The effects of stock market rumors on stock prices: evidence from an emerging market

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1 ejournal of Multinational Financial Management 11 (2001) The effects of stock market rumors on stock prices: evidence from an emerging market Halil Kiymaz * Finance and Economics-SBPA, Uni ersity of Houston-Clear Lake, Houston, TX 77058, USA Received 5 June 1999; accepted 18 February 2000 Abstract The purpose of this study is to investigate the effects of stock market rumors on the prices of stocks traded at the Istanbul Stock Exchange. The sample consists of 355 favorable rumors mentioned in the HOTS column of Ekonomik Trend. While positive significant abnormal returns are observed in each of the 4 days prior to the publication date, negative insignificant abnormal returns are detected in the post-publication period. The findings in the pre-publication period refute the strong form of market efficiency while the findings in the post-publication period suggest that investment decisions based on the published rumors would not benefit investors. A further analysis based on the content of rumor shows that earning expectations rumors, and purchases by foreign investors rumors generate greater impact on stock prices than other rumors Elsevier Science B.V. All rights reserved. JEL classification: G14; G15 Keywords: Stock market rumors; Emerging market; Istanbul stock exchange 1. Introduction Although the behavior of stock market prices has been investigated extensively, the question of whether trading based on a particular set of information can lead investors to obtain excess returns remains as an interesting topic to study. Studies investigating effects of analysts recommendations or rumors on stock prices are * Tel.: ; fax: address: (H. Kiymaz) X/01/$ - see front matter 2001 Elsevier Science B.V. All rights reserved. PII: S X(00)

2 106 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) mainly related to the market efficiency hypothesis. The strong form of the efficient market hypothesis assumes that all information, whether public or private, is rapidly incorporated into security prices that no investor can use it to earn excess returns. Although the initial studies (i.e. Diefenback, 1972; Logue and Tuttle, 1973) argue that information based on market rumors does not have any economic value, later studies report statistically significant stock price reactions to stock market rumors. The majority of studies in literature seem to refute the market efficiency hypothesis in its strongest form. These studies document the existence of significant abnormal returns following analysts recommendations or rumors. Among them Lloyd-Davies and Canes (1978), Syed et al. (1989), Liu et al. (1990), Barber and Loeffler (1993) report abnormal stock price performance following recommendations reported in the Dartboard column of the Wall Street Journal (WSJ). The objective of this study is to investigate whether stock market rumors have any impact on common stocks traded at the Istanbul Stock Exchange (ISE) by examining the Heard on the Street (HOTS) column of Ekonomik Trend (ET) weekly. Furthermore, the impact of the content of the rumors on stock prices is investigated. The results of this study provide additional international evidence on effects of rumors on stock prices. The empirical findings show the existence of positive and significant abnormal returns in each of the 4 days prior to the publication date, and negative insignificant abnormal returns in the post-publication period. These results suggest that rumors and gossips contained in the HOTS column have been disseminated prior to their publication. A further analysis based on the content of rumor reveals that the earning expectation rumors and purchases by foreign investors rumors generate greater impact on stock prices than other rumors. 2. Literature review The question of whether trading based on recommendations and/or rumors published in newspaper or magazines would benefit investors has been investigated extensively. The empirical studies in this subject report mixed results. Diefenback (1972) and Logue and Tuttle (1973) are two initial studies reporting that analysts recommendations have no value for investors. Later studies, on the other hand, report that information provided by the Wall Street Journal Heard on the Street column or analysts contain valuable information to investors. Lloyd-Davies and Canes (1978) focus on financial analysts recommendations as discussed in the HOTS column of the WSJ. They report that buy recommendations provide significant positive abnormal returns, while sell recommendations are associated with significant negative abnormal returns on the day of publication. They conclude that analysts and investment advisors provide valuable service to investors. Liu et al. (1990) extend the Lloyd-Davies and Canes (1978) study with more recent sample and further analyze the effects of the single-company versus multi-company recommendations, and the trading volume around the publication day. Their findings are in the line with the Lloyd-Davies and Canes (1978) study. Moreover, the results

3 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) indicate that investors respond earlier to the information and single company recommendations have greater impact on the stock prices than those of multi-company recommendations. Finally, they report higher trading volume around the publication day. There are also studies investigating the factors influencing the magnitude of stock market reaction to analysts information or recommendation provided by various publications. Beneish (1991) investigates explanations for the significant stock price reaction to analysts information reported in the HOTS column of the WSJ. The results indicate that market reaction persists after controlling for confounding releases. Furthermore, stock prices adjust prior to publication when recommendations are reported on a single firm. Huth and Maris (1992) examine the same issue in terms of the usefulness of recommendations in short term trade decision making and firm size. The findings indicate that information obtained from the HOTS column can produce statistically significant stock price movements. Firm size is found to be important only for negative comments in the column. Barber and Loeffler (1993) analyze the stock price and volume behaviors using recommendations published in the Dartboard column of the WSJ. They report average positive abnormal returns of 4% in 2 days following the publication. Furthermore, average volume doubles normal volume level in the same period. More recently, Mathur and Waheed (1995) investigate the stock price behavior of firms that are favorably mentioned in the Inside Wall Street column of Business Week. The results reveal the existence of positive significant abnormal returns on the day before the publication date, the publication date, and 2 days after the publication date. The study suggests that information provided by the column is valuable to short term traders if transaction costs are low. Moreover, the results indicate that investors who invest long term based on the information obtain rate of returns below market returns. In general, the studies on stock market rumors or analysts recommendations support the view that information provided to investors is valuable. This paper aims to investigate the effects of stock market rumors on stocks traded at the ISE to provide evidence from an emerging market. 3. Data and methodology The study uses the stock market rumors published in the HOTS column of the ET weekly magazine during the period of July 21, 1996 and August 17, The HOTS page is published every week in ET. Topics covered in the page include information about both single firms and a group of firms. The purpose of the page is to inform investors about market developments influencing stock prices. Information provided by the HOTS, with rare exceptions, is favorable. 1 The study period of is randomly selected.

4 108 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) Table 1 reports the sample selection and the division of final sample based on the content of rumors/gossip. During this period, a total of 614 favorable gossip/rumor are reported. 2 From this sample, the rumors published on the same topic and about the same firm in subsequent weeks are eliminated (186 rumors). Furthermore, firms with missing stock price data (73 rumors) are eliminated. The net sample consists of 355 rumors/gossip. I, then, classify the net sample according to the content of the rumors. I identify six groups of rumors. They are earning expectations rumors; firm sales/export rumors, undervalued stocks rumors, purchases by foreign investors rumors, unclassified rumors, and rumors without any content. The distribution of net sample based on the content of rumors is outlined in the Panel B of Table 1. The most favorite topic of rumors is earnings expectations with 128 rumor, followed by unclassified topics 3 with 108 rumors. Rumors without any content 4 (68 rumors) are in the third place. The remaining topics include undervalued stocks (23 rumors), purchases by foreign investors (22 rumors), and sales/export expectations (six rumors). Table 1 Sample selection and content of rumors a Panel A: Sample selection All rumors published 614 Less: subsequently published rumors 186 Less: missing data 73 Net sample 355 No. rumors Panel B: Classification of net sample based on the content of rumors Content of rumors No. rumors Earnings expectations 128 Firm sales/export 6 Undervalued stocks 23 Purchases by foreign investor 22 Unclassified 108 Rumors without content Total a This table presents the sample selection and the contents of rumors. The sample consists of favorable stock market rumors published in the HOTS column of Ekonomik Trend weekly magazine during the period of The magazine is published and distributed on Sundays. 2 During the study period, there were only three unfavorable rumors/gossips in the HOTS column, and they were not included in the study. 3 These rumors are the ones, which do not fall into any of identified rumors/gossips group. However, they do have contents. 4 These rumors do not contain any reason. A typical rumor in this case would state that an increase in stock prices is expected based on conversations on the street.

5 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) Table 2 Daily average abnormal returns (AARs) surrounding the publication of rumors a Event days AARs (%) t-value *** ** *** *** ** a This table presents the abnormal returns surrounding the publication date t=0 intheekonomik Trend. Abnormal return is calculated as the difference between the actual and expected return. Expected return is generated from the market model parameters. The ISE Composite index used as a proxy for market. The t-statistics tests the null hypothesis that the average abnormal returns are equal to zero. *** Statistically significant at 1%. ** Statistically significant at 5%. The event study methodology is employed to analyze the effects of rumors/gossips on stock prices as surveyed by Brown and Warner (1985). The analysis period extends from day 30 to +30 relative to publication date t= Empirical results To determine how stock prices are influenced by rumors, I pose three period analyses. The first examines the effect of rumors around the publication date. The 5 Standard event methodology is used to measure the stock price reaction for N firms in each of the group of firms. The standard event study methodology is not spelled out here.

6 110 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) second looks for unusual activity prior to publication of rumors. Finally, I analyze price movement after the publication date. The empirical results are reported on Tables 2 4. The daily average abnormal returns (AARs) for all rumors are calculated over 30 and +30 period relative to the event day 0. Only AARs for 10 and +10 period are reported on Table 2. The results indicate that the sample experiences statistically significant positive abnormal returns prior to publication of rumors. The AARs are 0.52, 0.29, 0.76 and 0.78% for the days 4, 3, 2 and 1, respectively. These results are statistically significant at 1% level. The AARs following the publication day are mostly negative and statistically insignificant. For example, AARs are 0.07% on day +1, 0.43% on day +2, 0.04% on day +3, and 0.37% on day +4. Only AARs on day +2 is statistically significant at 5% level. The average cumulative abnormal returns (CARs) for all rumors are reported on Table 3. In the top part of table, the CARs around the publication of rumors are reported. The results indicate that firms experience positive abnormal returns just before and after publication date. For example, during ( 1, +1), ( 2, +2), and Table 3 Cumulative abnormal returns (CARs) surrounding the publication of rumors a Windows CARs (%) t-value Combined periods ( 1, +1) *** ( 2, +2) *** ( 5, +5) *** ( 10, +10) * ( 20, +20) ( 30, +30) Prior to publication date ( 5, 1) *** ( 10, 1) *** ( 20, 1) ** After publication date (+1, +5) (+1, +10) (+1, +20) a This table presents the cumulative abnormal returns in combined, pre, and post publication period relative to publication date t=0 in the Ekonomik Trend. Abnormal return is calculated as the difference between the actual and expected return. Expected return is generated from the international market model parameters. The t-statistics tests the null hypothesis that the cumulative abnormal returns are equal to zero. *** Statistically significant at 1%. ** Statistically significant at 5%. * Statistically significant at 10%.

7 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) Table 4 Daily average abnormal returns (AARs) based on the content of rumors a Days Earnings expectations Sales/export expectations Undervalued stocks Purchases by foreign investor Unclassified rumors Rumors without content (n=128) (n=6) (n=23) (n=22) (n=108) (n=68) AARs t-value AARs t-value AARs t-value AARs t-value AARs t-value AARs t-value ** * * ** *** ** * ** *** ** *** ** ** ** * ** ** a This table presents the average abnormal returns based on the content of rumors, surrounding the publication date t=0 intheekonomik Trend. Abnormal return is calculated as the difference between the actual and expected return. Expected return is generated from the market model parameters. The ISE Composite index used as a proxy for market. The t-statistics tests the null hypothesis that the average abnormal returns are equal to zero. Event day (0) represents the day of publication of rumors/gossips and corresponds to Sundays. *** Statistically significant at 1%. ** Statistically significant at 5%. * Statistically significant at 10%.

8 112 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) ( 5, +5) periods, CARs are 0.85, 1.19 and 1.35%, respectively. All of them are statistically significant at 1% level. In longer time periods firms experience negative insignificant abnormal returns. For example, during ( 20, +20) and ( 30, +30) periods, CARs are 0.28 and 1.22%, respectively. Based on these results, one would conclude that stock market rumors provide valuable information to investors. Trading based on rumors would provide statistically significant abnormal returns. I further analyze the behavior of stock prices in the period prior and after the publication of rumors. In the middle part of Table 3, the CARs in the pre-publication period for several windows are reported. The CARs in the pre-publication periods are positive and statistically significant. For example; during ( 20, 1), ( 10, 1) and ( 5, 1) periods, the CARs are 1.48, 1.82 and 2.16%, respectively. While the results of ( 20, 1) period is statistically significant at 5%, others are statistically significant at 1% level. The significant positive stock price reaction in the pre-publications days may be explained by two interpretations. The first one is related to the possible use of information by those who initially posses it. These may include insiders, who may use information for their trading, and stock analysts, who may supply information to their clients for trading. The second interpretation can be attributed to the nature of the HOTS column itself. Typically, the stocks mentioned in HOTS are those that recently have been performing well. This may be one of the reasons why almost all HOTS rumors/gossips are favorable. Finally, in the bottom part of Table 3, CARs in the after-publication period are analyzed. The CARs for (+1, +5), (+1, +10) and (+1, +20) windows are 0.81, 1.38 and 1.78%, respectively. None of these results is statistically significant. The negative gains in the after publication period would support the view that trading based on the rumors would not benefit to investors and information does not have any value. These results are contrary to those of recent US studies, which reports a positive price reaction after the publication date. The results of this study seem to suggest the possible dissemination of information prior to the publication date. To further analyze the differences in stock price reaction with respect to the contents of rumors, I classify gossips into six sub-groups. The results of AARs are reported on Table 4. When the pre-publication period is examined, earning expectations rumors, purchases by foreign in estor rumors, and unclassified rumors groups have positive significant abnormal returns. For example; earning expectations rumors group experiences abnormal returns of 0.65 and 0.67% on days 4 and 2. Both findings are statistically significant at 5% level. Unclassified rumors group shows the highest abnormal returns in pre- publication period. The AARs are 2.18, 1.96 and 0.83% for the days 1, 2, and 4, respectively. All of them are statistically significant at 1% level. The rest of the groups do not show any statistically significant specific patterns. In the period following the publication of rumors, the AARs are mostly negative and some of them are statistically significant. For example; earning expectations group has a return of 0.62% on day +4, which is statistically significant at 5% level. Similarly, purchases by foreign investors group experiences a return of 1.46% on the day +1.

9 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) Table 5 reports for CARs for three periods based on the subjects of rumors. In pre-publication period positive CARs are observed for earning expectations rumors, purchases by foreign in estors rumors, and unclassified rumors groups. For example; earning expectations rumors group experience CARs of 1.54% during ( 5, 1) windows, purchases by foreign in estors rumors and unclassified rumors groups have CARs of 2.48 and 4.94% in the same time period. While the first two results are statistically significant at 5% level, the last one is highly significant at 1% level. In the after publication period, all CARs are negative but none of them is statistically significant. For combined periods, only CARs for other topics are statistically significant. For example; CARs are 2.37, 3.99, 3.89% in the windows ( 1, +1), ( 2, +2) and ( 5, +5) respectively. The analysis of content of rumors reveals that there are differences in abnormal returns with respect to the content of stock market rumors. Clearly rumors related to earning expectations and purchases by foreign in estors have greatest impact on stock prices, while others have statistically insignificant effects. Overall, the empirical results indicate the existence of positive statistically significant abnormal returns in the pre-publication period of rumors. Such findings would refute the strong form of market efficiency, and are in line with the existing literature. The findings pertaining to the post-publication of rumors, on the other hand, show that there are statistically insignificant negative abnormal returns. This suggests that investment strategies based on the published rumors would not generate any wealth gains to investors, implying that information provided by column does not have any value at all. The results seem to suggest the possible dissemination of information prior to publication, and are contrary to those of US studies. 5. Summary and conclusions The question of whether the trading based on a particular set of information can lead investors to obtain abnormal returns continues to receive attention from researchers and investors. A vast majority of these studies on analysts recommendations and stock market rumors reports statistically significant stock price reaction to the publication of information and, hence, concludes that information has value. This study investigates the effects of stock market rumors/gossips on the prices of stocks traded at the ISE by using 355 favorable rumors mentioned on the HOTS column of ET. The empirical findings suggest that there are statistically significant abnormal returns around the publication date. While positive, significant abnormal returns are observed in each of the 4 days prior to the publication date, negative insignificant abnormal returns are detected in the post-publication period. The significant stock price reaction in pre-publications days may be interpreted in two ways. The first one is related to the possible use of information by either insider, who may use information for their trading, or stock analysts, who may supply information to their clients for trading. This interpretation suggests the dissemination of information prior to publication. The second interpretation can be at-

10 114 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) Table 5 Cumulative abnormal returns (CARs) based on the content of rumors a Earnings expectations Sales/export expectations Undervalued stocks Purchases by foreign investor Unclassified rumors Rumors without content (n=128) (n=6) (n=23) (n=22) (n=108) (n=68) CARs t-value CARs t-value CARs t-value CARs t-value CARs t-value CARs t-value Prior to publication ( 20, 1) *** ( 10, 1) * *** ( 5, 1) ** ** *** After publication (+1, +5) (+1, +10) (+1, +20) Combined periods ( 1, +1) *** ( 2, +2) *** ( 5, +5) *** ( 10, +10) *** ( 20, +20) ( 30, +30) a This table presents the cumulative abnormal returns based on the content of rumors in combined, pre, and post publication period relative to publication date t=0 intheekonomik Trend. Abnormal return is calculated as the difference between the actual and expected return. Expected return is generated from the market model parameters. The ISE Composite index used as a proxy for market. The t-statistics tests the null hypothesis that the cumulative abnormal returns are equal to zero. *** Statistically significant at 1%. ** Statistically significant at 5%. * Statistically significant at 10%.

11 H. Kiymaz / J. of Multi. Fin. Manag. 11 (2001) tributed to the nature of the HOTS column itself. Typically, the stocks mentioned in HOTS are those that recently have been performing well. The negative insignificant abnormal returns in the post-publication period may suggest that investment decisions based on the published rumors would not benefit investors. Hence, information provided by such columns may not have any value. A further analysis based on the content of rumors/gossips reveals that earning expectations rumors, purchases by foreign investor rumors generate higher abnormal returns than other rumors. Acknowledgements I thank the participants at the 1999 meeting of Financial Management Association International, the editor, and an anonymous referee for helpful suggestions on an earlier draft. References Barber, B.M., Loeffler, D., The dartboard column: second-hand information and price pressure. Journal of Financial and Quantitative Analysis 28, Beneish, M.D., Stock prices and the dissemination of analysts recommendations. Journal of Business 64, Brown, S.J., Warner, J.B., Using daily stock returns: the case of event studies. Journal of Financial Economics 14, Diefenback, R., How good is institutional brokerage research. Financial Analyst Journal 28, Huth, W.L., Maris, B.A., Large and small firm stock price responses to heard on the street recommendations. Journal of Accounting and Auditing 7, Liu, P., Smith, D., Syed, A., Stock reaction to the Wall Street Journal s securities recommendations. Journal of Financial and Quantitative Analysis 25, Lloyd-Davies, P., Canes, M., Stock prices and publication of second-hand information. Journal of Business 51, Logue, D., Tuttle, D., Brokerage houses investment advises. The Financial Review 8, Mathur, I., Waheed, A., Stock price reactions to securities recommended in Business Week s inside Wall Street. The Financial Review 30, Syed, A., Lui, P., Smith, S., The exploitation of inside information at the Wall Street Journal: a test of strong form efficiency. The Financial Review 24,

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