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
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. 12
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.
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. 13
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
International Research Journal of Business and Management – IRJBM ISSN 2322-083X
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© Global Wisdom Research Publications – All Rights Reserved. 14
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
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© Global Wisdom Research Publications – All Rights Reserved. 15
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.
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. 16
(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
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© Global Wisdom Research Publications – All Rights Reserved. 17
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.
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TABLE – 4
DETERMINATION OF STOCK RETURN PERFORMANCE OF BUY
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
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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).
DETERMINATION OF STOCK RETURN PERFORMANCE OF BUY
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
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© Global Wisdom Research Publications – All Rights Reserved. 20
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
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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
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© Global Wisdom Research Publications – All Rights Reserved. 22
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.
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© Global Wisdom Research Publications – All Rights Reserved. 23
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
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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.
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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.
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© Global Wisdom Research Publications – All Rights Reserved. 26
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.
International Research Journal of Business and Management – IRJBM ISSN 2322-083X
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© Global Wisdom Research Publications – All Rights Reserved. 27
• 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.
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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.
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© Global Wisdom Research Publications – All Rights Reserved. 29
VI. REFERENCES
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© Global Wisdom Research Publications – All Rights Reserved. 30
10. Scott E. Stickel “The Anatomy of the Performance of Buy and Sell Recommendations”
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IRJBM – (www.irjbm.org ) March - 2014 - Volume No – III
© Global Wisdom Research Publications – All Rights Reserved. 31
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