they strived into a new venture because they had core competencies to do so. In stark contrast to what Porter emphasized, the proponents of this strategy lay down that the industry is not the unit of analysis, but it is the strategic move which holds more significance. The following are some of the features that differentiate Red Ocean and blue ocean (Kim Mauborgne 2005) Thus Blue Ocean strives to create untapped market place. The competition is not a defining characteristic and most importantly the focus is to provide the low cost and differentiation simultaneously unlike those in competitive strategy which stresses upon either low cost or differentiation. For e. g. Cirque de soleil successfully entered a totally unattractive industry because it restructured the industry through value innovation, created a new market place and eventually turned out to be a winner. This is what the core essence of Value innovation is. The intent is to create a leap in value for both customers as well as the company (Kim Mauborgne 2005) The companies that create blue oceans set up huge barriers for about 10-15 years which are very difficult to be broken down by other companies and generate economies of scale very rapidly thus jeopardizing the success of their rivals in the industry. A significant example of this is seven eleven convenience stores in Japan mainly which enjoy huge economies of scale, making it impossible for imitators to track down their path. Ikea used value innovation as it co-opted the customer into value chain in the final assembly and delivery stages which enabled it to emerge as a major international brand. Then although a late entrant into the highly competitive computer market, Dell tapped into an enormous reservoir of trapped value with its innovative direct model and left other established players way behind it. Leavy Carry, 2002). Nintendo Wii games were brand new products that didn’t care about the already existent market players like PlayStation by Sony and emerged as the most successful one. In Pakistan very few companies have been able to create new markets. The most important of all of them is Trakkar private limited which introduced a simple device that allowed the customers to track their own vehicle in their bid to prevent against auto theft. No such product ever existed in the market before so it achieved unhampered growth. (Aleem Bawany, 2011). In the termination, I would like to say that the Blue Ocean and Red Ocean have always co-existed together. In the present times the companies cant escape the so called notion of competition. But they need to broaden their horizons by thinking beyond their defined market boundaries i. e. there is a dire need to incorporate the blue ocean strategy. In other words the current time calls for maintaining a balance between the two scales with competitive strategy on one side and value innovation on the other side of the scale.