Stock Recommendation and Market Reaction: The
Empirical Analysis in Taiwan
Yi-Hsien Wanga* Chin-Tsai Linb Shiou-Chen Liub
Department of Finance, Yuanpei University, No.306, Yuanpei St., HsinChu, Taiwan 30015, R.O.C
Graduate Institute of Business and Management, Yuanpei University, No.306, Yuanpei St., HsinChu,
Taiwan 30015, R.O.C
Author for correspondence, e-mail: email@example.com
This study examines the effects of media recommendations on the performance of electronics
companies listed on Taiwan stock market. This empirical study found that investors who obtained
different information contents from a newspaper column around the announcement date. These
analytical results provide evidences that that stock market information is often leaked in advance and
investors would hold a conservative position following information disclosure of recommendatory
Keywords Public Information, Recommendatory Stock, Abnormal Return, Event Study,
From an investor prospective, the best opportunity can earn extra remuneration is through
information disclosure. All investors desire the latest information under the minimal cost. The
information recommendation stock such as investment column of financial paper, major magazine and
public journalism that can be obtained approximately cost without in the market. Hence, academicians
and practitioners would pay attention to investors decision that obtained abnormal returns through
recommendatory stock of investment columns (Davies and Cance, 1978; Liu et al., 1990). They have
significant value by analysts’ stock recommendations. The investment strategy of buying stocks and
selling stocks that the recommendations yields abnormal return (Barber et al., 2001). They founds
sample period had a significant impact relating with analysts’ stock recommendations (Barber et al.,
2002). When initiating recommendation that is a significant short stock return (Sayrak and Dhiensiri,
2002; Irvine, 2003). There is a negative significant that opinion of analysts and the stock market
response to recommendation (Dhiensiri et al., 2005). The analysis founds the market’s response to
strongly influenced by the analysts’ recommendation (Brown, Chen and Ho, 2006).
In an empirical study of U.S. stock market, established a hypothesis for an efficient market and
distinguished three markets by information content, so three markets hypothesis of efficiency are Weak
Form Efficiency Market, Semi-Strong Form Efficiency Market and Strong Form Efficiency Market
(Fama, 1970). The test of the weak form efficiency market, an investor cannot obtain an abnormal
return for the historical price, but can obtain an abnormal return by relying on public information or
private information. However, the test of the semi-strong form efficiency market, an investor cannot
obtain an abnormal return by relying on public information but can obtain abnormal return using
private information, and in the case of strong form efficiency market, private or public information
correlates with price, that is explained with relation to an investor can not obtain abnormal return if it is
obtained normal return. In the efficient market, if securities firms have not provides with information
content and stock recommendation column of journalism publishes, generally speaking, it should not
affect the behavior of stock recommendation which the investor can not obtainment extra return by
information content. Stock price completed and immediate response all information that the investor
can not arbitrage by the column of information. According to latest journalism recommended stock
column of data, set against the effectiveness research of the investor. An attempt is also made to further
understand recommendation stock of the information content, that expecting gained the support from
stock recommendation column.
If the stock reacts to recommendation of information content, the stock will not overturn afterwards.
However the stock overturns as a result of price pressure, explaining why the stock produces the
overturning effect (Barber and Loeffler, 1993). They found any investor indefinite variation market
revelation of information impossible. Until investors achieve these conditions, analysts can credibly
convey unfavorable information, but it can not convey favorable information (Morgan and Stocken,
2003). According to analysts’ forecast is recalculated every time a recommendation is changed (Barber
et al., 2001, 2003). They found that initiating recommendations bring add information to the market
and encourages participants to trade (Brennan and Tamarowski, 2000; Irvine, 2003). Our analysis finds
that it is negative relationship between opinion of analysts and the stock market (Dhiensiri et al., 2005).
In this paper, we examine how stock recommendations from journalism affect that the reaction of
stock price of investors acting upon those recommendations. The paper touches on two fundamental
themes: reactions to abnormal return around announcement date of the analysts’ recommendations and
reactions to trading volumes around announcement date of the analysts’ recommendations. We show
that the price survey effect document activity triggered tells us. First, we show that the
recommendation stock obtain extra abnormal return. This trading effect may price and trading
volumes of recommendation stock for around announcement date. Second, issuers may deliberately
change the recommendation stock to investment for around announcement date, meanwhile, the
information about successful recommend may appears these information leakage
effect and price effect lead investors to buy and sell recommendation stock on the
announcement date. Third, if they believe that the public information can content to
future, performance. Nevertheless, public information will react positively to buy and
sell stock and this information effect will appear to price and trading volumes of
recommendation stock following the announcement data of stock issuance.
Prior to the research found that the journalism recommendation did not obtained abnormal returns
(Cowles,1933; Longue and Tuttle, 1973; Bidwell, 1977), but obtain abnormal return were found that
take account of methodology and collection of the research data from the journalism recommendation
in recent research (Dimson and Marsh, 1984; Elton et al., 1986; Stickel, 1995; Womack, 1996; Barber
et al., 2001). Stock recommendation comparison of recommended and non-recommended stocks,
showed that the average weekly return on recommended stocks was significant, indicating that
recommendation had information value (Bjerring et al., 1983). Existing researches found the short
column recommends the information value, while, under long-term, the column recommends the
absence of information value (Lee, 1986). The stock analysts provide economical price which an
obtained abnormal return from column information (Davies and Cance, 1978; Liu et al., 1990). While
investors that purchasing long one or two days before the recommendation will obtain positive
abnormal returns and those selling out will obtain negative abnormal returns. These founds
demonstrated the value of information obtained by investors (Benish, 1991).
They are suggested more than information for reduce actively traded securities by volume analysis
(Ferreira and Smith, 1999). So far numerous study found that a positive significant in trading volumes
from public information (Richardson et al., 1986; Karpoff, 1987; Woodruff and Senchack, 1988;
Ferreira and Smith, 1999). These daily trading volumes of t-test will resolution, if an average trading
volume is significantly different (Liu et al., 1990; Palmon et al.). The stocks with high (low) trading
volume earn lower (higher) returns (Lee and Swaminathan, 2000). A few impacts on volatility and
negative price effects made positive trading volumes (Draper et al., 2001 ). Caused statistically
significant include positive price effect and positive trading volumes (Chen and Wu, 2001). The trading
volume relationship to event for analysts’ recommendations is associated to significant increase
(Morgan and Stocken, 2003). According to the above studies, this study examines the effects of
journalism recommendations on the performance of electronics companies listed on Taiwan Stock
Market. This study explores how stock recommendations from journalism public affect reaction of the
stock price of investors acting upon those recommendations. Hence, might to estimation investor
behavior whether could to obtain abnormal return and trading volumes, using event study approach
based on database from Taiwanese electronic corporations listed on the Taiwan Stock Market. The rest
of this paper is organized as follows. Section 2 describes our date sources and the methodology.
Section 3 examines the sample of price and trading volume surrounding recommendations revisions.
Finally, section 4 presents concludes this paper.
2. Database and methodology
2.1 Description of the sample
This study analyzed compose of a sample derive from the “Investment Guide” column that is issue
daily in the Economic Daily News of Sunday from March 1, 2005 to February 28, 2006. An initial
sample is selected to occur with the electronics companies listed on the Taiwan Stock Market. Daily
stock index data source are provided by the Taiwan Economic Journal (TEJ) in Taiwan. In our analysis,
we collect initial 102 samples. Thus, these sample including 52 samples of particular stock, new stock
and estimated cover stock, were excluded. The final sample announcements with respect to the number
of different industries, 50 are represented.
2.2 Event study and methodology
To determine whether there exist information effect around the announcement date, an event study
methodology described is performed. This studied period event window contains announcement days,
15 days before and 15 days after, so that the possibility of obtaining abnormal returns. The criterion for
include 90 days of return in the estimation period. Therefore, observational period include 121 days
that combine estimation period and event period.
The event day is cleared about the announcement data of recommendation stock. The event window
extends from 15 trading days before and 15 trading days after the announcement date. This study
utilized event study methodology. The purpose of the investigation whether caused abnormal returns of
stock, when information and event happened. Event study can be divided into three types: Market-
Wide, Industry-Specific or Firm-Specific. An example of a Market-wide is change of government policy
or shock of macroeconomics variable; Industry-Specific and Firm-Specific are emphasize that affect a
property or a company (Fama, 1970; Morgan and Stocken, 2003). Events include effects on specific
properties of the economic event, changes of laws, changes in the company dividend polices and profit
The expected return was derived using the market model where the model parameters α and β were
obtained from the estimation period.
Rit = α i + β i Rmt + ε it (1)
Average abnormal returns estimating value on day t for a portfolio of N stocks can be calculated as
∑ AR i ,t
ARt = i =1
where t = -15, -14, …, 0, …, 14, 15.
The event period of average abnormal returns through t days from b accumulated to e, (-15≦b≦e≦15),
can be calculated as
1 N e
CAR (b, e) = ∑∑ ( ARt ,t )
N t =1 t = b
where (b, e) is the event window, CAR(b, e) is the average abnormal return from event b day
cumulative to e day.
The ordinary cross-sectional method ignores estimation period estimates of variance, thus, this paper
uses the standardized residual cross-sectional for its t-test (Boehmer et al., 1991). The resulting t-test
statistic for is
SAR E (4)
N ( N − 1)
∑ (SARiE − ∑ N iE )2
i =1 i =1
N SARi , E .
where SARE = ∑ N
The t-test statistic for the CARt for standardized residual cross-sectional is calculated as
SAR(r1 , r2 ) (5)
t SROCSM =
1 N N
SCARi (r1 , r2 )
∑ SCARi (r1, r2 ) − ∑
N ( N − 1) j =1 N
So far numerous research found that a significant cumulative trading volumes from public
information (Richardson et al., 1986; Karpoff, 1987; Woodruff and Senchack, 1988; Ferreira and
Smith, 1999). Hence, trading turnover ratio for recommendations stock i on day t is proxy for trading
volumes (VOLit) for recommendations stock i on day t (Michaely et al., 1995; Chan and Wei, 2001;
Chuang and Chuang, 2005). The daily trading turnover ratio for recommendations stock i on day t is
Number of shares tradedit (7)
Number of shares outsanding it
where t = -105, . . . , -16.
Normal trading volumes (NVOLi) for recommendations stock, we use the 90 days estimated period to
the event window for as well as normal trading volume.
NVOLi = ∑ TVit
90 t = −105
where i = 1, 2, . . . , N.
This consider the average trading volumes (AV) during event window, which are estimated of the
average trading volume is normalized and can be compared across other stocks of multiform sizes. The
test uses the average daily trading volumes for a portfolio of N stocks is then calculated as (Brown and
1 N VOLit
AVt = ∑
N i =1 NVOLit
where t = -15, -14, . . . , 14, 15.
Finally, the abnormal trading volumes (AVOLt) period the for day t and its standard deviation (s) are
calculated, respectively, as
AVOLt = AVt − 1, t = −15, . . . , + 15 (10)
s= ∑ ( AVt − AV ) 2 ;
31 t =−15
AV = ∑ AVt .
31 t = −15
3. Empirical tests
In this section, we discussion the empirical results for price and trading volume momentum
strategies. We deal with the stock price response to recommendation in section 3.1 and the response of
trading volume in section 3.2. The plan of this paper is as follow. In section 3.1, we show the abnormal
returns and ignore the assumption of homoscedasticity of the OLS residuals that satisfied to have
efficient parameter estimates using the market model of the recommendation stock around the
announcement data. In section 3.2, we introduce trading volume of t-test and nonparametric test (sign
test and cross-sectional test) of the recommendation stock on the window event around the
3.1 Returns results of sample
Table 1 presents the results to the behavior of abnormal return (AR) and standardized abnormal
return (SAR) of the listed electronic stock on the event window around the announcement date for
journalism recommendation. Moreover, Table 2 presents the similar results on the behavior of
cumulative abnormal return (CAR) and standardized cumulative abnormal return (SCAR) of the listed
electronic stock on the event window around the announcement date for journalism recommendation.
The trend of abnormal return and standardized abnormal return are shown as Fig. 1 and Fig. 2,
respectively. The trend of cumulative abnormal return and standardized cumulative abnormal return are
shown as Fig. 3 and Fig. 4, respectively.
-1.5 -15 0 +15 -.6 -15 0 +15
Fig. 1. Abnormal return of announcements Fig. 2. Standardized abnormal return of
0 -15 0 +15 0 -15 0 +15
Fig. 3. Cumulative abnormal return of Fig. 4. Standardized cumulative abnormal
announcements return of announcements
Table 1 presents the results on the behavior of abnormal return (AR), standardized abnormal return
(SAR) and their t-test statistics of the listed electronic stock on event window around the announcement
date for Media recommendation. Prior to the announcement date of media recommendation events, the
empirical evidence found that the negative abnormal returns, -0.5107, -0.5872 and -0.5977, for day +7,
+8 and +9 are statistically significant at 0.05 level by t-test. Moreover, there the positive abnormal
returns were significantly in the following -15 days (See Fig. 1). The test of the standardized abnormal
return around the analysts’ recommendation show that there is significant on the days of the
announcement date, while there is found that the negative abnormal return of -0.235, -0.2289, -0.3026
and -0.2746, for day +7, +8, +9 and +11 are statistically significant at 0.05 level by t-test (See Fig. 2).
Table 2 presents the results on the behavior of cumulative abnormal return (CAR), standardized
cumulative abnormal return (SCAR) and its t-test statistics of the listed electronic stock on event
window around the announcement date for Media recommendation. Prior to the announcement data of
media recommendation events, the empirical evidence found that the cumulative abnormal returns for
event window from -11 to +15 show statistically significant about at 0.01 level (See Fig. 3).
Furthermore, the standardized cumulative abnormal return around the analysts’ recommendation show
that the significant reaction on the days of the announcement date, while there is found that the
standardized cumulative abnormal return for event window from -12 to +15 show statistically
significant at 0.01 level (See Fig. 4).
Table 1 and Table 2 show positive abnormal returns “event window” includes -1, -2, -3, -5, -7, -11,
-12 and -15 days before and +10 days after on the announcement days, and negative abnormal returns
one day the announcement is significant. Therefore, days before had positive abnormal returns and
event days after had negative abnormal returns (Brown and Warner,1985; Carrado, 1989). This study
finding the return the days before bought recommendation shows that there exists a significant effect
on the days before the announcement (Menendez- Requejo, 2005).
The results show a striking positive abnormal effect 15 days before and a negative abnormal effect
one day after, but the abnormal return was not significant in the following 6 days. These abnormalities
reveal the phenomenon of leaked out information content. A phenomenon which a recommended
amount of stock is purchased before recommended stocks are purchased for the recommended. On the
announcement day, investors received information and bought recommend stocks. However, the
recommended sold stocks and obtained abnormal returns, which caused increases in increased stock
As Table 1 and Table 2 demonstrate, an investor can use a journalism recommendation, but the
abnormal return is insignificant after event days. However, most investors use investment analysis for
invest by journalism or television includes both news and advice from stock professionals.
Furthermore, internal information is not easily obtained investment information. In the stock market,
because of time differences, abnormal returns are not easily obtained by the average investor.
Therefore, the Taiwan stock market can be considered semi-efficient.
Table 1 Abnormal return and Standardized abnormal return around announcement
date of the analysts' recommendations
Event window AR t-test SAR t-test
-15 0.7534 2.1414
＊ 0.3847 2.2536
-14 0.2844 0.9249 0.1478 1.0697
-13 -0.2892 -0.9264 -0.1526 -1.1253
-12 1.0326 2.6658
＊＊ 0.4665 2.6708
-11 1.0513 2.6805
＊＊ 0.5273 2.7491
-10 0.5194 1.3079 0.3402 1.8077
-9 0.0072 0.0238 0.034 0.2554
-8 0.1626 0.4725 0.1083 0.6713
-7 1.0541 2.7924
＊＊ 0.4784 2.9422
-6 0.3169 0.9431 0.123 0.8045
-5 1.1805 3.8364
＊＊ 0.5313 3.5064
-4 0.2507 0.887 0.1325 1.0219
-3 0.6841 2.3150
＊ 0.272 2.0442
-2 1.6721 3.8629
＊＊ 0.7579 3.8209
-1 1.5789 4.0677
＊＊ 0.7467 3.9365
0 0.5053 1.2975 0.2771 1.5257
1 -1.0315 -2.9773
＊＊ -0.5016 -3.1279
2 0.1705 0.4808 0.0173 0.1012
3 0.3121 0.8958 0.1788 1.0595
4 -0.3898 -1.0245 -0.1919 -1.1246
5 0.2927 0.7284 0.1351 0.7767
6 -0.1239 -0.3203 -0.0241 -0.1284
7 -0.5107 -1.6454
＊ -0.235 -1.7504
8 -0.5872 -2.1767
＊ -0.2289 -1.9261
9 -0.5977 -1.6552
＊ -0.3026 -1.8142
10 0.8753 2.8126
＊＊ 0.3729 2.8637
11 -0.7582 -2.6800
＊＊ -0.2746 -1.8431
12 -0.1353 -0.3853 -0.0209 -0.1242
13 -0.1017 -0.2814 -0.0582 -0.3334
14 -0.0016 -0.0055 0.0225 0.1562
15 0.0959 0.2063 0.0957 0.4609
Note: 1. The average abnormal returns for the event window from -15 to15 are calculated using a
market model. The market model is estimated over 90 days prior to the event window. 2.**(*)denotes
statistical significance at the 1% (5% ) level.
Table 2 Cumulative abnormal return and Standardized cumulative abnormal return around
announcement date of the analysts' recommendations
Event window CAR t-test SCAR t-test
-15 0.7534 ＊ 0.3847 ＊
-14 1.0377 ＊ 0.5325 ＊＊
standardized average trading volumes (SAV) of the listed electronic stock on event window around the
announcement date for media recommendation. Moreover, Table 4 presents the similar results on the
behavior of cumulative average trading volumes (CAV) and standardized cumulative average trading
volumes (SCAV) of the listed electronic stock on event window around the announcement date for
The trend of average trading volumes and standardized average trading volumes are shown as Fig. 5
and Fig. 6, respectively. And the trend of cumulative average trading volumes and standardized
cumulative average trading volumes are shown as Fig. 7 and Fig. 8, respectively.
0.0-15 0 +15 0 -15 0 +15
Fig. 5 Average volume of announcements Fig. 6 Standardized average volume of
0.4-15 0 +15 0 -15 0 +15
Fig. 7 Cumulative average volume of Fig. 8 Cumulative standardized average
announcements volume of announcements
As shown, Table 3 presents average trading volumes (AV), standardized average trading volumes
(SAV) and their t-test statistics and nonparametric test (sign test and cross- sectional test ) of the
recommendation stock on the event window around the announcement date (Corrado, 1989). The
average trading volumes are resolved for daily day of the event window included day -15 to day +15.
For the recommendation stock, Table 3 shown that the average trading volumes (AV) 1.805 for day -1 is
positive statistically significant at 0.05 level using t-test is 2.011, respectively, the sign test and cross-
sectional test are also significant the same results (See Fig. 5). Furthermore, our founding that the
standardized average trading volumes for day -15 to day +15 are significant, performance (See Fig. 6).
Table 4 presents that the cumulative average trading volumes, standardized average trading volumes
and their t-test statistics and nonparametric test (sign teat and cross- sectional test) on the event
window. The test found that the cumulative average trading volumes from day -10 to day -7 show
statistically significant at 0.05 level using t-test are 1.7710, 1.8288, 1.9763 and 2.08518, nevertheless,
on the event window for day -6 to day +15 show positive statistically significant at 0.01 level using t-
test (See Fig. 7). Furthermore, the standardized cumulative average trading volumes appear the
significant reaction on the days of the announcement date, while there is found that the standardized
cumulative average trading volumes for event window from -15 to +15 show positive statistically
significant at 0.01 level (See Fig. 8).
Table 3 and Table 4 results show that estimate average volumes and cumulative average volumes
positive statistically significant prior to the announcement date of the analysts’ recommendations for
day -1. Hence, the results that the analysts’ recommendations conduce to trading volumes reason on the
4 16.3011 4.0611** 4.8603** 3.8103** 21.0240 34.1512** 4.1130** 3.8103**
5 17.1252 4.1636** 4.9263** 4.0825** 22.3371 35.4097** 4.1252** 4.0825**
6 17.8306 4.2354** 4.8386** 4.0825** 23.3267 36.1283** 4.0587** 4.0825**
7 18.3136 4.2545** 4.7351** 4.3546** 24.0846 36.4822** 4.0007** 4.3546**
8 18.6458 4.2405** 4.6640** 4.0825** 24.6957 36.6202** 3.9519** 4.0825**
9 19.1277 4.2622** 4.6150** 4.0825** 25.4456 36.9698** 3.9267** 4.0825**
10 19.9927 4.3684** 4.5685** 4.0825** 26.7782 38.1504** 3.8992** 4.0825**
11 20.4723 4.3896** 4.5278** 4.0825** 27.4211 38.3360** 3.8803** 4.0825**
12 20.9172 4.4042** 4.4842** 4.0825** 28.0338 38.4865** 3.8603** 4.0825**
13 21.6546 4.4801** 4.418** 4.0825** 29.2787 39.4964** 3.7906** 4.0825**
14 22.2636 4.5287** 4.3483** 4.0825** 30.3504 40.2540** 3.7436** 4.0825**
15 23.0329 4.6090** 4.3154** 4.0825** 31.6138 41.2478** 3.7000** 3.8103**
Note: 1. The cumulative average trading volumes and standardized cumulative average trading volumes
for the event window from -15 to 15 are calculated using a market model. The market model is
estmated over 90 days prior to the event window. 2. **(*) denotes statistical significance at the 1%(5%)
This paper analysis of abnormal return and trading volume from the “Investment Guide” column that
is daily in the Economic Daily News of Sunday. This paper analyzes the returns to analysts’
recommendations over the March 1, 2005 to February 28, 2006 period. It is shown that the introduction
of recommendation stock leads to a price effect and trading volume, phenomenon.
For the purpose of the this investigation whether the stock market interprets the information content
in analysts’ recommendation by journalism published, and how category of the efficiencies market on
Taiwan stock market. We find this paper verify that analysis of importance to investors and all stock
market participator with relation to information content. Our findings also have journalism
recommendation stock that it is empirical results presented that positive abnormal returns are
statistically significant for day 0 and +9. However, positive abnormal returns of the stock disappeared
following announcement of publicly recommendation events. If investor rely on recommend stock of
public journalism that can not earn abnormal return. Investor would allocate to hold the active or
conservative position of portfolio or reduced the average holding cost following publicly information
disclosure of recommendatory stock. Therefore, Taiwanese stock market conforms to the semi-strong
form efficiency market, hence, fundamental and technical analysis that were ineffective.
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