THE ROLE OF THE MEDIA IN THE INTERNET IPO BUBBLEN Utpal Bhattacharya Kelley School of Business Indiana University bhattac@indiana. ed Neal galpin Kelley School of Business Indiana University galpin @indiana. edu Rina ray Kelley school of Business Indiana university riray@@indiana. edu Yu Carlson School of Management University of Minnesota yu(@csom. umn. edu ber15.2005 Key words: initial public offerings, media, internet bubble EL number: E32G14 G30 s We are grateful fo gestions from Laura Field, Murray Frank and seminar participants at Penn State Unive management University, University of New Orleans and at the followin conferences: European Finance Association Annual Meeting 2005 and China International Finance Conference 2005. All mistakes remain our own responsibility
THE ROLE OF THE MEDIA IN THE INTERNET IPO BUBBLE* Utpal Bhattacharya Kelley School of Business Indiana University ubhattac@indiana.edu Neal Galpin Kelley School of Business Indiana University ngalpin@indiana.edu Rina Ray Kelley School of Business Indiana University riray@indiana.edu Xiaoyun Yu Carlson School of Management University of Minnesota xyu@csom.umn.edu September 15, 2005 Key words: initial public offerings, media, internet bubble JEL number: E32, G14, G30 * We are grateful for suggestions from Laura Field, Murray Frank and seminar participants at Penn State University, Singapore Management University, University of New Orleans and at the following conferences: European Finance Association Annual Meeting 2005 and China International Finance Conference 2005. All mistakes remain our own responsibility
THE ROLE OF THE MEDIA IN THE INTERNET IPO BUBBLE Abstract The first part of this paper explores whether aggregate media coverage was different for internet IPOs as opposed to a matching sample of non-internet IPOs in the late 1990s. So we read all news items that came out between 1996 through 2000 on 458 internet IPOs and a matching sample of 458 non-internet IPOs-a total of 171, 488 news items-and classify each news item as good news, neutral news or bad news. We find, not surprisingly, that the overall media coverage was more intense for internet IPOs. Further. we document that the overall media coverage was much more positive for internet IPOs in the period of dramatic rise in share prices and was mucl more negative for internet IPOs in the period of dramatic fall in share prices. The second part of the paper explores whether this differential media coverage had any effect on the difference in risk-adjusted returns between internet stocks and non-internet stocks. We find, surprisingly, that the answer is no the market somewhat discounted the media sentiment -though net news (number of good news minus number of bad news) Granger caused risk-adjusted returns for both samples of IPOs, the effect was lower for internet IPOs, especially in the bubble period. So our conclusion is that the media was not a significant factor in the dramatic rise and fall of internet shares in the late 1990s
THE ROLE OF THE MEDIA IN THE INTERNET IPO BUBBLE Abstract The first part of this paper explores whether aggregate media coverage was different for internet IPOs as opposed to a matching sample of non-internet IPOs in the late 1990s. So we read all news items that came out between 1996 through 2000 on 458 internet IPOs and a matching sample of 458 non-internet IPOs – a total of 171,488 news items – and classify each news item as good news, neutral news or bad news. We find, not surprisingly, that the overall media coverage was more intense for internet IPOs. Further, we document that the overall media coverage was much more positive for internet IPOs in the period of dramatic rise in share prices and was much more negative for internet IPOs in the period of dramatic fall in share prices. The second part of the paper explores whether this differential media coverage had any effect on the difference in risk-adjusted returns between internet stocks and non-internet stocks. We find, surprisingly, that the answer is no: the market somewhat discounted the media sentiment – though net news (number of good news minus number of bad news) Granger caused risk-adjusted returns for both samples of IPOs, the effect was lower for internet IPOs, especially in the bubble period. So our conclusion is that the media was not a significant factor in the dramatic rise and fall of internet shares in the late 1990s
THE ROLE OF THE MEDIA IN THE INTERNET IPO BUBBLE L INTRODUCTION The offer price of eToys'initial public offering(IPO)on May 20, 1999 was $20. It shot up to $76.5625 at the end of the first trading day. Later, in a special report, Wall Street Journal's technology editor Jason Fry noticed that "driving the company's success is a cleanly designed, easy-to-use site designed to soothe adults rattled by the pitfall of toy shopping in the real world". He wrote: ". for many an overeager Web outfit, they [eToys] have proved hard to duplicate. The company is fanatical about providing top-rate customer service, including actual human beings who answer the telephone. It didnt open for business until founder and Chief Executive Officer Toby Lenk believed he understood the toy industry and how it should work online. And eToys is dedicated to moving at Web speed. It has stayed ahead of its deep-pocketed competitors by constantly transforming itself, for example, by diversifying its inventory to include books, music, videos and baby products. "By the end of 2000, the firm traded at 0. 1875 per share, which was 0. 24% of its first day closing price, and 0.94%of its offer price. Today, eToys does not trade. The company went bankrupt and its stock was de-listed from Nasdaq on February 26, 2001 In this paper, we use the phrase "bubble/post-bubble "to reflect the dramatic rise and dramatic fall of stock prices in the period of 1996-2000. We ask and answer the following two questions: was the overall media coverage for internet IPOs in the years 1996 through 2000 different from a matching sample of non-internet IPOs and, if yes, did this difference in the media coverage have any effect on the difference in risk-adjusted returns between internet stocks and non-internet stocks There are many reasons for believing that the media coverage and/or its effect were more pronounced for internet IPOs than for non-internet IPOs in the late 1990s. First, the media were more In this paper we look at stock returns after the first day of trading. In a companion paper, we look at stock returns at the first day of trading. The reason we separated our analysis is because the information dissemination during the pre IPO book-building stage is very different from the information dissemination during the post-IPO stage. In the pre IPO stage, institutions disseminate information and, therefore, the natures of these institutions are the significant control variables. A rich literature exists on what affects the first days return. In the post-IPO stage, on the other hand, the main source of information is the traded price itself. This, therefore, becomes the paramount control variable in this paper
1 THE ROLE OF THE MEDIA IN THE INTERNET IPO BUBBLE I. INTRODUCTION The offer price of eToys’ initial public offering (IPO) on May 20, 1999 was $20. It shot up to $76.5625 at the end of the first trading day. Later, in a special report, Wall Street Journal’s technology editor Jason Fry noticed that “driving the company’s success is a cleanly designed, easy-to-use site designed to soothe adults rattled by the pitfall of toy shopping in the real world”. He wrote: “…for many an overeager Web outfit, they [eToys] have proved hard to duplicate. The company is fanatical about providing top-rate customer service, including actual human beings who answer the telephone. It didn’t open for business until founder and Chief Executive Officer Toby Lenk believed he understood the toy industry and how it should work online. And eToys is dedicated to moving at Web speed. It has stayed ahead of its deep-pocketed competitors by constantly transforming itself, for example, by diversifying its inventory to include books, music, videos and baby products.” By the end of 2000, the firm traded at $ 0.1875 per share, which was 0.24% of its first day closing price, and 0.94% of its offer price. Today, eToys does not trade. The company went bankrupt and its stock was de-listed from Nasdaq on February 26, 2001. In this paper, we use the phrase “bubble/post-bubble” to reflect the dramatic rise and dramatic fall of stock prices in the period of 1996-2000. We ask and answer the following two questions: was the overall media coverage for internet IPOs in the years 1996 through 2000 different from a matching sample of non-internet IPOs and, if yes, did this difference in the media coverage have any effect on the difference in risk-adjusted returns between internet stocks and non-internet stocks.1 There are many reasons for believing that the media coverage and/or its effect were more pronounced for internet IPOs than for non-internet IPOs in the late 1990s. First, the media were more 1 In this paper we look at stock returns after the first day of trading. In a companion paper, we look at stock returns at the first day of trading. The reason we separated our analysis is because the information dissemination during the preIPO book-building stage is very different from the information dissemination during the post-IPO stage. In the preIPO stage, institutions disseminate information and, therefore, the natures of these institutions are the significant control variables. A rich literature exists on what affects the first day’s return. In the post-IPO stage, on the other hand, the main source of information is the traded price itself. This, therefore, becomes the paramount control variable in this paper
likely to be interested in internet IPOs, because in this period there were so many of them, and many of them had dramatic first-day returns(Benveniste, Ljungqvist, Wilhelm and Yu 2003, Ljungqvist and Wilhelm 2003 and Ritter and Welch 2003). Second, as the internet industry was new, there was no history of cash flows of comparable firms that had gone public. This made valuations difficult, and so expectations of future cash flows for internet IPOs were more likely to be sensitive to media news(Blanchard and Watson 1982, Hirota and Sunder 2002 provide experimental evidence. )Third, the limits to arbitrage were more binding for internet IPOs during the period of 1996-2000(Lamont and Thaler 2003 and Ofek and Richardson 2003), so the divergence of stock prices from their fundamental value was likely to be greater for internet IPOs. Further, institutional investors did not attempt to trade against market movements, but actively rode with both the run-up and run-down of the stock( Griffin, Harris and Topaloglu 2003 and Brunnermeier and Nagel 2004). Fourth, and finally, there is now increasing evidence that the spectacular rise and spectacular fall of internet IPOs in the late 1990s can not be reconciled with fundamentals( Cooper, Dimitrov and Rau 2001, Ofek and Richardson 2002, Loughran and Ritter 2004). A good place to begin looking for other explanations is to formally explore the economic role of the media in this period Was the overall media coverage different for internet IPOs? We read all news items that came out between 1996 through 2000 on 458 internet IPOs and a matching sample of 458 non-internet IPOs -a total of 171, 488 news items- and classify each news item as good news, neutral news or bad news. We find not surprisingly, that the media coverage was more intense for internet IPOs. All types of news-good bad, or neutral - were more for internet IPOs than for non-internet IPOs in both the bubble period and the post-bubble period. Second, we use net news(good news minus bad news) to proxy media sentiment. We find that compared to the matching sample, the net news was more positive for internet IPOs in the bubble 2 Cutler, Poterba and Summers(1989) is one of the early papers that show stock return variances cannot be caused by fundamental news such as macroeconomic news s Shiller(2000) believes that the stock price increases in the late 1990s were driven by irrational euphoria among individual investors, fed by an emphatic media, which maximized TV ratings and catered to investor demand for pseudo-news. Professional investors"are not immune from the effects of the popular investing culture that we observe in individual investors'(p. 18) 4 The issue whether media sentiment reflects public sentiment or is different from public sentiment-though nteresting in its own right, is beyond the scope of this paper
2 likely to be interested in internet IPOs, because in this period there were so many of them, and many of them had dramatic first-day returns (Benveniste, Ljungqvist, Wilhelm and Yu 2003, Ljungqvist and Wilhelm 2003 and Ritter and Welch 2003). Second, as the internet industry was new, there was no history of cash flows of comparable firms that had gone public. This made valuations difficult, and so expectations of future cash flows for internet IPOs were more likely to be sensitive to media news (Blanchard and Watson 1982; Hirota and Sunder 2002 provide experimental evidence.) Third, the limits to arbitrage were more binding for internet IPOs during the period of 1996-2000 (Lamont and Thaler 2003 and Ofek and Richardson 2003), so the divergence of stock prices from their fundamental value was likely to be greater for internet IPOs. Further, institutional investors did not attempt to trade against market movements, but actively rode with both the run-up and run-down of the stock (Griffin, Harris and Topaloglu 2003 and Brunnermeier and Nagel 2004). Fourth, and finally, there is now increasing evidence that the spectacular rise and spectacular fall of internet IPOs in the late 1990s can not be reconciled with fundamentals (Cooper, Dimitrov and Rau 2001, Ofek and Richardson 2002, Loughran and Ritter 2004).2 A good place to begin looking for other explanations is to formally explore the economic role of the media in this period.3 Was the overall media coverage different for internet IPOs? We read all news items that came out between 1996 through 2000 on 458 internet IPOs and a matching sample of 458 non-internet IPOs – a total of 171,488 news items – and classify each news item as good news, neutral news or bad news. We find, not surprisingly, that the media coverage was more intense for internet IPOs. All types of news – good, bad, or neutral – were more for internet IPOs than for non-internet IPOs in both the bubble period and the post-bubble period. Second, we use net news (good news minus bad news) to proxy media sentiment.4 We find that compared to the matching sample, the net news was more positive for internet IPOs in the bubble 2 Cutler, Poterba and Summers (1989) is one of the early papers that show stock return variances cannot be caused by fundamental news such as macroeconomic news. 3 Shiller (2000) believes that the stock price increases in the late 1990s were driven by irrational euphoria among individual investors, fed by an emphatic media, which maximized TV ratings and catered to investor demand for pseudo-news. Professional investors “are not immune from the effects of the popular investing culture that we observe in individual investors” (p.18). 4 The issue – whether media sentiment reflects public sentiment or is different from public sentiment – though interesting in its own right, is beyond the scope of this paper
period, and more negative for internet IPOs in the post-bubble period. Third, we document that net news increased after a positive stock return, and decreased after a negative stock return for internet firms. This provides some evidence in favor of Shiller's(2000) positive feedback hypothesis. Interestingly, the positive feedback was asymmetric. During the bubble period, net news increases regardless of whether the previous stock return is positive or negative. However, during this bubble period, the increase after a positive stock return was larger for internet IPOs than for non-internet IPOs. These findings reverse in the post-bubble period. In the post-bubble period, net news decreases regardless of whether the previous stock return is positive or negative, however, the decrease in net news after a negative stock return was larger for internet IPOs than for non-internet IPOs. Our results are robust to whether we follow the traditional definition of the bubble in calendar time( the period that ended March 24, 2000)or in event time(the firm- specific period that ended on the day the firms stock price peaked). We, therefore, draw the following conclusion about media coverage of IPOs in the late 1990s: it seems that the overall media coverage was more positive about internet IPOs in the bubble period and more negative about internet IPOs in the post bubble period Did the differential media coverage have any effect on the difference in risk-adjusted returns between internet stocks and non-internet stocks during this period? We check whether news in the media, measured by numbers and type, Granger caused abnormal returns, where abnormal returns is the error term of a Fama-French(1993)three factor model. We incorporate the previous periods abnormal returns as a control when we examined the effect of the media in our analysis. This buys us a few advantages. First, and most important, it corrects for feedback effects: does the media affect returns or do returns affect the media. Both are possible. As a matter of fact, our analysis on aggregate media coverage showed that the latter effect exists. Second, it corrects for possible momentum or reversal in daily stock returns. Third, as the last period's abnormal return contains the cumulative effect of past media reports, it corrects for the possibility that the media effect lasts longer than a day. Finally, because lagged return occurs on the same day as the news reports used for tests, lagged return controls for contemporaneous relationships between stock prices and news coverage. We also control for firm-fixed effects to mitigate the variations in news
3 period, and more negative for internet IPOs in the post-bubble period. Third, we document that net news increased after a positive stock return, and decreased after a negative stock return for internet firms. This provides some evidence in favor of Shiller’s (2000) positive feedback hypothesis. Interestingly, the positive feedback was asymmetric. During the bubble period, net news increases regardless of whether the previous stock return is positive or negative. However, during this bubble period, the increase after a positive stock return was larger for internet IPOs than for non-internet IPOs. These findings reverse in the post-bubble period. In the post-bubble period, net news decreases regardless of whether the previous stock return is positive or negative; however, the decrease in net news after a negative stock return was larger for internet IPOs than for non-internet IPOs. Our results are robust to whether we follow the traditional definition of the bubble in calendar time (the period that ended March 24, 2000) or in event time (the firmspecific period that ended on the day the firm’s stock price peaked). We, therefore, draw the following conclusion about media coverage of IPOs in the late 1990s: it seems that the overall media coverage was more positive about internet IPOs in the bubble period and more negative about internet IPOs in the postbubble period. Did the differential media coverage have any effect on the difference in risk-adjusted returns between internet stocks and non-internet stocks during this period? We check whether news in the media, measured by numbers and type, Granger caused abnormal returns, where abnormal returns is the error term of a Fama-French (1993) three factor model. We incorporate the previous period’s abnormal returns as a control when we examined the effect of the media in our analysis. This buys us a few advantages. First, and most important, it corrects for feedback effects: does the media affect returns or do returns affect the media. Both are possible. As a matter of fact, our analysis on aggregate media coverage showed that the latter effect exists. Second, it corrects for possible momentum or reversal in daily stock returns. Third, as the last period’s abnormal return contains the cumulative effect of past media reports, it corrects for the possibility that the media effect lasts longer than a day. Finally, because lagged return occurs on the same day as the news reports used for tests, lagged return controls for contemporaneous relationships between stock prices and news coverage. We also control for firm-fixed effects to mitigate the variations in news
overage related to the specific nature of the firm and to remove the author bias effect from news classification, if we assume this effect is firm-specific After controlling for previous abnormal returns, firm fixed effects, market trading conditions and news volumes, we find, not surprisingly, that good news increases risk-adjusted returns the next period, and bad news decreases risk-adjusted returns the next period, and so net news(good news minus bad news increases risk-adjusted returns the next period. We find, surprisingly, that the effect of net news on next period's risk-adjusted return was lower for internet IPOs, especially during the bubble period. In addition, during the post-bubble period the effect of good news matters more on next period's risk-adjusted return for internet IPOs than for non-internet IPOs. Our results are robust to whether we risk-adjust individual stocks, or whether we risk-adjust a portfolio consisting of either internet or non-internet stocks. We therefore, draw the following conclusion: though the media coverage was much more positive about internet IPOs in the bubble period and was much more negative about internet IPOs in the post-bubble period, the market somewhat discounted the media sentiment, especially during the bubble period Although there could be many other rational or irrational factors that contributed to the dramatic rise and fall of the stock market in the period 1996 through 2000, our results suggest that media sentiment, bein discounted by the market, was not a major determinant of the bubble and its crash Our paper is organized as follows. In Section II, we discuss the related literature on media and its relation with changes in stock prices. Section Ill discusses how we obtained our data. Section IV gives our results on differential media coverage of internet IPOs as opposed to a matching sample of non-internet IPOs. Section V answers whether the differential media coverage affected the difference in risk-adjusted returns between the two samples. Section VI covers various tests for robustness that we conducted Though we are tempted, we want to be cautious to draw definitive conclusions about market efficiency from our findings. This is because of the following reason. Differences in net media news(good news minus bad news) will positively affect differences in net returns between internet firms and non-internet firms if media news reflect fundamentals and the market is efficient with respect to media coverage(i.e. only media news about fundamentals moves prices), or, if media news reflect sentiment and the market is inefficient with respect to media coverage (i.e only media news about sentiment prices). On the other hand, differences in net media news will not affect differences in net returns between internet firms and non-internet firms if media news reflect sentiment and the market is efficient with respect to media news, or, if media news reflect fundamentals and the market is inefficient with respect to media ne
4 coverage related to the specific nature of the firm and to remove the author bias effect from news classification, if we assume this effect is firm-specific. After controlling for previous abnormal returns, firm fixed effects, market trading conditions and news volumes, we find, not surprisingly, that good news increases risk-adjusted returns the next period, and bad news decreases risk-adjusted returns the next period, and so net news (good news minus bad news) increases risk-adjusted returns the next period. We find, surprisingly, that the effect of net news on next period’s risk-adjusted return was lower for internet IPOs, especially during the bubble period. In addition, during the post-bubble period, the effect of good news matters more on next period’s risk-adjusted return for internet IPOs than for non-internet IPOs. Our results are robust to whether we risk-adjust individual stocks, or whether we risk-adjust a portfolio consisting of either internet or non-internet stocks. We, therefore, draw the following conclusion: though the media coverage was much more positive about internet IPOs in the bubble period and was much more negative about internet IPOs in the post-bubble period, the market somewhat discounted the media sentiment, especially during the bubble period. Although there could be many other rational or irrational factors that contributed to the dramatic rise and fall of the stock market in the period 1996 through 2000, our results suggest that media sentiment, being discounted by the market, was not a major determinant of the bubble and its crash.5 Our paper is organized as follows. In Section II, we discuss the related literature on media and its relation with changes in stock prices. Section III discusses how we obtained our data. Section IV gives our results on differential media coverage of internet IPOs as opposed to a matching sample of non-internet IPOs. Section V answers whether the differential media coverage affected the difference in risk-adjusted returns between the two samples. Section VI covers various tests for robustness that we conducted, 5 Though we are tempted, we want to be cautious to draw definitive conclusions about market efficiency from our findings. This is because of the following reason. Differences in net media news (good news minus bad news) will positively affect differences in net returns between internet firms and non-internet firms if media news reflect fundamentals and the market is efficient with respect to media coverage (i.e. only media news about fundamentals moves prices), or, if media news reflect sentiment and the market is inefficient with respect to media coverage (i.e. only media news about sentiment moves prices). On the other hand, differences in net media news will not affect differences in net returns between internet firms and non-internet firms if media news reflect sentiment and the market is efficient with respect to media news, or, if media news reflect fundamentals and the market is inefficient with respect to media news
including an experiment to check the validity of our technique of classifying news. We conclude in Section THE RELATED LITERATURE The first question of this paper-was the overall media coverage for internet IPOs different from the overall media coverage of non-internet IPOs-belongs to a growing literature on bias in the financial media. How do the financial media choose which stories to cover? Of the stories they choose to cover what is the slant given? And why is there a slant? Shiller(2000)writes: The role of the news media in the stock market is not, as commonly believed, simply as a convenient tool for investors who are reacting directly to the economically significant news itself. The media actively shape public attention and categories of thought, and they create the environment within which the stock market events we see are played out. He believes that the financial media strive to enhance interest by attaching news stories to stock price movements that the public has already observed, thereby creating a positive feedback effect Dyck and Zingales(2003a) note that there is a pro-company bias in the financial media, which is stronger during a boom, and is weaker and is sometimes reversed during a bust. They argue that this is because of incentives. Reporting good news during booms allows media access to the company, but this access is not important during busts because the company does not want to share news. Dyck and Zingales(2003b) find empirical support in that media spin affects the stock market response to earnings announcements Mullainathan and shleifer(2003)demonstrate that the media can slant the presentation of the news to cater to the preferences of their audience. Baron(2004)explains why persistent media bias can exist in competitive equilibrium; in his hypothesis, bias originates with journalists who have a preference for influence and are willing to sacrifice wages to exercise it Our second research question - did the differential media coverage have any effect on the difference in risk-adjusted returns between the two samples- extends from a large literature on how media news affects returns. According to classical asset pricing models, news will affect returns if it affects expectations of future cash flows and/or expectations of the discount rate. By filtering, aggregating and
5 including an experiment to check the validity of our technique of classifying news. We conclude in Section VII. II. THE RELATED LITERATURE The first question of this paper – was the overall media coverage for internet IPOs different from the overall media coverage of non-internet IPOs – belongs to a growing literature on bias in the financial media. How do the financial media choose which stories to cover? Of the stories they choose to cover, what is the slant given? And why is there a slant? Shiller (2000) writes: “The role of the news media in the stock market is not, as commonly believed, simply as a convenient tool for investors who are reacting directly to the economically significant news itself. The media actively shape public attention and categories of thought, and they create the environment within which the stock market events we see are played out.” He believes that the financial media strive to enhance interest by attaching news stories to stock price movements that the public has already observed, thereby creating a positive feedback effect. Dyck and Zingales (2003a) note that there is a pro-company bias in the financial media, which is stronger during a boom, and is weaker and is sometimes reversed during a bust. They argue that this is because of incentives. Reporting good news during booms allows media access to the company, but this access is not important during busts because the company does not want to share news. Dyck and Zingales (2003b) find empirical support in that media spin affects the stock market response to earnings announcements. Mullainathan and Shleifer (2003) demonstrate that the media can slant the presentation of the news to cater to the preferences of their audience. Baron (2004) explains why persistent media bias can exist in a competitive equilibrium; in his hypothesis, bias originates with journalists who have a preference for influence and are willing to sacrifice wages to exercise it. Our second research question – did the differential media coverage have any effect on the difference in risk-adjusted returns between the two samples – extends from a large literature on how media news affects returns. According to classical asset pricing models, news will affect returns if it affects expectations of future cash flows and/or expectations of the discount rate. By filtering, aggregating and
repackaging information into news items, the media reduce the cost of collecting and certifying relevant information, and therefore can have significant impact on financial markets. In an early paper, Niederhoffer(1971)observes large price movements following world event headlines; the market appears to overreact to bad news. Mitchell and Mulherin(1994)document a weak relationship between the amount of publicly reported information, approximated by the number of daily dow Jones news stories, and the aggregate trading activity and the price movements in securities markets. Antweiler and frank(2004a)find statistically significant return momentum for many days after the news is made public and a bigger and more prolonged impact of average news on returns during a recession than during an expansion. Chan (2003)shows stocks with large price movements, but no identifiable news, show reversal in the next month and prices are slow to reflect bad public news Alternatively, Merton(1987)argued that investors will buy and hold only those securities which they are aware of. The most common way to facilitate investors' awareness is to promote the visibility of the firm through media. Falkenstein(1996) documents that mutual funds avoid stocks with low media exposure. Barber and Odean(2003)provide direct evidence that individual investors tend to buy stocks that are in the news. Antweiler and Frank(2004b) and Wysocki (1999) find that the volume of stock messages posted on internet stock message boards predicts subsequent stock returns and market volatility Tetlock(2003) provides evidence that media coverage affects market index returns and aggregate trading volume. Huberman and Regev(2001)document that old news repackaged as new news can also affect returns. Antunovich and Sarkar(2003) find that stocks with higher media exposure have bigger liquidity gains and lower excess returns on the pick day. Chen, Noronha, and Singal(2002) show that media exposure increases following additions to the s&P 500 index, and price changes around S&P 500 index additions are consistent with greater investor awareness of the added stocks A literature focusing on the relation between media and IPO firms has already started to emerge Examining the post-offer performance of a sample of IPOs, Loughran and Marietta-Westberg(2002) find that investors over-react to positive-return news events and under-react to negative news events. Johnson and Marietta-Westberg(2004) show that the increase in idiosyncratic volatility for IPO firms over time is
6 repackaging information into news items, the media reduce the cost of collecting and certifying relevant information, and therefore can have significant impact on financial markets. In an early paper, Niederhoffer (1971) observes large price movements following world event headlines; the market appears to overreact to bad news. Mitchell and Mulherin (1994) document a weak relationship between the amount of publicly reported information, approximated by the number of daily Dow Jones news stories, and the aggregate trading activity and the price movements in securities markets. Antweiler and Frank (2004a) find statistically significant return momentum for many days after the news is made public and a bigger and more prolonged impact of average news on returns during a recession than during an expansion. Chan (2003) shows stocks with large price movements, but no identifiable news, show reversal in the next month, and prices are slow to reflect bad public news. Alternatively, Merton (1987) argued that investors will buy and hold only those securities which they are aware of. The most common way to facilitate investors’ awareness is to promote the visibility of the firm through media. Falkenstein (1996) documents that mutual funds avoid stocks with low media exposure. Barber and Odean (2003) provide direct evidence that individual investors tend to buy stocks that are in the news. Antweiler and Frank (2004b) and Wysocki (1999) find that the volume of stock messages posted on internet stock message boards predicts subsequent stock returns and market volatility. Tetlock (2003) provides evidence that media coverage affects market index returns and aggregate trading volume. Huberman and Regev (2001) document that old news repackaged as new news can also affect returns. Antunovich and Sarkar (2003) find that stocks with higher media exposure have bigger liquidity gains and lower excess returns on the pick day. Chen, Noronha, and Singal (2002) show that media exposure increases following additions to the S&P 500 index, and price changes around S&P 500 index additions are consistent with greater investor awareness of the added stocks. A literature focusing on the relation between media and IPO firms has already started to emerge. Examining the post-offer performance of a sample of IPOs, Loughran and Marietta-Westberg (2002) find that investors over-react to positive-return news events and under-react to negative news events. Johnson and Marietta-Westberg (2004) show that the increase in idiosyncratic volatility for IPO firms over time is
Granger-caused by the increase in news in recent decades. The extent of pre-IPO media exposure is found to be positively related to IPO underpricing both in US (Reese 1998 and Ducharme, Rajgopal and Sefcik 2001a)and in other countries(Ho, Taher, Lee and Fargher 2001). The pre-IPO media hype is related to the IPO's short-term and long-term volume (Reese 1998)and to their post-offer return performances (Ducharme, Rajgopal and Sefcik 2001b). Initial return is shown to have a positive influence on the subsequent media coverage(Demers and Lewellen 2003), suggesting IPO underpricing publicizes stocks to investors who buy the stock in the after-market. Our paper differs from this literature in that we do not focus on what drives the media coverage of IPO firms. Nor do we focus on the pre-lPO stage or on the first day's return. Instead, we take the bubble period as given and follow IPOs over their rise and fall in the period 1996 through 2000. Second, unlike most of the above papers, we look at both the numbers of news items and their type(good, bad or neutral) from all media sources to capture the aggregate media effect IIL DAtA A. The IPO sample We start with a large sample of firms that went public between January 1996 and December 2000 After excluding unit offers. rights offers. closed-end mutual funds REITs and ADRs. our search of the Thomson Financial's SDC database yielded 2, 603 completed issues We identify and extract 461 internet companies from this sample using the reference list from Loughran and Ritter(2004 ). We cross-check our internet IPO issues with Loughran and Ritter(2002)and Ljungqvist and wilhelm(2003)to correct errors in the Sdc data. We remove one issue that went publ twice and was, therefore, counted twice during our sample period. That leaves us with 459 internet IPOs For the remaining 2, 142 issues in this SDC sample, we first manually check for misclassification, and exclude 9 issues which are in fact ADRs, I belonging to unit trusts, 2 misclassified as IPOs, 2 without filing, offer or trading price information in SEC, news sources and CRSP, and I foreign offer with a minor tranche in the US. Then we extract a matching set of non-internet iPos from the rest of the 2. 127 issues based on offer size and offer date as follows: for each of the internet IPOs, we impose a 20% band on its
7 Granger-caused by the increase in news in recent decades. The extent of pre-IPO media exposure is found to be positively related to IPO underpricing both in US (Reese 1998 and Ducharme, Rajgopal and Sefcik 2001a) and in other countries (Ho, Taher, Lee and Fargher 2001). The pre-IPO media hype is related to the IPO’s short-term and long-term volume (Reese 1998) and to their post-offer return performances (Ducharme, Rajgopal and Sefcik 2001b). Initial return is shown to have a positive influence on the subsequent media coverage (Demers and Lewellen 2003), suggesting IPO underpricing publicizes stocks to investors who buy the stock in the after-market. Our paper differs from this literature in that we do not focus on what drives the media coverage of IPO firms. Nor do we focus on the pre-IPO stage or on the first day’s return. Instead, we take the bubble period as given and follow IPOs over their rise and fall in the period 1996 through 2000. Second, unlike most of the above papers, we look at both the numbers of news items and their type (good, bad or neutral) from all media sources to capture the aggregate media effect. III. DATA A. The IPO sample We start with a large sample of firms that went public between January 1996 and December 2000. After excluding unit offers, rights offers, closed-end mutual funds, REITs, and ADRs, our search of the Thomson Financial’s SDC database yielded 2,603 completed issues. We identify and extract 461 internet companies from this sample using the reference list from Loughran and Ritter (2004). We cross-check our internet IPO issues with Loughran and Ritter (2002) and Ljungqvist and Wilhelm (2003) to correct errors in the SDC data. We remove one issue that went public twice and was, therefore, counted twice during our sample period. That leaves us with 459 internet IPOs. For the remaining 2,142 issues in this SDC sample, we first manually check for misclassification, and exclude 9 issues which are in fact ADRs, 1 belonging to unit trusts, 2 misclassified as IPOs, 2 without filing, offer or trading price information in SEC, news sources and CRSP, and 1 foreign offer with a minor tranche in the US. Then, we extract a matching set of non-internet IPOs from the rest of the 2,127 issues based on offer size and offer date as follows: for each of the internet IPOs, we impose a 20% band on its
offer size and choose the matching firm with the closest offer date among candidates. matches are formed without replacement. So we have a matching sample of 459 non-internet IPOs Since we study the effect of media on returns of Ipo firms during the boom and bust of the internet bubble period, we expect each of our sample firms to have some degree of news coverage. There is one irm in our non-internet sample where we cannot identify any news report from Factiva using various combination of search. We therefore removed this firm from our analysis. Excluding or including this firm in our sample does not change our results. Our final sample contains 458 internet IPOs and a matching 458 on-internet IPOs Offer characteristics such as offer size, venture-capital backing, and the stock exchange in which the IPO first traded, are from SDC. Stock prices and daily returns are from CRSP. Fama-French factors are obtained from Frenchs website. We manually collect missing founding date for 193 issues within the non- internet sample and 222 issues within the internet sample from SEC filing prospectuses, subsequent 10-Ks, or news sources B The news sample We define the media to be the Dow Jones Interactive Publications Library (DJI)of past newspapers periodicals, and newswires. After DJI's conversion to Factiva in June, 2003, we create a customized list that includes major news and business publication sources worldwide. This list is consistent with the news sources in DJI prior to its conversion. We choose dow Jones Interactive and Factiva because they provide by far the most complete sources of media coverage across time and stocks. As pointed out by Chan (2003), this source does not suffer from gaps in coverage, and is the best approximation of public news for general investors. We do not include magazines, since it is difficult for us to pin down precisely when the information is publicly available. We also exclude investment newsletters, analyst reports and other sources We use the matched firms in two ways. For the main analysis, we ignore the individual matches, drawing conclusions based only on whether internet firms differ from non-internet firms. For robustness( see Section VI, C2), we consider the individual matches directly, drawing conclusions based on whether internet firms differ from their particular match /The resulting list of data sources includes Dow Jones Asia, Europe, Africa, North America, South America Australia and New Zealand and contains all the English language sources of daily news 8
8 offer size, and choose the matching firm with the closest offer date among candidates. Matches are formed without replacement.6 So we have a matching sample of 459 non-internet IPOs. Since we study the effect of media on returns of IPO firms during the boom and bust of the internet bubble period, we expect each of our sample firms to have some degree of news coverage. There is one firm in our non-internet sample where we cannot identify any news report from Factiva using various combination of search. We therefore removed this firm from our analysis. Excluding or including this firm in our sample does not change our results. Our final sample contains 458 internet IPOs and a matching 458 non-internet IPOs. Offer characteristics such as offer size, venture-capital backing, and the stock exchange in which the IPO first traded, are from SDC. Stock prices and daily returns are from CRSP. Fama-French factors are obtained from French’s website. We manually collect missing founding date for 193 issues within the noninternet sample and 222 issues within the internet sample from SEC filing prospectuses, subsequent 10-Ks, or news sources. B. The news sample We define the media to be the Dow Jones Interactive Publications Library (DJI) of past newspapers, periodicals, and newswires. After DJI’s conversion to Factiva in June, 2003, we create a customized list that includes major news and business publication sources worldwide.7 This list is consistent with the news sources in DJI prior to its conversion. We choose Dow Jones Interactive and Factiva because they provide by far the most complete sources of media coverage across time and stocks. As pointed out by Chan (2003), this source does not suffer from gaps in coverage, and is the best approximation of public news for general investors. We do not include magazines, since it is difficult for us to pin down precisely when the information is publicly available. We also exclude investment newsletters, analyst reports and other sources 6 We use the matched firms in two ways. For the main analysis, we ignore the individual matches, drawing conclusions based only on whether internet firms differ from non-internet firms. For robustness (see Section VI, C2), we consider the individual matches directly, drawing conclusions based on whether internet firms differ from their particular match. 7 The resulting list of data sources includes Dow Jones Asia, Europe, Africa, North America, South America, Australia and New Zealand and contains all the English language sources of daily news