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2007bai7415.doc

  1. 1. Stock Recommendation and Market Reaction: The Empirical Analysis in Taiwan Yi-Hsien Wanga* Chin-Tsai Linb Shiou-Chen Liub a Department of Finance, Yuanpei University, No.306, Yuanpei St., HsinChu, Taiwan 30015, R.O.C b Graduate Institute of Business and Management, Yuanpei University, No.306, Yuanpei St., HsinChu, Taiwan 30015, R.O.C * Author for correspondence, e-mail: holland@mail2000.com.tw Abstract 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 stock. Keywords Public Information, Recommendatory Stock, Abnormal Return, Event Study, Abnormal Volumes 1. Introduction 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 1
  2. 2. 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). 2
  3. 3. 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 3
  4. 4. (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 4
  5. 5. 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 announcements. 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 t (2) ∑ AR i ,t ARt = i =1 N 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 (3) 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 ARit SAR E (4) tSROCSM = AR N N 1 SAR N ( N − 1) ∑ (SARiE − ∑ N iE )2 i =1 i =1 N SARi , E . where SARE = ∑ N i =1 The t-test statistic for the CARt for standardized residual cross-sectional is calculated as 5
  6. 6. SAR(r1 , r2 ) (5) t SROCSM = SCAR 2 1 N  N SCARi (r1 , r2 )  ∑  SCARi (r1, r2 ) − ∑  N ( N − 1) j =1  N   j =1  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 calculated as Number of shares tradedit (7) VOLit = 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. 1 −16 NVOLi = ∑ TVit 90 t = −105 (8) 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 Warner, 1985). 1 N VOLit AVt = ∑ N i =1 NVOLit (9) 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) 6
  7. 7. (11) 1 15 s= ∑ ( AVt − AV ) 2 ; 31 t =−15 1 15 where 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 announcement data. 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. 7
  8. 8. 2.0 .8 1.5 .6 1.0 .4 0.5 .2 0.0 .0 -0.5 -.2 -1.0 -.4 -1.5 -15 0 +15 -.6 -15 0 +15 Fig. 1. Abnormal return of announcements Fig. 2. Standardized abnormal return of announcements 12 6 10 5 8 4 6 3 4 2 2 1 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). 8
  9. 9. 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 prices. 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 9
  10. 10. -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 * 2.1414 2.2536 -14 1.0377 * 0.5325 ** 2.3104 2.5749 10
  11. 11. -13 0.7486 * 0.3799 1.419 1.1726 -12 1.7812 * 0.8465 ** 2.2109 2.4285 -11 2.8324 ** 1.3737 ** 3.2191 3.4611 -10 3.3518 ** 1.7139 ** 3.457 3.7945 -9 3.359 ** 1.7479 ** 3.2851 3.6414 -8 3.5216 ** 1.8562 ** 3.3221 3.5981 -7 4.5756 ** 2.3346 ** 4.2401 4.3372 -6 4.8925 ** 2.4576 ** 4.6387 4.6972 -5 6.0731 ** 2.9889 ** 5.1837 5.2318 -4 6.3238 ** 3.1214 ** 5.4347 5.5035 -3 7.0078 ** 3.3934 ** 5.9042 5.9076 -2 8.6799 ** 4.1512 ** 6.5274 6.2586 -1 10.2588 ** 4.898 ** 7.0534 6.5064 0 10.7641 ** 5.1751 ** 6.5938 6.1309 1 9.7326 ** 4.6735 ** 6.3673 5.9957 2 9.9031 ** 4.6908 ** 6.1172 5.7098 3 10.2152 ** 4.8697 ** 5.5562 5.1653 4 9.8254 ** 4.6777 ** 5.0997 4.7482 5 10.1181 ** 4.8129 ** 4.9607 4.8311 6 9.9941 ** 4.7888 ** 4.9015 4.9188 7 9.4835 ** 4.5538 ** 4.6062 4.696 8 8.8963 ** 4.3249 ** 4.2547 4.3564 9 8.2986 ** 4.0223 ** 3.8409 4.0656 10 9.1739 ** 4.3952 ** 4.1442 4.3692 11 8.4158 ** 4.1206 ** 3.7809 3.9412 12 8.2804 ** 4.0996 ** 3.6211 3.7032 13 8.1787 ** 4.0414 ** 3.4543 3.4482 14 8.1771 ** 4.0639 ** 3.3552 3.3277 15 8.273 ** 4.1596 ** 3.1342 3.1172 Note: ** (*) denotes statistical significance at the 1% (5%) level. 3.2 Volumes results of sample By estimate average trading volumes preface the adjusted volumes model from event window. An analysis of trading volumes is the results of event study for analysts’ recommendations. Relative volume in Table 3 presents the results on the behavior of average trading volumes (AV) and 11
  12. 12. 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 media recommendation. 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. 2.0 24 20 1.6 16 1.2 12 0.8 8 0.4 4 0.0-15 0 +15 0 -15 0 +15 Fig. 5 Average volume of announcements Fig. 6 Standardized average volume of announcements 2.8 32 28 2.4 24 2.0 20 1.6 16 12 1.2 8 0.8 4 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 12
  13. 13. 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 announcement date. 13
  14. 14. Table 3 Average trading volumes and Standardized average trading volumes around announcement date of the analysts' recommendations Event AV t-test OCSM Sign test SAV t-test SROCSM Sign test window -15 0.6688 0.7452 2.4524** 1.9052* 0.802 5.8259** 2.5677** 1.9052* -14 0.4599 0.5124 2.6793** 0.5443 0.5711 4.1486** 2.7753** 0.5443 -13 0.2686 0.2993 1.6851* 0.2722 0.4631 3.3644** 2.1927** 0.2722 -12 0.6775 0.7549 3.2627** 1.3608 0.7883 5.7263** 2.9085** 1.3608 -11 1.1233 1.2515 3.6590** 2.4495** 1.324 9.6182** 3.8060** 2.4495** -10 0.6954 0.7747 2.7227** 0.2722 0.8861 6.4369** 2.8799** 0.2722 -9 0.4494 0.5007 1.84298* 0.8165 0.6127 4.4507** 2.5311** 0.8165 -8 0.6743 0.7513 2.7394** 0.2722 0.7571 5.4998** 2.7803** 0.2722 -7 0.5972 0.6654 3.3876** 1.3608 0.6171 4.4831** 3.1071** 1.3608 -6 1.1889 1.3246 4.5410** 3.2660** 1.3201 9.5897** 4.4173** 3.2660** -5 0.7545 0.8406 3.4974** 1.6330 1.0386 7.5450** 3.3201** 1.6330 -4 0.6256 0.6970 2.6880** 1.9052* 0.9091 6.6039** 3.0815** 1.9052* -3 0.7465 0.8317 3.5738** 2.9938** 1.124 8.1650** 3.3145** 2.9938** -2 1.2546 1.3978 5.1172** 3.8103** 1.5744 11.4373** 5.5320** 3.8103** -1 1.8050 2.0110* 4.6298** 3.8103** 2.5347 18.413** 4.1927** 3.8103** 0 1.0225 1.1392 3.7435** 3.2660** 1.2976 9.4263** 3.3090** 3.2660** 1 0.7521 0.8380 2.8931** 2.4495** 0.9471 6.8802** 2.0670* 2.4495** 2 0.8976 1.0000 3.0965** 2.9938** 1.0188 7.4014** 3.7512** 2.9938** 3 0.7191 0.8012 2.7030** 0.2722 1.0603 7.7028** 2.8577** 0.2722 14
  15. 15. 4 0.9202 1.0252 2.7500** 1.9052* 1.378 10.0105** 2.6930** 1.9052** 5 0.8241 0.9182 3.2405** 1.9052* 1.3131 9.5389** 3.1657** 1.9052** 6 0.7055 0.7860 2.6350** 1.6330 0.9896 7.1890** 2.4778** 1.6330 7 0.4829 0.5381 2.1994* 1.9052* 0.7579 5.5055** 2.5295** 1.9052** 8 0.3322 0.3701 1.5726* 0.2722 0.6111 4.4394** 2.1541* 0.2722 9 0.4819 0.5370 2.1133* 0.2722 0.7498 5.4473** 2.2834* 0.2722 10 0.8649 0.9636 2.9856** 1.6330 1.3326 9.6808** 3.0016** 1.6330 11 0.4796 0.5344 2.4968** 0.8165 0.6429 4.6701** 2.7181** 0.8165 12 0.4449 0.4957 2.4161** 0.8165 0.6128 4.4515** 2.4365** 0.8165 13 0.7374 0.8216 2.5384** 1.6330 1.2449 9.0435** 2.4476** 1.6330 14 0.6091 0.6786 2.3293** 1.0887 1.0717 7.7853** 2.4661** 1.0887 15 0.7693 0.8571 2.8573** 2.1773* 1.2634 9.1780** 2.6764** 2.1773* Note: 1. The average trading volumes and standardized 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%) level. Table 4 Cumulative average trading volumes and standardized cumulative average trading volumes around announcement date of the analysts' recommendations Event CAV t-test OCSM Sign test SCAV t-test SROCSM Sign test window -15 0.6688 0.7452 2.4524** 1.9052* 0.802 5.8259** 2.5677** 1.9052* -14 1.1288 0.8893 2.7240** 1.6330 1.373 7.0530** 2.8850** 1.6330 -13 1.3974 0.8989 2.7015** 1.6330 1.8362 7.7012** 2.9603** 1.3608 -12 2.0749 1.1559 3.2618** 1.9052* 2.6244 9.5326** 3.1558** 1.9052* -11 3.1982 1.5935 3.8250** 3.266** 3.9484 12.8276** 3.8267** 3.2660** -10 3.8935 1.7710* 3.7437** 3.266** 4.8345 14.3378** 3.7960** 3.2660** -9 4.3429 1.8288* 3.6144** 2.9938** 5.4472 14.9564** 3.7404** 2.9938** -8 5.0172 1.9763* 3.6469** 3.2660** 6.2043 15.9349** 3.7301** 3.2660** -7 5.6145 2.08518* 3.7473** 2.7217** 6.8214 16.5180** 3.7737** 2.7217** -6 6.8034 2.3970** 4.1647** 3.5382** 8.1415 18.7028** 4.0209** 3.5382** -5 7.5579 2.5389** 4.2676** 3.2660** 9.1801 20.1074** 4.0771** 3.2660** -4 8.1834 2.6320** 4.2010** 2.7217** 10.0891 21.1577** 4.0812** 2.7217** -3 8.9299 2.7594** 4.2624** 3.2660** 11.2131 22.5922** 4.0713** 3.2660** -2 10.1845 3.0326** 4.5991** 4.3546** 12.7875 24.8272** 4.3626** 4.3546** -1 11.9895 3.4490** 4.8569** 4.3546** 15.3222 28.7395** 4.4637** 4.3546** 0 13.012 3.6243** 5.0183** 3.5382** 16.6198 30.1835** 4.4300** 3.5382** 1 13.7642 3.7193** 4.9711** 4.0825** 17.5669 30.9510** 4.2225** 3.5382** 2 14.6617 3.8503** 4.9622** 3.8103** 18.5857 31.8235** 4.2366** 3.8103** 3 15.3809 3.9314** 4.9378** 3.8103** 19.6460 32.7418** 4.2209** 3.8103** 15
  16. 16. 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%) level. 4. Conclusion 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. REFERENCES Barber, B. M. & Loeffler, D. 1993. The sarboard column: second-hand information and price pressure. Journal of Financial and Quantitative Analysis, 28, 273-284. 16
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