A Study on Analysts’ Recommendations and Stock Price ...irjbm.org/irjbm2013/March2014/Paper2.pdf4 Koutons Retails(India) 1 - 1 - 1 5 Simplex Infrastructures 1 1 - - 1 6 Allcargo

International Research Journal of Business and Management – IRJBM ISSN 2322-083X

IRJBM – (www.irjbm.org ) March - 2014 - Volume No – III

© Global Wisdom Research Publications – All Rights Reserved. 11

A Study on Analysts’ Recommendations and Stock Price Performance:

An Empirical Study

Mrs.L.Leela

Research Scholar, Bharathiar School of Management and Entrepreneur Development,

Bharathiar University, Coimbatore, Tamil Nadu, South India

Dr.R.Shanmugham Associate Professor, Bharathiar School of Management and Entrepreneur Development,

Bharathiar University, Coimbatore, Tamil Nadu, South India

ABSTRACT

This paper examines the impact of the investment advice of leading “The Hindu Business

Line – Investment World” and to identify the relationship between “The Hindu Business Line

– Investment World and Stock Price drift. The result of the study indicates that the analyst

recommendations do have impact and is beneficial to the investors at least in short-term

decisions. Many study also inferred that the volume of stocks traded has increased when

recommendations are announced but there is no significant relationship between

recommendation date and trading volume on the subsequent dates. Between the trading

volume and market adjusted return, there is a positive relationship between them.

KEYWORDS: Analysts’ Recommendation, Stock Price drift, t-test.

INTRODUCTION

It’s a general view that security prices reflect the performance of a company. Various factors

both economic and non-economic invariably affect stock return behavior. As Cootner (1964)

says, “the prices of securities are typically very sensitive, responsive to all events, both real

and imagined”. Recommendation of Analyst also play major role in equity market leading to

stock return fluctuations.

The strongest form of the Efficient Market Hypothesis (EMH) predicts that an analyst’s

recommendation would result in no adjustment at all. A weaker section would allow the

recommendation to carry information and predict that prices will adjust as soon as the

analyst’s clients have access to the information. Under this version, clients act as arbitrageurs,

purchasing undervalued stock in anticipation of abnormal returns. As long as a stock is

undervalued, clients continue to purchase, and ultimately the information contained in the

recommendation is completely reflected in the price.

During the recent decade, considerable evidence has been produced in support of the

hypothesis that stock prices reflect all publicly available information. The apparent difficulty

of “picking winners” has generated a certain skepticism about the economic value of

professional investment advice. In 1973 WOMACK, KENT L., concluded that “buy”

recommendations of stocks by security analysts at major U.S. brokerage firms showed

significant, systematic discrepancies between pre-recommendation prices and eventual

values. The initial return at the time of the recommendations is large, even though few

recommendations coincided with new public news or provided previously unavailable facts.

Similar conclusions were reached by Davies, Peter Lloyd and Michael Canes, (1978), James

H. Bjerring, Josef Lakonishok, and Theo Vermaelen, (1983), Werner F.M. De Bondt and




Richard Thaler, (1985), Roger Kormendi and Robert Lipe, (1987), Pu Liu, Stanley D. Smith,

and Azmat A.Syed, (1990), Messod D. Beneish (1991), Scott E. Stickel, (1995), Brad Barber,

Reuven Lehavy, Maureen Mc Nichols, And Brett Trueman, (2001), Alon brav and Reuven

lehavy, (2003), Michalis Glezakos and Anna Merika, (2007), Oral Erdogan, Dan Palmon and

Ari Yezegel and Turkey, (2007), Mark Bagnoli, Michael Clement, Michael Crawley, Susan

Watts, (2009). They provide evidence that brokerage houses and investment advisory

services do provide valuable investment advice to their customers. It is interesting that the

more recent studies which report positive abnormal performance are more careful in adjusting

for risk, and concentrate on returns achieved by customers of the brokerage house/investment

adviser, rather than by readers of a more widely disseminated publication.

The purpose of this paper is analyzing the impact of investment recommendations in the

financial press on the performance of stocks in the stock market, and to analyze the impact of

analysts’ recommendation on movement of stocks on the publication day, in pre-

recommendation and post recommendation period and also to study the behavior of trading

volume.

II. THE DATA, SAMPLE SELECTION CRITERIA, AND DESCRIPTIVE

STATISTICS

The recommendations of analysts were collected from “THE HINDU BUSINESSLINE -

Investment World” on Sundays (January 2009 and February 2009). The study is based on

the secondary data (Stock price and Index return) collected from PROWESS database of

Centre for Monitoring Indian Economy (CMIE). This study used only ‘Buy’ recommendation

for analysis. It is done only for 18 Stocks and for a period of 2 years only. And it did not

concentrate on name specific the individual analyst recommendations. Daily returns for

individual securities were collected for a period of two years from 1st July 2008 to 30

th June

2010. Daily sector wise Index Return were collected from CMIE Index, Bombay Stock

Exchange 500 Index, Nifty Midcap 50 for period of two years from 1st July 2008 to 30

th June

2010. Two years data has been used in the study for computation of pre-recommendation

returns.

Data for 24 companies was collected from PROWESS but the data of only 18 companies,

based on buy recommendation was selected for the analysis in the study. Data of 18

companies for 3 months was taken to analyze but only 21 days data were used in the study to

analyze the volume traded and market adjusted return. Table 1 provides descriptive statistics

for these recommendations.




TABLE 1

DESCRIPTIVE STATISTICS OF ANALYST RECOMMENDATION

(JULY2008-JUNE2010)

BUY HOLD

SELL

YEAR

No. of

Recom-

mendation

No. of

Companies

No. of

Analyst

Average

Rating N % N % N %

Jul’08 –

Dec’08 52 49 8 0.13 41 79 9

17 2 04

Jan’09-

Jun’09 98 52 11 0.17 82 84 16 16 3 03

Jul’09-

Dec’09 100 65 10 0.15 71 71 23 23 3 03

Jan’1-Jun’10 115 106 10 0.11 88 77 22 19 5 04

Overall Total 365 291 11 0.13 282 78 70.1 19 13 04

In this above table, out of 365 Recommendations during the period July 2008 to June 2010,

“Buy” recommendations are larger in number (282) and it constitutes 78 percent of the total.

“Sell” recommendations are very small in number (13) and constitutes only 4% of the total.

The recommendations from “Business Line” for four half-yearly period are furnished in the

table. Out of these four half yearly periods, the second half-yearly period i.e., from January

2009 - June 2009 contains a higher number of “buy” recommendations. This supported by the

average ratings shown in the table. The average rating in the second half yearly period is 0.17

and 0.15 in the third half yearly period. For this study, 18 “Buy” recommendations made

during the period January to February 2009 only are consider for analysis.

TABLE -2

SHIFT OF ANLYSTS’ RECOMMENDATION

FOR THE PERIOD OF JANUARY 2009 TO JUNE 2010

To Recommendation of:

From

Recommendation of:

1

BUY

2

HOLD

3

SELL Total Percent




1 BUY 71 13 8 92 34

2 HOLD 17 6 2 25 9

3 SELL 1 1 1 3 1

STABLE 119 25 6 150 56

TOTAL 208 45 17 270 _

PERCENT 77 17 6 _ 100

This table shows the shift of analyst’ recommendations from one category to the other. The

first row reports that the recommendation of 1 (Buy) to 1, 2(hold), 3 (Sell). The second row is

from ‘hold’ and the third is from ‘Sell’. The fourth row reports that there are certain

recommendations that are kept constant without any shift in recommendation which

categorized as ‘stable’. More specifically, in 78 cases the analysts repeated the same

recommendations and in 50 cases the analysts shift their recommendations from one category

to another. As per this report, even made changes in recommendations, the high percent (77)

is support the ‘buy’ recommendations.

TALBE – 3

DISTRIBUTION OF ANALYSTS’ RECOMMENDATIONS

(JANUARY 2009 AND FEBRUARY 2009)

S.

NO. Company Name

No. of

Recommendation

Per Company

No. of

Recommendation

per Type

No. of Analyst that

Recommended the

Stock

Buy Hold Sell

1. Tulip Telecommunication 2 2 - - 2

2. Rural Electrification

Corporation 2 2 - - 2

3 Nestle India 1 1 - - 1

4 Koutons Retails(India) 1 - 1 - 1

5 Simplex Infrastructures 1 1 - - 1

6 Allcargo Global Logistics 1 - 1 - 1

7 ACC 1 1 - - 1

8 Federal Bank 2 2 - - 1

9 Rallis India 1 1 - - 1




10 Vishal Retail 1 - - 1 1

11 Zee Entertainment

Enterprise 1 1 - - 1

12 Bank of India 1 1 - - 1

13 India Cements 1 - - 1 1

14 Crompton Greaves 2 2 - - 2

15 Mundra Port & SEZ 2 2 - - 1

16 DLF 1 - 1 - 1

17 Sanghvi Movers 1 1 - - 1

18 Madras Cements 1 - 1 - 1

19 IDFC 1 1 - - 1

20 CCCL 1 1 - - 1

21 Bartronics India 2 2 - - 2

22 Sesa Goa 2 2 - - 2

23 Reliance Communication 1 1 - - 1

24 Container Corporation 3 3 - - 2

TOTAL 33 27 5 1 30

As it appears from Table 3, the 33 recommendations refer to 24 firms, a number which is

companies listed for the recommendations of the sample period. Our sample, confirms what

is already known from the literature, that financial analysts are mainly interested in ‘buy’

recommendations because the eagerness of analysts to recommend positively becomes

apparent from Table 2, which presents the repetitions of the initial recommendation as well as

its variation. The analysts‟ recommendations in our sample came from “The Hindu Business

Line – Investment world” a weekly magazine. Out of these 24 companies, we only take 18

companies for analysis which is comes under ‘buy’ recommendations.

METHODOLOGY

We focused on the influence of analysts’ recommendations on stock returns and employed an

event study methodology.

The above strategies abide by usual practice. It has the significant advantages that does not

require very close monitoring or daily rebalancement and therefore avoids the huge costs

associated with it. We proceeded by constructing portfolios according to the three levels of

recommendations (buy, hold, sell) and we then measured the returns of these portfolios.

Specifically, to construct the portfolios the following steps were followed.




(i) We classified the 33 recommendations into the three categories as stated above.

(ii) The returns of the companies were measured for the following periods compared to the

day that securities were recommended.

For the next day (t+1)

For the previous day (t-1) and for the recommended day (t-0).

For the Short term period was next 3 month of the recommendations.

For the Long term period was next 6 month of the recommendations.

And also calculate Pre recommendation for previous 6 month from the recommendations

made.

For the purpose of analysis, returns were calculated both for individual stocks and indices.

The data have been processed through appropriate statistical technique such as t-test from

parametric test.

T-test

T-test is based on t-distribution and is used for judging the significance of several statistical

measures, particularly the mean or for judging the significance of difference between the

means if two samples in case of small samples when population variance is not known. In

case of two samples are related, we use paired t-test (or what is known as difference test) for

judging the significance of the mean of difference between the two related samples. It can

also be used for judging the significance of the coefficients of simple and partial correlations.

The relevant test statistic, t, is calculated from the sample data and then compared with its

probable value based on t-distribution (to be read from the table that gives probable values of

t for different levels of significance for different degrees of freedom) at a specified level of

significance for concerning degrees of freedom for accepting or rejecting the null hypothesis.

It may be noted that t-test applies only in case of small sample(s) when population variance is

unknown. Testing technique will differ in different situations.

This study has the following situation and hence the following method of t-test was used for

this study.

• Population normal, population infinite, sample size small and variance of the

population unknown, Ha may be one-sided or two-sided:

n

X

s

Ho

/σ

µ−

with d.f. = (n-1)

)1(

)( 2

−

−∑n

XX i

Where,

X = Mean of the sample




1X = Mean of the Sample one

n = No. of items in a sample

Standard deviation of population

Hypothesized mean for population

HYPOTHESIS

The following purposes of this study, the following hypothesis were framed:

1. There is no significant relation between analyst recommendations and the drift

of stocks in the Stock Market.

2. Analysts’ recommendation is not beneficial in the Long-term to the public at

large.

3. Analysts’ recommendation has no impact on the post-recommendation

movements.

4. Analysts’ recommendation has no impact on stock prices on the publication

day.

5. Analysts’ recommendation has no impact on the volume of stock traded.

III. ANALYSIS

III.A. BEHAVIOR OF STOCK’S ABNORMAL RETURN ((MONTHLY BASIS):

Summary statistical measures of stock return used in this study consist of mean,

standard deviation and t-test. Mean is a measure of average stock returns over a period of

time. Standard deviation is a measure of variation of stock returns. Regarding t-statistics, it is

a parametric test that used for judging the significance of sample mean or for judging the

significance of difference between the means of two samples in a case of small sample.

DETERMINATION OF STOCK RETURN PERFORMANCE OF BUY

RECOMMENDATION:

In order to determine the performance of stock return on month wise, with help of t-test for

Average Market Adjusted Return (AMAR) and Cumulative Average Market Adjusted Return

(CAMAR) are presented in the table 4.




TABLE – 4


RECOMMENDATION

(July 2008 - June 2010)

Period AMAR

(%)

Standard

Deviation of

AMAR

t-test CAMAR

(%)

S.D of

ACAR t-test

A.2008

July -8.43 9.19 -3.89 -8.43 9.19 -3.89

August -2.6 9.79 -1.127 -11.03 11.09 -4.216

September 11.41 10.40 4.655* 0.38 16.11 0.1

October 45.68 23.97 8.084* 46.06 32.12 6.084*

November 18.45 16.24 4.82* 64.51 45.47 6.019*

December -15.56 13.31 -4.958 48.95 44.62 4.655*

B. 2009

January 5.31 15.95 1.413 54.26 51.46 4.459*

February 5.86 7.19 3.455* 60.12 54.52 4.664*

March -2.93 8.64 -4.386 57.19 53.26 4.063*

April 17.59 9.64 -7.736 74.78 52.64 2.674*

May -39.51 19.91 -8.419 35.27 43.23 -0.597

June -8.39 8.82 -4.036 26.88 40.59 -1.513

July -4.77 10.28 -1.968 22.11 44.52 -1.834

August -3.08 8.28 -1.578 19.03 40.37 -2.346

September -6.39 11.14 -2.434 12.64 42.36 -2.826

October 2.82 16.52 0.725 15.46 46.71 -2.307

November -6.76 7.06 -4.061 8.70 50.17 -2.719

December -4.06 5.46 -3.158 4.64 50.42 -3.047

C.2010

January 0.08 6.61 0.052 4.72 49.48 -3.098




February -1.01 8.66 -0.493 3.71 53.38 -2.709

March -4.35 6.72 -2.746 -0.64 54.26 -3.005

April -2.75 6.96 -1.678 -3.39 55.55 -3.144

May 4.42 9.24 0.029 1.03 57.71 -2.701

June -5.3 9.35 -2.406 -4.27 54.82 -3.254

* Significance of 5%

Market adjusted return i.e., the difference between the index return and stock return.

This Return is also called the Abnormal Return. Market adjusted return is the excess return

arising from a stock. Table – 4 shows the percentage of Average Market Adjusted Return

(AMAR) and the percentage of Cumulative Average Market Adjusted Return (CAMAR) of

selected 18 stocks. Standard Deviation and t-test were applied on the percentage of AMAR

and CAMAR. By the result of t-test we can determine the performance of a stock

authentically. The t-test values of AMAR indicates that the recommendations published in

the “The Hindu Business Line - Investment World” on Sundays have a significant

relationship on stock prices for the month of September 2008 (t=4.655), October 2008

(t=8.084), November 2008 (t=4.82) and February 2009 (3.455). The t-test values of CAMAR

indicates that the recommendation published in the “The Hindu Business Line - Investment

World” on Sunday has a significant relationship on stock prices for the months of October

2008(6.084), November 2008(6.019), December 2008(4.655) and January 2009 (4.459),

February 2009 (4.664), March 2009 (4.063) and April 2009 (2.674).


RECOMMENDATION (PRE. AND POST RECOMMENDATION PERFORMANCE):

Analyzing the performance of stock return on pre-recommendation period and post

recommendation period, the Market Adjusted Return (MAR) playing a major role. It is

derived by subtracting stock return from index return. It classified according to the period.

The details are shown in the table 5.

TABLE – 5

MARKET ADJUSTED RETURN

(July 2008 - June 2010)

Index / Company Name

Pre-

Recommen

dation

Post- Recommendation

Jun'08-

Dec'08

April'

09-

June'

09

Apr'

09-

Sep'

09

Apr'

09-

Dec'

10

Apr'

09-

Mar'

10

Apr'

09-

Jun'

10

(6 Months) 3 6 9 12 15




Cmie

Index(Eq):Communi

cation Services

TULIP

-1.89 2.17 1.11 -0.03 -0.62 -0.95

B S E 500 Index RECLTD -5.76 -0.10 -1.58 -1.20 -0.16 -0.36

Cmie

Index(Eq):Food

Products NESTLE -1.86 1.86 1.61 0.54 -1.26 -2.46

Cmie

Index(Eq):Industrial

& Infrastructural

Construction

SIMPLEXI

NF -5.51 3.06 1.70 0.67 0.28 -0.89

Cmie

Index(Eq):Cement ACC -8.76 0.66 0.66 0.46 0.86 0.40

Cmie

Index(Eq):Financial

Services

FEDERAL

BNK -6.55 -0.85 -3.09 -4.63 -4.96 -6.04

Cmie

Index(Eq):Pesticides RALLIS -4.51 -2.39 -5.90

-

10.21

-

14.04

-

16.29

Cmie

Index(Eq):Recreatio

nal Services ZEEL -4.00 0.77 0.02 -0.92 -1.01 -2.00

Cmie

Index(Eq):Financial

Services

BANK

INDIA -10.59 0.95 0.99 2.24 3.90 3.63

B S E 500 Index

CROMP

GREAV -4.95 0.00 -1.29 -2.75 -4.12 -6.27

B S E 500 Index

MUNDRAP

ORT -8.42 0.53 -1.52 -3.22 -2.64 -3.14

Nifty Midcap 50

Index

SANGHVI

MOV -6.58 1.46 1.17 -0.26 0.28 1.17

B S E 500 Index IDFC -1.81 2.62 3.53 3.74 4.67 4.24

Cmie

Index(Eq):Industrial

& Infrastructural

Construction CCCL -6.09 4.00 4.85 4.26 4.12 4.43

B S E 500 Index

BARTRON

ICS -5.30 0.06 -1.93 -1.67 -1.10 -1.11




Cmie

Index(Eq):Minerals SESA GOA -6.43 0.70 -0.28 -0.24 -0.42 0.81

Cmie

Index(Eq):Communi

cation Services RCOM -3.99 1.95 2.74 4.45 7.65 10.88

B S E 500 Index CONCOR -4.18 0.20 -1.06 -2.36 -2.83 -3.79

95 % Significance

Level TOTAL -5.40 0.98 0.10 -0.62 -0.63 -0.99

MEAN -5.40 0.98 0.10 -0.62 -0.63 -0.99

S.D 2.38 1.50 2.53 3.48 4.63 5.60

t-test -9.64 2.78 0.16 -0.76 -0.58 -0.75

Table -5 has 10 types of Index. For making calculation of Market Adjusted Return, it

possesses an important place. Among the 10 Index, 8 Index from Sector wise Index. The

remaining 2 index from BSE 500 INDEX and NIFTY MIDCAP 50 INDEX. The BSE 500

INDEX used for 6 companies and NIFTY MIDCAP 50 INDEX for 1 company and Sector

wise Index were used for remaining companies. The t-test result of pre-recommendation

shows poor performance of the selected shares during the study period. The t-test result for

the 1st quarter of post recommendation period (April 2009 – June 2009) shows good

performance of shares during this period, but the overall cumulative quarter does not show

good performance (-0.75).

The cumulative result indicates that “The Hindu Business Line – Investment World”

recommendations can be used profitably for short term period because the t-statistic (2.78)

strongly favours positive relation with share movements in short term whereas the

relationship is not as significant in the long term (-0.75).

RELATIVE PERFORMANCE OF STOCK RETURN, INDEX RETURN AND

MARKET ADJUSTED RETURN:

Analyzing the performance of abnormal return of stocks, the comparison of the Stock Return,

Index return and Market Adjusted Return are presented in the table 4.2.9




TABLE – 6

Relative Performance of Stock Return, Index Return and Market Adjusted Return

(July 2008 - June 2010)

Pre-Recommendation Post Recommendation

Jun'08-

Dec'08

April'09-

June'09

Apr'09-

Sep'09

Apr'09-

Dec'10

Apr'09-

Mar'10

Apr'09-

Jun'10

Stock Return 3.92 1.99 3.95 4.93 5.04 5.68

Index Return -1.48 2.97 4.05 4.31 4.40 4.70

MAR -5.40 0.98 0.10 -0.62 -0.63 -0.99

FIGURE – 1

Table – 6 shows the comparison of Stock Return, Index Return and Market Adjusted Return,

during the pre recommendation and post recommendation period.

In the Figure – 1 three Curves are shown. Curve 1 indicates Stock Return, Curve 2 indicates

the Index Return and Curve 3 indicate the Market Adjusted Return. The chart clearly

compares the indications of the three types of return values.

Curve1 (Stock return curve) starts from the bottom and shows a steady increase

during the pre recommendation period. Thereafter the decline in the curve is not steady. It

shows only a marginal decrease.

Curve 2 (Index return curve) shows a steady increase during the pre

recommendation period and reach the peak in the pre recommendation period and shows a

steady increase till June 2010.




Curve 3 (MAR curve) again shows an initial during the pre recommendation period

and then it increase post recommendation period.

Hence one should not conclude based on the values of single return. Before

concluding one has to compare the values of all the three returns. From curve 3 we can see

that abnormal returns short term. Hence, it can be said following the short term

recommendation is beneficial for the news paper readers.

III.B. BEHAVIOR OF STOCK’S ABNORMAL RETURN (ON DAILY BASIS):

Analyzing the performance of recommendation in the publication day, immediate proceeding

and following days of 18 selected stocks, t-test play a major role. The t-statistics of Average

Daily Abnormal Return, Average Cumulative Abnormal Return are presented in the

following table 7.

TABLE – 7

Average Daily Abnormal Return, Average Cumulative Abnormal Return and the t-

statistics for the combined sample and the Buy recommendations surrounding the

Publication Day

Event Day AMAR S.D t-value CAMAR S.D t-value

-10 1.440 3.98 1.537 1.440 4.347 0.538

-9 -1.111 3.38 -1.395 0.329 4.594 0.305

-8 0.567 4.18 0.575 0.896 3.971 0.959

-7 -0.230 5.45 -0.179 0.666 6.251 0.453

-6 -0.254 5.75 -1.876 0.412 5.403 -1.472

-5 -1.000 3.83 -1.106 -0.588 6.362 -1.917

-4 0.691 5.39 0.543 0.103 9.164 -1.011

-3 -0.146 3.24 -0.190 -0.043 10.901 -0.907

-2 0.297 3.60 0.350 0.254 10.490 -0.822

-1 0.479 3.21 0.633 0.733 9.847 -0.669

0 1.077 6.63 0.689 1.810 10.522 0.180

1 0.159 5.17 -0.908 1.969 9.269 -0.131

2 0.100 2.19 -0.557 2.069 9.870 -0.080

3 0.530 2.70 -0.601 2.599 10.194 0.143

4 0.741 2.69 1.171 3.340 11.303 0.407




5 0.575 3.26 0.748 3.915 11.829 0.595

6 0.680 2.54 1.138 4.595 11.457 0.867

7 -0.470 2.47 -0.815 4.125 10.771 0.735

8 0.460 2.62 0.750 4.585 11.239 0.879

9 0.290 3.823 0.316 4.875 11.477 0.966

10 0.080 4.33 0.075 4.955 12.440 0.918

Table – 7 shows the percentage of Average Market Adjusted Return (AMAR) and the

percentage of Cumulative Average Market Adjusted Return (CAMAR) of the selected 18

stocks for 21event days. Standard Deviation (S.D) and t-test were applied on the percentage

of AMAR and CAMAR. Through t-test the performance of the stock can be determined

authentically. The t-test on the AMAR and CAMAR shows that “The Hindu Business Line”

has no immediate relationship with stock movements because when we compare the

calculated value with the Table value (2.110), the calculated value was low for the whole

event days.

FIGURE – 2

The Figure – 2 shows the day wise movement of MAR (%) for 21 Event days (pre

recommendation of 10 days (-10 to -1), day of the recommendation and post recommendation

of 10 days (+1 to +10). The Figure indicates highly fluctuating movements during the entire

21 event days. When closely observed, a positive performance can be seen in a day just

before recommendation day and an immediate fall after the recommendation day. The reason

can be attributed to the information provided by the brokerage house to their valuable

customers.




FIGURE – 3

The Figure – 3 shows the cumulative movement of Cumulative Average Return (CAR) for 21

event days (Pre Recommendation of 10 days (-10 to -1), day of the Recommendation and

Post Recommendation of 10 days (+1 to +10). The Pre Recommendation period is highly

fluctuating with frequents ups and downs. From the day of recommendation a study increase

with a few ups and downs can be seen. It indicates a favorable movement during the post

recommendation period.

III.C. BEHAVIOR OF TRADED VOLUME (ON DAILY BASIS):

Many recent studies have found that increased trading volume was associated with the release

of information. For example, Karpoff (1986)21

, developed a theoretical model to provide a

rationale for the use of trading volume in event studies that attempt to identify the

information content of an event. Jarrell and poulsen (1988)22

, found that trading volumes of

the targets of tender offers increased significantly around firm’s annual earnings

announcement of the bid. Asquith and Krasker (1985)23

, and Richardson, Sefeik, and

Thompson (1986) concluded that there was a significant increase in trading volume

surrounding the announcement of change in dividend policy. Lakonisok and Vermaelen

(1986)24

, examined trading volume around ex-dividend days and reported that trading volume

increased significantly around ex-dividend day.

The trading volume data were obtained from PROWESS data base. Day t=0 was used as the

base trading volume for each stock, and each day’s volume was expressed as a percentage of

day t=0 volume. The results are presented in following table.




TABLE – 8

THE AVERAGE RELATIVE VOLUME, THE STANDARD DEVIATION, AND T-

STATISTICS FOR SAMPLES OF 18 STOCKS FROM PRE-TEN DAYS TO POST-

TEN DAYS PERIOD

Event

Day

Daily

Volume

Average Relative

Volume

Standard

Deviation t-Statistic

-10 6.613 1.05 1.014 0.197

-9 3.694 1.00 0.880 -0.003

-8 6.414 1.04 1.010 0.161

-7 6.441 1.27 1.314 0.903

-6 6.677 1.41 1.714 -6.132

-5 6.625 3.53 8.060 1.370

-4 6.875 1.57 2.870 0.869

-3 6.828 1.99 4.866 0.888

-2 7.219 2.04 2.767 1.643

-1 7.248 1.21 0.934 0.960

0 6.698 1.00 0.000 0.000

1 6.978 1.17 0.926 0.797

2 6.172 19.31 75.406 1.058

3 6.821 1.27 1.273 0.935

4 6.778 2.25 4.322 1.258

5 6.402 3.46 9.510 1.127

6 6.213 0.87 0.676 -0.864

7 6.202 0.99 0.720 -0.048

8 6.627 1.04 0.799 0.207

9 6.529 1.38 2.060 5.008

10 6.308 3.44 6.070 1.753

• Each Stock's daily volume is divided by the stock's volume on day t=0.




• The average relative volume is the mean for all stocks on the respective date.

• The t-statistic is for a test for a difference between the day's average relative

volume and day t=0's volume.

The table – 8 shows the average relative volume of daily traded volume. From the

ARV it can be observed (shaded region) from the recommendation day, the Pre

Recommendation period has shown some increase in volume of traded , similarly the post

recommendation period also show increase in the volume of trade for a short span. But when

t-statistic is observed, we can see there is no significant relationship between

recommendation and ARV.

FIGURE – 4

The Figure - 4 shows the movement of average relative volume for 21 event days (pre

recommendation of 10 days (-10 to -1), day of the recommendation and post recommendation

of 10 days (+1 to +10)). From the curve it can be seen in the post recommendation period

there is a sharp increase and then it has steady increase with few occasional fluctuations in

the after recommendation period.

IV. INTERPRETATIONS

1. When analyzing the performance of each stock on monthly basis, most of the stocks

had good performance from September 2008 to December 2008 and January 2009 and

February 2009. As per these findings, we infer that the recommended stocks showed positive

abnormal return in pre-recommendation period and the post recommendation period showed

an improvement in return. It is possible to get the good performance in pre-recommendation

period because before recommendation is published, the brokerage house reveals the

expected movements of shares to selected customers.

2. The market price of shares was constant during January 2009 and February 2009,

following an immediate short term decline. Short term decline is followed by short term peak

in the month of March 2009 and April 2009. In an overall perspective from July 2008 to June

2010, we find that the market was volatite with sharp peaks and declines.




3. As for as the Average Market Adjusted Return (AMAR) and Cumulative Average

Market Adjusted Return (CAMAR), the t-test results indicates that the recommendation

published in the “The Hindu Business Line – Investment World” on Sundays have significant

relationship on stock prices for the month of September 2008(t=4.655), October 2008

(t=8.084), November 2008 (t=4.82) and February 2009 (3.455). The t-value of CAMAR

indicates that the recommendation published in “The Hindu Business Line – Investment

World” on Sunday has a significant relationship on stock prices for the months of October

2008 (96.084), November 2008 (6.019), December 2008 (4.655) and January 2009 (4.459),

February 2009 (4.664), March 2009 (4.063) and April 2009 (2.674).

4. When analyzing the t-test result of pre-recommendation and post recommendation

period, the result of the pre-recommendation period, shows poor performance. The t-test

result for the Ist

quarter of post recommendation period (April 2009 – June 2009) shows good

performance of shares, the overall cumulative return does not show good performance (-

0.75).

5. The cumulative result indicates that “The Hindu Business Line – Investment World”

Sunday recommendations can be used profitably for short term period because the t-statistics

(2.78) strongly favors positive relation with share movements in short term where as the

relationship is not significant in long-term(-0.75).

6. From the study it can be identified that analyst’ recommendations is beneficial only in

short-term to the public at large and recommendations have no significant impact on the

movement of stocks in the pre-recommendation period and in the post –recommendation

period, there is significant impact for short term, but there is no significant impact for the

whole period of post recommendation.

7. While the performance of the traded volume on the publication day of the

recommendation and surrounding days. We find out that Average Relative Volume (ARV) on

the pre recommendation period has shown some increase in trading volume. Similarly, the

post recommendation period also shows increase in the traded volume for a short span. It can

be identified that the volume of stocks traded increased when recommendations are

announced but there is no significant relationship between recommendation date and trading

volume on the subsequent date.

8. When comparing the relation between Market Adjusted Return (MAR) and Relative

Trading Volume (RTV), it can be identified that the movement of MAR coincides with the

movement of RTV. But, after recommendation there is sharp increase in volume than market

adjusted return. From the study it is found that there is a positive relationship between trading

volume and market adjusted return.

V. CONCLUSION

The fundamental conclusion to be drawn from this paper is that the publication of “THE

HINDU BUSINESSLINE - Investment World” on Sundays newspaper appears to have an

impact on stock prices and is beneficial to the investors at least in short-term decisions. Many

study also inferred that the volume of stocks traded has increased when recommendations are

announced but there is no significant relationship between recommendation date and trading

volume on the subsequent dates. Between the trading volume and market adjusted return,

there is a positive relationship between them.




VI. REFERENCES

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10. Scott E. Stickel “The Anatomy of the Performance of Buy and Sell Recommendations”

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International Evidence” March, 2004

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ONLINE RESOURCES

1. www.thehindubusinessline.com

2. www.sebi.gov.in

3. www.papers.ssrn.com

4. www.jstor.org

5. www.springerlink.com

6. www.scribd.com

7. www.financeindia.org

8. www.capitalmarket.com

9. www.en.wikipedia.com

10. www.investopedia.com

11. www.economywatch.com

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