Information Flow and its Effects on Stock Prices-Evidence from S&P BSE Healthcare

 

Dr. M. Babu

Assistant Professor, Bharathidasan School of Management, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India.

*Corresponding Author Email: drbabu@bdu.ac.in

 

ABSTRACT:

The present study is an attempt to evaluate the share price behaviour of sample companies listed in SandP BSE Health care. In the literature of Economics and Finance, market efficiency has been a long debate since thirty years back. Indian Healthcare sector is growing at a rapid pace with foreign investments at a high level. The Research and Development in Indian Pharmaceutical sector has brought out with much technological advancement in the treatment of patients. The combined growth of Rand D and Foreign Investments has made the shares of Indian Healthcare sector to be significantly volatile. In this connection, the study evaluated the dependency of share prices of sample healthcare companies listed in SandP BSE Healthcare over the period 01st April 2007 to 31st March 2013. Using various statistical and econometric methods namely Runs Test, Autocorrelation test, the study found that historical share prices of sample companies had not effects in determining the future share price movements.

 

KEYWORDS: SandP BSE Healthcare, Volatility, Market Efficiency, Research and Development, Runs Test, Autocorrelation.

 


INTRODUCTION:

Healthcare has become one of the India’s largest sectors -both in terms of revenue and employment. Healthcare comprises hospitals, medical devices, clinical trials, outsourcing, telemedicine, medical tourism, health insurance and medical equipment. The Indian healthcare sector is growing at a brisk pace due to its strengthening coverage, services and increasing expenditure by public as well private players.

 

The industry is growing at a tremendous pace owing to its strengthening coverage, services and increasing expenditure by public as well private players. During 2008-20, the market is expected to record a CAGR of 16.5 per cent.

 

The Government is emphasising on the eHealth initiatives such as Mother and Child Tracking System (MCTS) and Facilitation Centre (MCTFC). Indian companies are entering into merger and acquisitions with domestic and foreign companies to drive growth and gain new markets.

 

Deloitte Touche Tohmatsu India has predicted that with increased digital adoption, the Indian healthcare market, which is worth around US$ 100 billion, will likely grow at a CAGR of 23 per cent to US$ 280 billion by 2020. The healthcare market can increase three fold to US$ 372 billion by 2022.

 

India is experiencing 22-25 per cent growth in medical tourism and the industry is expected to double its size (April 2017) US$ 3 billion to US$ 6 billion by 2018. There is a significant scope for enhancing healthcare services considering that healthcare spending as a percentage of Gross Domestic Product (GDP) is rising. Rural India, which accounts for over 70 per cent of the population, is set to emerge as a potential demand source. A total of 3,598 hospitals and 25,723 dispensaries across the country offer AYUSH (Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homoeopathy) treatment, thus ensuring availability of alternative medicine and treatment to the people.

 

Efficiency of capital market is judged by its success in incorporating and inducting information, generally about the basic value of securities, into the price of securities. This fundamental value of securities is the present value of the cash flows expected in the future by the person owning the securities.

 

SandP BSE HealthCare tracks the performance of leading healthcare sectors stocks which are listed in the Bombay Stock Exchange. The base period for SandP BSE HealthCare was from 1st February, 1999 and the base index value is 1000 points. SandP BSE HealthCare Index was launched on 9th August, 1999. During the initial days, the index was based on full market capitalization method and with effect from 23rd August, 2004, the index calculation methodology was shifted to free-float market capitalization.

 

The fluctuation in the value of stocks encourages traders to trade in a competitive manner with the objective of maximum profit. This results in price movements towards the current value of the cash flows in the future. The information is very easily available at cheap rates because of the presence of organized markets and various advanced technological innovations. An efficient capital market reflects information quickly and accurately in the prices of securities.

 

REVIEW OF LITERATURE:

Fatih Konak and Yasin Seker (2014), in the article on, “The Efficiency of developed markets: Empirical evidence from FTSE 100”, analyzed the weak form efficiency of Financial Times Stock Exchange 100 (FTSE 100) for the period from January 2001 to November 2009. The presence of unit root was examined using Augmented Dickey Fuller and Phillips Perron Test. GARCH (1,1) was used to examine the market efficiency. The results supported weak form market efficiency of FTSE 100.

 

Mohammad Shafi (2014) in the article entitled, “Testing the Market Efficiency in the Weak form taking CNX Nifty as a Benchmark Index: A study”, made an attempt to examine the weak form efficiency in Indian Capital Market using the daily return of Nifty stocks. The tools used for analysis were Runs test and Autocorrelation test. The results evidenced that Indian Capital Markets were inefficient in the weak form.

 

 

M. Babu and S. Srinivasan (2014), in the article entitled, “Testing the Co-Integration in Indian Commodities Markets: A Study with reference to Multi Commodity Exchange India Ltd” evaluated the spot and futures price relationship of ten sample commodities listed in Multi Commodity Exchange of India Ltd. Over the study period of one year from January to December 2012, using Johansen Trace Statistic and Max-Eigen Statistic, it was found that the current spot prices had no relevance in determining the future spot prices.

 

“Testing the Weak-form Efficiency of the Finnish and Swedish stock markets”, an article by Abu Towhid Muhammad Shaker (2013), examined the weak form EMH of the Finnish and Swedish stock markets, using Serial Correlation, Augmented Dickey Fuller Test and Variance ratio test. It was concluded that sample stock indices did not follow random walk during the study period.

 

“Stock Market Efficiency and Crisis: Evidence from India”, a paper by Kinjal Jethwani and Sarla Achuthan (2013), tested the weak form efficiency of SandP CNX Nifty from 1st January 1996 to 31st December 2012, using Autocorrelation, Variance ratio test, Kolmogrov-Smirnov and Runs Test. The results evidenced that Indian Stock Market was not weak form efficient in all periods.

 

In the paper entitled, “Testing the Weak Form Efficiency in Indian Commodities Market”, M. Babu and S.Srinivasan (2012), analyzed the efficiency of daily spot and future prices of sample commodities traded at Multi Commodity Exchange of India Limited over the period 01st April 2008 to 31st March 2011. Using Runs Test and Autocorrelation, it was concluded that majority of sample commodities did not provide evidence to support weak form market efficiency.

 

Tariq Zafar S.M (2012) in his paper entitled, "A systematic study to test the EMH on BSE Listed Companies before Recession" analyzed the Bombay Stock Exchange Efficiency during the pre recession period from 4th January 2008 to 24th December 2008.The results evidenced that market was efficient in the weak form.

 

An article entitled, "Does BSE Random Walk Randomly? An Innovative Investment Approach”, by Totala N.K et al (2012), examined the weak form efficiency for BSE Bankex companies, by using Unit root test, Runs Test and Autocorrelation. The daily prices of the scripts and value of Bankex for a period of 1st April 2006 to 31st March 2011 were collected from BSE we0bsite. All the fourteen banking companies listed on the Index, were selected as the sample. The results of the study suggested that the share prices of Bankex companies in BSE were located between inefficiency and weak form of market efficiency.

 

There are many studies aimed at testing the price dependency of markets. The results of some of the major studies are highlighted in the above paragraph. It is to be noted that all the earlier studies either at national or international level provided different views on market efficiency. There are similar views of the market by some authors whereas other authors provided contradictory view. This evidences that market efficiency needs to be reviewed and analyzed from time-to-time based on the information flow which has its effects on the markets. Further, it is also to be noted that to the knowledge of the author there were no studies concerning the market efficiency of sample companies listed in SandP BSE Healthcare. Hence, the present study attempts to fill the gap by providing a gist of dependency of price movements of health care companies traded at BSE which can help investors to understand the dynamics of market movements with respect to health care companies to diversify their portfolio in health care stocks. The results of the present study would contribute to the piece of knowledge which can add upon the literature.

 

RESEARCH QUESTIONS:

The present attempts to provide answers to the following research questions

·       Whether spot prices of sample companies could be used as an indicator to determine future prices?

·       Whether future prices follow spot prices or vice versa?

·       What is the degree of market efficiency of sample companies?

 

NEED FOR THE STUDY:

The study would be useful for the investors and technical analysts to make investment decisions by understanding the market conditions relating to the performance of Healthcare companies listed in SandP BSE Healthcare Sectors. The study would provide an understanding of the market efficiency of the Indian Healthcare Market. It would also provide ample data for benchmarking the SandP BSE Healthcare Index. It is to be noted that the projected CAGR of Indian Healthcare sector was 16.5% over the period 2008-2020. The initiative by the Government of India in the budget allocation to healthcare sector has kindled positive growth of Indian Healthcare sector which could help in getting more funds inflow by the investors of health care. Therefore, a study on market efficiency of health care stocks would provide an instrument for the investors to understand the movements of share prices of health care companies listed in BSE.

 

 

OBJECTIVES OF THE STUDY:

1.     To assess the efficiency of sample companies listed in S and P BSE Healthcare.

2.     To analyze the randomness in the movements of daily share price returns of selected companies listed in SandP BSE Healthcare.

 

Null Hypotheses of the Study:

NH01: The daily share price returns of sample companies are non-stationarity.

NH02: The daily share price returns of sample companies are not efficient in weak form.

NH03: The share price movements of the sample companies are not random.

 

METHODOLOGY OF THE STUDY:

a)       Coverage:

The present study made an attempt to test the efficiency of the Indian Capital Market with respect to sample companies listed in Healthcare sector of the Bombay Stock Exchange during the period from 01.04.2007 to 31.03.2013.

 

b)       Sample Selection:

Selected sample companies listed in SandP BSE Healthcare during the study period were selected on the basis of following criteria:

1.        Based on the total market capitalization of the sample companies as on 8th October 2013.

2.        Availability of daily market prices was also considered for considering it as the sample.

 

Table 1-Details of Sample Companies selected from SandP BSE HEALTHCARE

S.NO

NAME OF THE COMPANY

MARKET CAPITALIZATION

[As on 8th Oct.2013] (Rs. in Crores)

1.

Sun Pharmaceuticals Industries Ltd

 

1,27,030.99

2.

Dr.Reddy's Laboratories Ltd

40,706.49

3.

Lupin Ltd

39,863.02

4.

Cipla Ltd

34,931.09

5.

Glaxo Smithkline Pharmaceuticals

 

20,962.73

Source: Retrieved from http://www.bseindia.com/indices/IndexArchiveData.aspx?expandable=1

c)        Data Collection:

The information relating to share price of sample companies, volume of indices for Healthcare were obtained from bseindia.com. The other relevant information regarding the efficiency of the Indian Capital Market were extracted from various publications, PROWESS Corporate Database and BSE website.

 

 


 

d)       Statistic/Econometric Methodology of the study:

Table 2 Statistic/Econometric Tools used in the study

S.No

Statistical/

Econometric Tools

Formula

Relevance to the study

1

Daily Logarithmic Returns

Where,Ri,t = Returns on security i on time t

                Pt = Price of the security at time t

                Pt-1 = Price at time t -1

To convert the raw data into logarithmic returns to arrive at reliable results

 

 

 

 

 

 

2

Descriptive Statistics

Mean

= Where,

= represents the mean.

=Symbol of Summation

xi =Value of the ith item x, i= 1, 2, 3 ….n

n=total number of items.

 

To arrive at single numerical value that represents the entire data set.

Standard Deviation

Where,

standard deviation

X=random variable

µ=mean value

 

To measure the variation in the data set between the periods.

Skewness

Where, µÎ is the Îth central movement

 

To identify the degree of symmetry or asymmetry of the data distribution.

Kurtosis

Where, µÎ denotes the Îth central moment (and in particular, µ2 is the variance).

 

To identify the peakedness of the data distribution. To know how far the data is deviated from normal distribution.

 

 

 

3

 

 

Augmented Dickey Fuller Test

∆yt =α +βt+γyt-1+δ∆y-1+…+δρ∆yt-t

Where, α=Constant,

β = The coefficient on a time trend, and

p = The lag order of the autoregressive process.

To test the Stationarity of the time series data.

Stationarity=

Mean=Variance=Co-Variance.

 

4

 

Runs Test

To assess the increase or decrease or no change in prices.

 

 

5

 

 

Autocorrelation

Where,

 The sample autocorrelation function for the lag K.

 The returns on the day.

 The mean returns.

T The total number of observation.

 Variance of the returns series.

 

Used for measuring the dependence of successive terms in a given time series.

 

 

 

 

 

RESULTS AND DISCUSSIONS:

Table-3 Summary Results of Descriptive Statistics for the daily share price returns of Sample Companies listed in SandP BSE HealthCare from 01.04.2007 to 31.3.2013

Period/Name of the Company

Statistic

Dr. Reddy’s Laboratories

Cipla

GSK

Lupin

Sun Pharma

01.04.2007

to 31.03.2008

Mean

-8.282

-2.791

-2.641

-8.126

0.00061

Std.Deviation

0.0182

0.0232

0.0216

0.0211

0.0235

Minimum

-8.042

-1.540

-8.277

-7.126

-1.187

Maximum

6.517

6.989

6.273

6.281

8.264

01.04.2008

to 31.03.2009

Mean

-7.822

-7.615

0.0001

0.0013

-4.184

Std.Deviation

0.0279

0.0236

0.0159

0.0284

0.0257

Minimum

-1.378

-1.241

-5.964

-1.511

-8.592

Maximum

8.704

8.884

6.155

1.021

9.728

01.04.2009

to 31.03.2010

Mean

0.00393

0.0017

0.0201

0.0035

0.0019

Std.Deviation

0.02116

0.0217

0.0150

0.0226

0.0217

Minimum

-6.770

-9.821

-1.108

-6.49

-1.297

Maximum

9.981

8.753

6.562

1.026

7.538

01.04.2010

to 31.03.2011

Mean

0.00098

-1.920

0.0006

-5.369

-5.507

Std.Deviation

0.0150

0.0151

0.0132

0.1027

0.102

Minimum

-4.793

-6.637

-4.846

-1.612

-1.605

Maximum

5.379

6.108

5.347

6.323

5.242

01.04.2011

to 31.03.2012

Mean

0.000284

-2.118

0.0003

0.0009

0.00101

Std.Deviation

0.0139

0.0145

0.0115

0.0158

0.0158

Minimum

-5.204

-6.484

-4.287

-4.115

-7.355

Maximum

4.796

6.304

3.746

5.157

5.0295

01.04.2012

to 31.03.2013

Mean

0.00014

0.0009

-1.272

0.0007

0.00142

Std.Deviation

0.01154

0.0137

0.009

0.0132

0.0119

Minimum

-4.390

-3.933

-3.840

-4.133

-3.949

Maximum

3.285

4.307

3.670

4.264

3.978

01.04.2007

to 31.03.2013

Mean

0.000617

0.00032

0.0004

0.00002

-1.732

Std.Deviation

0.0187

0.019

0.0150

0.046

0.046

Minimum

-0.1378

-1.540

-1.108

-1.612

-1.605

Maximum

0.0998

8.884

6.562

1.026

9.728

Source: Collected from www.bseindia.com and Computed using SPSS 20.0

 


e)        Limitations of the study:

1.     The study is based on secondary data and hence it is riddled with certain limitations which are bound to be connected with the secondary data.

2.     All the limitations associated with various tools like Augmented Dickey Fuller test, Runs Test, Auto Correlation (ACF) are applicable to this study also.

3.     The study period is restricted to six years from 01.04.2007 to 31.03.2013 only and hence the results are applicable from 2007 to 2013.

4.     The results are based on the data published in the Bombay Stock Exchange of India website.

5.     The recommendations provided in the study are based on the results and it is the opinion of the researcher.

6.     The findings are confined only to the sample companies during the period of the study and it cannot be generalized.

 

The summary statistics results of daily share price returns of five selected sample Healthcare Companies, under SandP BSE Healthcare, during the study period are given in the Table 3. During the first phase of the study period (ie) from 01.04.2007 to 31.3.2008, all the selected sample companies witnessed negative average returns except Sun Pharmaceuticals. This implies that the investors earned losses during the period. The standard deviations of all the sample companies were same i.e the volatility remained constant during the period for all sample companies. GlaxoSmithKline Pharmaceuticals and Lupin Ltd were recorded positive returns for the investors during 2008-09. Glaxo Smith Kline Pharmaceuticals was the only company which recorded a lower standard deviation of 0.015. All the other sample companies earned stable returns during the period as their standard deviation was the same. During the financial year 2009-10, Glaxo Smith Kline Pharmaceuticals earned the highest mean returns with corresponding standard deviation of 0.015, thereby offering a favorable position for the investors among all the other sample companies. Cipla, Lupin and Sun Pharmaceuticals earned negative average returns during the period 2010-11. This may be due to the impact of global slowdown during the year. The standard deviation, which measures the volatility, was the same for Cipla, Dr. Reddy's Laboratories (0.015) whereas Lupin and Sun Pharmaceuticals recorded a standard deviation of 0.10 which indicates that the former companies provided better returns to the investors than latter companies during the period. During 2012-13, GlaxoSmithKline recorded negative mean returns whereas Sun Pharmaceuticals realized the highest average returns for the investors.

 

From the overall analysis, it can be concluded that during the whole study period, Dr. Reddy's Laboratories offered the maximum returns to investors followed by GlaxoSmithKline, Cipla Ltd and Lupin. Investors of Sun Pharmaceuticals suffered a major downtrend during the study period as its mean returns were negative, with a standard deviation of 0.046.


 

Table 4 Summary of Augmented Dickey Fuller Test Statistic for the Daily Share Price Returns of sample companies listed in SandP BSE HEALTHCARE during the study period

 

 

ADF t-Statistics

Test Critical Values

 

S.No

Company

Level difference

Significance

First difference

Significance

Second Level Difference

1%

5%

10%

Prob.

1

Dr.Reddy’s Lab.

-39.775

-19.633

-18.911

-3.4346

-2.8633

-2.5677

<0.001

2

Cipla

-39.711

-18.573

-17.668

-3.4346

-2.8633

-2.5677

<0.001

3

Glaxosmithkline

-37.527

-17.120

-18.644

-3.4346

-2.8633

-2.5677

<0.001

4

Lupin

-37.886

-20.151

-17.517

-3.4346

-2.8633

-2.5677

<0.001

5

Sun Pharma

-38.290

-18.505

-17.534

-3.4346

-2.8633

-2.5677

<0.001

Source: Data collected from bseindia.com and computed using SPSS

 

Table 5 Summary of Results of Runs Test (Median Base) for SandP BSE Healthcare during the study period ('Z' Statistic)

Name of the

PERIOD

Sample Companies

 

01.04.2007

to

01.04.2008

to

01.04.2009

to

01.04.2010

to

01.04.2011

to

01.04.2012

to

01.04.2007

to

 

31.03.2008

31.03.2009

31.03.2010

31.03.2011

31.03.2012

31.03.2013

31.03.2013

Cipla

-0.316

0.965

1.796

0.000

2.477

2.915

2.979

Dr.Reddy's Laboratories

0.949

0.065

0.642

0.503

0.572

1.521

1.218

GSK

Pharma

0.696

-1.221

-0.898

-0.377

-0.444

0.760

-0.440

Lupin Ltd

-2.593

-0.321

1.155

0.377

-0.825

0.887

-0.648

Sun Pharma

0.063

0.450

0.385

-0.251

0.318

0.253

1.062

Source-Collected from bseindia.com and computed using SPSS 20.0

 


Table 4 illustrates the stationarity results using Augmented Dickey Fuller Statistic for the daily share price returns of sample companies listed in SandP BSE Healthcare during the study period from 01.04.2007 to 31.03.2013. It is proved from ADF test that the daily share price returns of all the selected sample companies attained stationary at level, first level difference and also in second level difference. This is evident from the ADF t-statistic values of Dr. Reddy’s Laboratories (-39.775), Cipla (-39.711), Glaxosmithkline (-37.527), Lupin (-37.886) and Sun Pharma (-38.290) at level difference which is lesser than the test critical values at 1%, 5% and 10% level. Further, the prob.value was less than 0.05 indicating the results to be statistically significant. To confirm the results arrived at level difference, the first level and second level difference was also tested which yielded the same results. Therefore, it becomes evident that the null hypothesis NH01 namely, “The daily share price returns of sample companies are non-stationarity” is rejected.

 

The summary results of Median Base Runs Test results for SandP BSE Healthcare companies during the study period are presented in the above Table 5. The results of Cipla Ltd indicate that during 2008-09 and 2009-10, the test statistic value was within the range of test critical value of±1.96 and therefore the NH02 is accepted. But the overall analysis shows that the NH02 could be rejected. This is an indication that the spot and futures were linked to each other. The overall study period analysis of Dr. Reddy's Laboratories shows that the statistical value was 1.218 which falls within the critical value range of±1.96, which is an indication to accept the NH02. In other words, the share price of Dr. Reddy’s Laboratories was efficient in weak form. During the financial year 2008-09 and 2009-10, the share prices of GlaxoSmithKline were not efficient which means that the prices were not dependent on each other. The share prices of Lupin Ltd indicates that during 2007-08, 2008-09 and 2010-11, it was efficient which clearly shows that the succeeding price changes were independent. The sub-period analysis of Sun Pharmaceuticals indicates rejection of NH02 for all the sub periods whereas the overall analysis evidenced acceptance of NH02. In short, the market was weak form efficient.

 

The overall study period analysis of SandP BSE Healthcare indicates for all the five sample companies, namely Dr. Reddy's Laboratories, Cipla, GlaxoSmithKline, Lupin Ltd and Sun Pharmaceuticals, the null hypothesis NH02, ‘The daily share price returns of sample companies are not efficient in weak form’ is rejected. In other words, the past prices had no influence on the current prices for the above sample companies. Hence it is evident that the investors earned abnormal returns during the study period and it was not possible for the investors to predict future price movements by examining the past prices.

 

 

 

Table 6 Summary Results of Autocorrelation function of sample companies during the study period

Lag

Autocorrelation Values

 

Dr.Reddy’s Laboratories

Cipla

GSK

Lupin

Sun Pharma

1

-.031*

-.027*

.027**

.018**

.007**

2

-.006*

-.010*

.024**

.011**

-.017*

3

-.017*

-.051*

.014**

-.016*

-.009*

4

.029**

.008**

-.046*

-.017*

.013**

5

-.035*

-.047*

.006**

-.019*

-.007*

6

-.013*

-.073*

-.035*

-.010*

.007**

7

.023**

.010**

-.006*

-.005*

-.007*

8

-.005*

-.007*

-.062*

-.012*

-.008*

9

-.055*

-.012*

-.037*

.008**

.000**

10

.056**

.017**

-.038*

-.012*

.013**

11

.055**

-.002*

-.008*

.010**

-.002*

12

.055**

.008**

.022**

.019**

-.012*

13

.036**

-.015*

.007**

.025**

-.006*

14

.031**

.035**

.006**

-.029*

.011**

15

.041**

.004**

-.013*

-.012*

-.020*

16

-.054*

-.009*

.064**

.014**

.005**

17

.033**

.057**

.010**

.007**

-.001*

18

-.027*

-.004*

.015**

-.017*

-.009*

19

.024**

.030**

.035**

-.001*

-.030*

20

.019**

-.012*

-.014*

.002**

-.017*

21

.034**

-.016*

.034**

.019**

.003**

22

-.062*

-.008*

-.011*

.012**

-.006*

23

-.032*

-.040*

-.051*

.014**

.000**

24

.039**

.023**

-.082*

-.029*

-.019*

Source: Collected from bseindia.com, computed using SPSS.

**Positive significance and *Negative significance at 5% level

Table 6 displays the results of autocorrelation function for the daily share price returns of sample companies listed in SandP BSE Healthcare during the study period. It is to be noted that Dr.Reddy's Laboratories the lag began with negative significance and subsequently turned positive in lag 4. There was a downward trend in the next few lags. Lags 11 to 15 recorded positive observations. The next two lags recorded negative values and the subsequent lag turned positive. The results of autocorrelation function for Cipla Ltd during the study period indicated that there was negative significance till lag 3. The next lag recorded positive value and the subsequent two lags turned negative. The last lag ended with positive significance. It can be observed that there were no stable movements in the share price of Cipla Ltd during the whole study period. The results of autocorrelation function for daily share price returns of GlaxoSmithKline for a lag period of 24 from 01.04.2007 to 31.03.2013, it can be observed that the autocorrelation values were positively significant for the first three lags and the next lag turned negative. The subsequent lag was positive. As per the results in the Table there was no correlation between past prices and current prices and the prices were volatile during the study period. With respect to Sun Pharma results, 12 positive returns and 12 negative returns for different lags at 5% significance level. It started positive for the first two lags (0.018) and (0.011). Again Lag 11 and 13 recorded positive significance. The subsequent two lags turned negative and the next lag recorded positive value. Lags 20 to 23 were positive and the last lag ended with negative significance. The results clearly indicate that the returns were equally shared as there were equal positive and negative signs. Hence the null hypothesis namely NH03: “The daily share price movements of the sample companies are not random” is rejected.

 

CONCLUSION AND RESEARCH IMPLICATIONS:

The stock market is always subjected to volatility. The information with respect to securities arrives the market in a random manner and information of one event is independent of another event. Once the information is received, the investors try to safeguard their investments by immediately taking buy/sell positions. Hence the present study made an attempt to evaluate the reaction in the share price movements of sample healthcare companies listed in Bombay Stock Exchange of India Limited using statistical methods namely Runs Test and Autocorrelation test. It is to be noted that there was no stable pattern in the movement of prices for all the sample companies during the study period. Hence from the overall analysis it is concluded that the prices were not dependent on each other and past prices had no role in determining the current prices.

 

REFERENCES:

1          Abu Towhid Muhammad Shaker (2013) “Testing the Weak-form Efficiency of the Finnish and Swedish stock markets”. European Journal of Business and Social Sciences. Vol. 2, No.9, pp. 176-185.

2          Babu. M and Srinivasan.S (2012). “Testing the Weak Form Efficiency in Indian Commodities Markets”. SMART Journal of Business Management Studies, Vol 8, No 1, January-June-2012, pp-75-86.

3          Babu. M and Srinivasan. S (2014). "Testing the Co-Integration in Indian Commodities Markets: A study with reference to Multi Commodity Exchange India Ltd". Indian Journal of Finance, ISSN 0973-8711. Vol. 8, No.3, March 2014, pp. 35-43

4          D. A. Dickey and W. F. Fuller (1979). “Distribution of the Estimators for Autoregressive Time Series with a Unit Root”. Journal of the American Statistical Association, Vol. 74, No. 366, pp. 427-431.

5          Eugene.F.Fama (1970). “Efficient Capital Markets: A Review of Theory and Empirical Work”. Journal of Finance, Vol. 25, No.2, pp. 383-417.

6          Fatih Konak and Yasin Seker (2014), “The Efficiency of developed markets: Empirical evidence from FTSE 100”. Journal of Advanced Management Science. Vol.2, No.1, pp. 29-32.

7          Kinjal Jethwani and Sarla Achuthan (2013). “Stock Market Efficiency and Crisis: Evidence from India”. Asia Pacific Finance and Accounting Review. Vol.1, No.2, pp.35-43.

8          Mohammad Shafi (2014). “Testing the Market Efficiency in the Weak form taking CNX Nifty as a Benchmark Index: A study. Research Journalis Journal of Finance, Vol. 2, No.2, pp. 1-20

9          Tariq Zafar S.M (2012). “A systematic study to test the EMH on BSE Listed Companies before Recession”. International Journal of Management and Social Sciences Research. Vol. 1, No.1, October 2012.

10       Totala N.K et al (2012). “Does BSE Random Walk randomly?” Pacific Business Review International. Vol.5, Issue 2, pp.11-22.

11       Text Books

12       Chris Brooks. (2008). Introductory Econometrics for Finance, (2nd Edition), Cambridge University Press, The ICMA Centre, University of Reading, London.

13       Roman Kozhan. (2010). Financial Econometrics with E-Views. Ventus Publishing Aps, Denmark.

14       Donald. E. Fisher and Donald. J. Jordan (2001). Security Analysis and Portfolio Management, Prentice-Hall of India, New Delhi.

 

 

 

 

 

Received on 07.02.2018          Modified on 19.03.2018

Accepted on 02.04.2018      ©AandV Publications All right reserved

Res.  J. Humanities and Social Sciences. 2018; 9(2): 454-460.

DOI: 10.5958/2321-5828.2018.00077.3