The First Analyst Coverage of Neglected Stocks

The First Analyst Coverage of Neglected Stocks Cem Demiroglu and Michael Ryngaert We examine the first analyst coverage of 549 neglected stocks that publicly traded at least one year without research coverage. The stocks experience a +4.86% abnormal return at initiation announcement. Positive returns are driven by positive coverage and not the mere introduction of coverage. Initiations from investment banks elicit lower announcement returns if the bank had a prior business relationship with the covered firm. Research firms paid by the covered company to provide coverage elicit announcement returns that are not significantly different from other analysts. Announcement returns are also influenced by liquidity increases and factors consistent with downward-sloping demand curves. In a press release dated July 7, 2005, Bob Greifeld, president and CEO of NASDAQ, noted that 35% of all publicly traded US firms had no analyst coverage. Additionally, he cited estimates by Reuters that from January 2002 to June 2005, 691 publicly traded US companies had lost all analysts coverage. Almost all of these companies had market capitalizations under $1 billion. Greifeld also noted...a lack of research coverage impacts company valuation, liquidity, and ultimately the welfare and growth of public companies. 1 In this paper, we examine the stock price impact of 549 analyst coverage initiations during the period 1997-2005 for firms that had been publicly traded without analyst coverage for at least one year. We demonstrate that analyst initiations are important information events. Specifically, we find that the share prices of the neglected stocks in our sample increase 4.86% at the announcement of initiation. The announcement returns are positively correlated with the strength of the analyst s recommendation, with strong buy ratings resulting in an average abnormal return of +7.13%, while neutral (hold) ratings result in abnormal returns of only +0.75%. The returns we document are higher than the returns observed in most initiations or rating upgrades (Irvine, 2003; Dhiensiri and Sayrak, 2004; Agrawal and Chen, 2008). 2 Furthermore, the returns are not due to confounding contemporaneous news announcements as argued by Altinkilic and Hansen (2009) in their analysis of stock upgrades and downgrades. However, we do not view the +4.86% return as an estimate of the value added from coverage due to factors such We thank an anonymous referee, Jason Karceski, Jay Ritter, and seminar participants at the University of Florida for useful comments. Cem Demiroglu is an Assistant Professor of Finance at Koc University, Sariyer, Istanbul 34450, Turkey. Michael Ryngaert is the Graham-Buffett Professor of Finance at the University of Florida in Gainesville, Florida, USA. 1 http://www.nasdaq.com/newsroom/news/pr2005/ne_section05_056.stm 2 Dhiensiri and Sayrak (2004) also analyze first time initiations of uncovered firms. They find returns of only about 2% on all initiations and 2.3% for positive initiations. We attribute the smaller returns to sampling problems using I/B/E/S data to identify and date first initiations. See our data discussion in Section I. Financial Management Summer 2010 pages 555-584

556 Financial Management Summer 2010 as liquidity enhancement and/or increased monitoring of management. 3 Stocks are not randomly chosen for initiation. As McNichols and O Brien (1997) argue, a stock is more likely to be covered if an analyst believes it is undervalued. Consistent with this argument, approximately 89% of the recommendations in our sample are buys or strong buys. The ratings for our sample firms are far more bullish than the ratings of sell-side analysts during our sample period. 4 Hence, the large positive returns that we document are not simply due to coverage but rather are due to coverage with a favorable investment opinion. 5 While it is known that analyst initiations result in positive price impacts (Irvine, 2003), our sample provides opportunities for additional insight into the impact of analyst coverage as the firms in our sample are precisely those that are presumably most impacted by coverage. In particular, analyst investment opinions might have more weight given the lack of published information on these firms. Furthermore, since our initiations do not closely follow initial public offerings, they are less anticipated and less likely to be priced into stocks. Given the unique aspects of our sample, we are able to extend and enhance the literature regarding the impact of analyst recommendations in four ways. First, we examine new and/or previously unresolved issues concerning how investors price out initial recommendations given the conflicts of interest faced by analysts. Second, we analyze whether theories postulating downward-sloping demand curves (Miller, 1977; Merton, 1987) are consistent with initiation announcement returns and institutional ownership changes around the initiation date. Third, we examine whether liquidity enhancement has an important role in explaining the share price impact of first-time initiations (Irvine, 2003). The analysis is done in a unified framework that controls for all of the factors above (which are often correlated) simultaneously. Finally, we examine long-run abnormal stock returns after the initiations to determine whether the market correctly prices the information in the initial rating. Stock price increases caused by positive analyst recommendations are often viewed as a puzzle given the conflicts of interest faced by analysts. Perhaps the most prominent conflict of interest cited in the literature is that positive recommendations by sell-side analysts can be viewed as a reward to covered companies for compensation paid for investment banking services (Michaely and Womack, 1999). We find that analysts affiliated with firms that were employed in an investment banking capacity by the covered firm in the past year have lower initiation announcement returns relative to analysts from other investment banks after controlling for recommendation level and other factors. This suggests investor skepticism regarding potentially conflicted initiations. Our results weigh into a literature for which the existing evidence is mixed. While there is agreement that analysts affiliated with investment banks that have provided services for covered firms are more optimistic in their forecasts and recommendations, whether investors adjust their investment decisions due to this optimism is less clear. Our results are consistent with Michaely and Womack (1999) and McNichols, O Brien, and Pamukcu (2007) who find that announcement returns are lower for initial recommendations made by analysts affiliated with the underwriters of a covered firm s recent IPO. Conversely, Lin and McNichols (1998) find less positive price responses for announcements of neutral recommendations by analysts whose firms underwrote the covered firm s SEO, but no differences for buy recommendations. Bradley, Jordan, and 3 Kelly and Ljungqvist (2007) estimate the value of coverage as approximately 1% of the stock value based on a sample of firms that lose all coverage due to exogenous events. 4 During this time period, sell-side analysts had buy or strong buy ratings on approximately 55% to 65% of rated stocks (Barber, Lehavy, and Trueman, 2007; Agrawal and Chen, 2008). 5 Similarly, Khorana, Mola, and Rau (2008) find that brokerage firms strategically drop coverage on firms that they expect will experience significant stock price and operating performance declines.

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 557 Ritter (2003, 2008) report that favorable coverage of IPO firms in the late 1990s and early 2000s was not viewed more skeptically when initiations originated from analysts whose firms provided underwriting services to the covered firms. Iskoz (2003) also finds no evidence that analyst recommendations are treated differently at announcement if the analyst is affiliated with a covered firm s lead underwriter for a recent SEO or IPO. All of the papers above, except Lin and McNichols (1998) and Iskoz (2003), have the drawback that (positive) analyst coverage from lead underwriters of an IPO is highly anticipated shortly after the IPO quiet period (Bradley, Jordan, and Ritter, 2003, 2008). Hence, our results are helpful in resolving the issue of whether conflicts are priced by investors at the time of an initiation. A second result of conflicts of interest involves a new breed of research firms, which we refer to as fee-based research firms. These firms offer coverage in return for an annual fee and a monthly retainer. The hiring of fee-based research firms can be viewed as an attempt by executives of uncovered firms to solve the no coverage problem. However, this raises concerns about the issuance of biased ratings in return for fees and the renewal of coverage contracts. Executives of fee-based research firms argue that they do not cover a firm unless they feel they can make truthful representations about a firm and still be of assistance to the firm. 6 Based on this argument, the ratings of such firms would be informative, with the fee-based firm analyst acting as a certifier of quality. We find that the recommendations of analysts employed by fee-based firms are received positively, with average initiation returns statistically similar to those of analysts affiliated with investment banks that have not been employed by the covered firms. This result is new to the best of our knowledge and indicates that fee-based analysts are viewed (at the time of initiation) by market price setters as no more compromised than analysts affiliated with investment banks that have no business relationship with the covered firms. Another recent development has been the increased importance of firms that rely primarily on selling their research to investors, often indirectly via brokerage or sales and trading business. These brokerage/independent research firms argue that they produce research free of bias since their analysts are not concerned about current or potential future business ties with the covered firm. We find that, holding all else constant, brokerage/independent research firm recommendations elicit lower stock returns at announcement than recommendations issued by investment banks that are not employed by the covered firms. The price impact of recommendations from brokerage/independent research firms and investment banks that have business ties with the covered firm are similar. These results suggest that investors do not place greater trust in analysts affiliated with brokerage/independent research firms. Our results are similar to Cliff (2007), who also finds that buy initiations by brokerage/independent firms have similar announcement returns to initiations made by analysts affiliated with lead underwriters of a covered firm. 7 We present evidence suggesting that a partial explanation for this result is due to the smaller size of the brokerage/independent research firms. Hence, they may have fewer resources to conduct quality research and their recommendations have less visibility. Another contribution of the paper is to examine whether our data are consistent with downwardsloping demand curves for stocks and whether certain stocks experience a larger initiation price impact due to characteristics that are associated with the elasticity of the stock s demand curve. Miller (1977) postulates a downward-sloping demand curve is caused by differences of opinion 6 This is based on a direct phone conversation with James Dutton, the CEO of J.M. Dutton & Associates, one of the most prominent fee-based research firms. 7 Cliff (2007) and Barber, Lehavy, and Trueman (2007) report that for longer run windows, independent research firms tend to have more positive abnormal returns associated with their buy recommendations. Cliff suggests that the initial response to such research is too negative.

558 Financial Management Summer 2010 and short sale constraints. In his model, an initiation can generate demand shocks and price increases by inducing a subset of investors to place a higher valuation on a stock. Merton (1987) argues that the demand curve is more downward sloping (i.e., steeper) when fewer investors are aware of a stock. Firms in our sample fit this description. An initiation can induce newly informed investors to buy the stock giving rise to a demand shock. A demand shock will create a larger price impact the less elastic the demand for the stock. Merton suggests that the demand curve will be less elastic if a firm s stock price volatility is greater (Wurgler and Zhuravskaya, 2002). Consistent with theories of downward-sloping demand curves for stocks, we find that initiation announcement returns are higher for stocks with greater return volatility. This is particularly true in cases where demand shocks are apt to be larger. Specifically, initiation returns are higher for the strongest buy recommendations issued for high-volatility stocks. Finally, consistent with the predictions of Miller (1977) and Merton, we find significant increases in the number of new institutional investors after an initiation relative to a control group. This evidence is consistent with the sales pitch of research firms who argue that research coverage for small firms expands a firm s shareholder base. 8 To complete our analysis of announcement returns, we also investigate whether increases in liquidity impact stock returns at initiation announcements. Irvine (2003) attributes increases in share prices associated with initiations to, at least in part, increases in liquidity. He documents trading increases after an initiation and finds that share price increases are positively correlated with volume increases. We find similar results and estimate an initiation based liquidity impact on share prices of 53 basis points. While 53 basis points is only a small part of the total initiation event returns, the initiation return includes the information content of first-time recommendations. The liquidity effect magnitude is plausible. For example, Kelly and Ljungqvist (2007) estimate the value of losing all coverage for exogenous reasons unrelated to new market information to be 110 basis points. They attribute the 110 basis point impact of dropped coverage to reduced liquidity and reduced price discovery. 9 The final issue we address is the long-term performance of initiated firms stocks. While the evidence regarding market reaction to initiation announcements suggests that investors value certain recommendations more highly, it is possible that investors do not properly value recommendations. This may be particularly true for neglected stocks. For instance, if investors overweigh conflicted analyst recommendations, they may suffer from poor long-run stock performance after the initiation announcement (Michaely and Womack, 1999; Cliff, 2007). It is difficult to make precise long-term assessments given the sample size and volatility of the returns of the small capitalization stocks in our sample, but we can reveal two things. First, the evidence hints that buy rated stocks perform better than hold rated stocks in the six-month to one-year period after an initiation. This is similar to Boni and Womack s (2006) finding that investors do not fully adjust to analyst upgrades and downgrades. Second, for buy ratings, those stocks initiated by analysts affiliated with investment banks that have done recent business with the covered firm tend to underperform stocks initiated by analysts affiliated with investment banks that have no prior business with the covered firm, consistent with Michaely and Womack (1999). The evidence is not, however, statistically strong. 8 For instance, on the website for Cohen Independent Research, the following claim is made, Analyst coverage enables your company s story to be known worldwide, impacts your shareholder base while giving you access to a large market of institutional and retail investors. 9 Consistent with Kelly and Ljungqvist (2007), Dhiensiri, Sayrak, and Zarowin (2005) document increased price discovery after initial stock coverage. Stock prices better reflect future earnings once analyst coverage is initiated.

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 559 The remainder of the paper is organized as follows. In Section I, we discuss our sample and classification of analysts in accordance with the conflicts of interest that they may face. In Section II, we analyze the short-term price and liquidity impacts of analyst initiations and investigate the determinants of the initiation induced share price changes. Section III reviews postinitiation stock price performance. We present our conclusions in Section IV. I. Data Sampling and Overview A. Analyst Initiation Sample We create a novel sample of 549 research initiations for neglected stocks defined as publicly traded stocks that received no analyst coverage for at least one year. We start by identifying the list of possible analyst initiations of uncovered firms using the I/B/E/S historical recommendation files from January 1997 to May 2005. 10 There are two groups of firms in this list: 1) firms for which I/B/E/S records indicate no prior history of recommendations and 2) firms that had prior analyst coverage but no listing of coverage in the past year. For firms in the second group, identifying when the firm lost prior coverage is critical; thus, a brief discussion of our methodology is warranted. I/B/E/S recommendation files report two types of dates for each recommendation. The recommendation date is the date a recommendation is added to the I/B/E/S files, and the review date is the last time a previous recommendation is confirmed by an analyst before the analyst changes his rating or drops coverage. Each I/B/E/S recommendation is valid between these two dates. 11 We assume that firms were covered for the last time at the review date of the last valid coverage. We require that the initiation be one year (or longer) after the most recent review date to enter into our sample. For example, if I/B/E/S reports an initiation for a firm on July 1, 2001 and the last I/B/E/S reported analyst coverage for the firm has a recommendation date of January 1, 2000 and a review date of December 1, 2000, the initiation would not enter the sample as there is only seven months between the most recent review date and the new recommendation release date. After getting a preliminary list of initiations from the I/B/E/S recommendation files, we use the I/B/E/S earnings forecast files, First Call recommendation and earnings forecast files, Investext, Factiva, LexisNexis, Marketwatch.com, and Newratings.com to check whether the firms had earnings estimates or analyst reports issued in the past year. We drop all firms that have coverage reported by these other sources within the 12-month window preceding the preliminary initiation date. We also require validation from one additional source, beyond I/B/E/S, that the initiation actually took place. This is important in correctly identifying event dates for the calculation of the initiation announcement abnormal returns. First Call recommendation files, Investext, Factiva, LexisNexis, Marketwatch.com, and Newratings.com are searched for an announcement of the initiation by the same broker listed in I/B/E/S. We use the earliest date from all these sources (including the I/B/E/S date) as the announcement date as long as it is not more than one month before the I/B/E/S date. There are a number of cases where the initiation was more than a few 10 Although I/B/E/S started recording recommendations in the second half of 1993, coverage in the first few years is less complete. This makes it difficult to identify firms that were truly uncovered via I/B/E/S. Also, the more recent period allows us to use other resources, such as First Call, Investext, and selected websites, to identify prior analyst coverage not recorded in the I/B/E/S files and to better identify the initiation release date. 11 Since I/B/E/S does not always record reiterations of a recommendation, the analyst may issue several reports with the same rating between the recommendation and the review dates.

560 Financial Management Summer 2010 Table I. Frequency of Analyst Initiations of Neglected Stocks by Year, Size, and Industry Our sample consists of 549 analyst initiations from January 1, 1997 to May 31, 2005 for firms whose stocks were publicly traded for at least a year with no analyst coverage. Panel A presents the distribution of the analyst initiations by year. Panel B presents the market capitalization of initiated stocks, and Panel C reports the industry affiliation of the stocks. Panel A. Number of Analyst Initiations by Calendar Year Year Number of Percentage of Initiations Sample (%) 1997 52 9.47 1998 41 7.47 1999 53 9.65 2000 43 7.83 2001 33 6.01 2002 64 11.66 2003 70 12.75 2004 141 25.68 2005 52 9.47 Panel B. Number of Analyst Initiations by Market Capitalization Market Capitalization Number of Percentage of Initiations Sample (%) Less than $25 million 63 11.47 Between $25 and $49.9 million 116 21.13 Between $50 and $99.9 million 157 28.60 Between $100 and $249.9 million 150 27.32 Between $250 and $499.9 million 45 8.30 Above $500 million 18 3.28 Panel C. Number of Analyst Initiations by Industrial Classification 2-Digit SIC Code: Industry Number of Percentage of Initiations Sample (%) 73: Business services 78 14.21 60: Depository institutions 61 11.11 28: Pharmaceuticals and biotechnology 43 7.83 36: Communication and electronic equipment 40 7.29 38: Engineering and scientific instruments 38 6.92 35: Office and computer equipment 26 4.74 days before the I/B/E/S date. 12 A final criterion is that the price of the stock two days before the announcement date is not less than one dollar. Table I presents a breakdown of the initiations by year, market capitalization, and industry. The number of initiations in our sample significantly declined in the 18-month period following the burst of the stock market bubble of 1999-2000. However, in the subsequent period, there is a 12 For this second group, it is often difficult to tell whether the original coverage date recorded by I/B/E/S is a delayed record or a reiteration of a previous initiation.

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 561 significant surge in the number of initiations. Most of the firms in our sample are small, which is consistent with their prior lack of coverage due to inadequate investor interest. More than 85% of the initiations are for firms with less than $250 million of stock market capitalization. Based on two-digit SIC codes, the business services industry has the highest number of initiations. B. Analyst Classifications We classify analysts consistent with their potential for conflicts of interest. We assign the firms that employ the analyst to one of the following categories: 1) investment bank, 2) brokerage/independent research firm, or 3) fee-based research firm. This classification is mainly based on the business descriptions of these firms (i.e., whether they have investment banking or trading units) and the way they are compensated for providing analyst coverage. Sources used to make classification decisions are Nelson s Research Directory, firm websites, and press accounts of a firm s business operations. Classifications are presented in Table II. It is well known that analysts associated with investment banking firms may provide optimistically biased coverage to attract business from firms they cover (Michaely and Womack, 1999). We identified 445 analyst initiations from analysts affiliated with investment banks. CSFB, Merrill Lynch, Bear Stearns, Robinson Humphrey, Brean Murray, and Sterne, Agee, & Leach are examples of investment banks in our sample. Table II reports that 58 of our initiations are from analysts affiliated with brokerage/independent research firms including brokerage houses such as Brookstone Securities and independent research firms such as Farmhouse Research and Provident Equity Research. Given short sale constraints and investor reluctance to short stocks, analysts whose firms provide brokerage services can generate more revenue for their firms by issuing favorable recommendations. 13 Most analysts deal with this conflict as most analysts are affiliated with firms that perform brokerage services. In recent years, a number of firms have identified themselves as independent research firms. In most cases, however, this pertains to a lack of significant investment banking operations. These outfits may be more properly classified as brokerage firms in that their ability to monetize their research is tied indirectly to institutional trading and/or actual brokerage services. Therefore, while their research is not tied to fees from the covered firm, it may still have an optimistic bias. Whether the recommendations are taken more seriously by the investment community is an empirical question. The sample contains 46 initiations from six different firms including Taglich Brothers, J.M. Dutton, and Spelman Research, which provide research coverage in return for subscription fees paid by the covered firm. We classify these firms as fee-based research firms. 14 These firms are relatively new. They tend to provide research for smaller companies. Their research-for-fee relationships are often subject to monthly or annual renewal, and companies enter into them in hopes of receiving favorable coverage and increased liquidity (Craig, 2003). 15 While the potential for an optimistic bias to fee-based reports is obvious, the executives of fee-based firms argue that they refuse to cover a firm if they cannot help the firm. Hence, an initiation serves as a quality 13 Irvine (2004) provides evidence that issuing optimistic recommendations helps brokerage firms to increase market share of trading volume in the covered stock. The advent of hedge fund trading and so called long/short funds might mitigate this problem. 14 As of 2004, Taglich Brothers collected a $5,000 initial retainer from companies and charged a $1,750 monthly fee for the creation and dissemination of research reports. The cost of enrollment in J.M. Dutton s one-year research program is $33,000. Dutton also charged companies a $3,250 annual fee for printing and dissemination costs. 15 Some of these firms have minor investment banking and consulting businesses as well. If they received direct fees associated with the commencement of research, we treated the firm as fee based.

562 Financial Management Summer 2010 Table II. Mean and Median Price, Market Capitalization, Return, Liquidity, and Institutional Ownership of Initiated Stocks Categorized by Analyst Type This table presents the characteristics of 549 stocks that receive analyst coverage after trading publicly a year or longer without research coverage. The period of analysis is January 1, 1997-May 31, 2005. Run-up is the buy-and-hold stock return for 68 to 6 trading days prior to the initiation announcement for initiated stock less the return to a value-weighted portfolio of stocks in the same CRSP market capitalization decile of the stock. Volatility is the standard deviation of daily returns (net of the CRSP market cap decile value-weighted return) for trading days 68 to 6 before initiation. Daily average volume is thousands of shares from CRSP, daily average number of trades and the quoted percentage bid-ask spread are calculated from TAQ data. All three liquidity measures are calculated from 68 to 6 trading days before initiation. Institutional holdings are as reported in Thomson Financial based on 13-F filings the quarter before initiation. Number of Initiations All Analyst Investment Bank Broker/Independent Fee-Based Categories Research Firm Research Firm 549 445 58 46 Mean Median Mean Median Mean Median Mean Median Price ($) 11.2 8.2 11.7 8.6 11.5 9.9 6.0 3.6 131.4 79.2 140.7 84.6 115.9 82.9 60.7 44.3 Market capitalization ($millions) Market-to-book (if book equity positive) 5.5 2.3 4.7 2.4 12.5 2.1 4.8 2.1 Run-up (%) 13.6 4.0 11.4 4.1 24.7 3.3 20.5 1.8 Volatility (%) 4.2 3.7 4.0 3.6 4.1 3.8 5.6 4.7 CRSP market cap. decile 4.1 4.0 4.2 4.0 4.0 3.9 2.9 3.0 (largest = 10) CRSP run-up decile (largest = 10) 6.3 7.0 6.3 7.0 6.4 7.0 6.4 6.5 Daily average volume 63.5 20.2 61.2 23.2 49.6 19.2 92.4 17.5 170.6 46.0 138.4 42.2 166.6 66.3 161.8 40.3 Daily average number of trades Quoted % bid-ask spread 4.3 3.6 3.4 2.8 4.5 3.9 5.8 4.7 Number of institutional 16.9 12.0 17.3 12.0 18.6 14.0 11.2 8.5 owners

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 563 certification. Nevertheless, investors may still view the opinions of fee-based analysts as more compromised than opinions issued by other analysts since renewals of coverage are contingent on the covered firm s satisfaction with the analyst s work. C. Prior Investment Banking Relationships In addition to controlling for differential conflicts of interest based on the above classifications, we also identify cases where the analyst s firm had a preinitiation investment banking relationship with the covered firm that could lead to more pronounced conflicts of interest. Lin and McNichols (1998) and Dugar and Nathan (1995) find that analysts affiliated with the underwriters of an SEO firm are more likely to issue optimistic recommendations and earnings forecasts than other analysts. 16 Dechow, Hutton, and Sloan (2000) document that SEO firms receive more favorable long-term earnings growth forecasts from analysts affiliated with the underwriter of the SEO. Michaely and Womack (1999) find that IPO firms receive relatively more favorable initial coverage from analysts affiliated with their lead underwriters. Consistent with investor skepticism about these recommendations, they also find that buy recommendations from analysts affiliated with the IPO lead underwriter elicit less positive market responses than buy recommendations from other analysts. More recently, however, Bradley, Jordan, and Ritter (2003, 2008) report no differential market reaction to initiations by analysts affiliated and those unaffiliated with a lead underwriter following the IPO quiet period. They argue that affiliated analysts may have better access to information and/or that unaffiliated analysts might have their own biases to lure away covered companies in future investment banking transactions. Iskoz (2003) also finds no evidence that analyst recommendations are given less weight at announcement if the analyst is affiliated with a covered firm s lead underwriter. An analyst s firm is classified as having a prior investment banking relationship with the covered firm if it acted as a lead or comanager in a secondary equity/debt offering, lead placement agent in a private placement, an advisor in a merger, and/or an advisor for generic investment banking services in the year prior to the initiation. The data on secondary public equity offerings, private placements, and mergers are derived primarily from Thomson Financial s SDC Database. To supplement the SDC data, we conducted searches of LexisNexis, Factiva, and Google for instances where the analyst s firm and the covered firm are both mentioned and for information regarding the covered firm s investment banking transactions with the analyst s firm. In our sample, there are 119 initiations from analysts affiliated with investment banks that have a prior business relationship with the covered firm. This constitutes 26.7% of all investment bank classified observations. D. Brokerage Firm Size The price impact of an initiation is also a function of the quality (e.g., informativeness) and visibility of the analyst s research (Clement, 1999; Jacob, Thomas, and Margaret, 1999; Mikhail, Walther, and Willis, 2004; Kelly and Ljungqvist, 2007; Malmendier and Shanthikumar, 2007). There might be heterogeneities across brokerage firms in that regard. For example, initiations from large brokerage firms might be perceived as more informative by investors as these firms tend to have larger research budgets and are likely to attract more skilled analysts. In addition, the larger a brokerage firm s client base, the more investors who will be aware of the initiation; 16 Lin and McNichols (1998) do not find significant differences between the short-term earnings forecasts of affiliated and unaffiliated analysts. Affiliated analysts may favor their firm s clients by issuing pessimistic short-term earnings forecasts, which lowers the bar and helps management meet the earnings expectations.

564 Financial Management Summer 2010 therefore, initiations are likely to result in larger share price impacts based on downward-sloping demand curves as in Miller (1977) and Merton (1987). We use the natural log of the number of analysts employed by the brokerage firm in the year of coverage as tracked by I/B/E/S as a proxy for brokerage firm size (Clement, 1999). 17 Controlling for brokerage firm size is also critical when estimating the marginal effect of the analyst s incentive conflicts on initiation announcement returns. For example, investment banks are typically much larger than brokerage/independent research firms, implying that their initiations are likely to be more informative and visible; however, they also have conflicts (e.g., pushing the stocks of their existing or potential future clients) that brokerage/independent research firms do not have, which might create investor skepticism about their recommendations. E. Covered Firm Characteristics Table II contains summary statistics for variables of interest for the entire sample and by the affiliation of the analyst providing coverage. The sample firms are small with an average market capitalization of $131.4 million. They experience an average return (net of the return to a value-weighted portfolio of stocks in the same CRSP market capitalization decile) of 13.6% for the period 68 to 6 trading days before the initiation announcement. The average (median) market-to-book equity ratio is 5.5 (2.3). The average number of institutional owners is 16.9. We also examine variables associated with liquidity in the period prior to initiation. The sample average (median) daily trading volume is 63,500 (20,200) shares. 18 The average number of trades per day is 170.6. The average bid-ask spread is approximately 4.3% of the share price. 19 To get an idea of relative stock trading activity, using the universe of CRSP firms, we placed stocks in liquidity deciles ranked from 1 to 10 based on trading volume with 10 being the highest level. A randomly selected CRSP stock would have an average rank of 5.5. The average firm in the sample has a daily volume rank of 4.4 and a dollar volume rank of 4.2 (not in the table). Hence, these stocks reflect below CRSP median trading activity levels. The firms covered by fee-based analysts differ considerably from the other firms. These firms are smaller with an average market capitalization of only $60.7 million. The average stock price is about half that of the entire sample at $6, and the average stock return volatility is higher than the volatility of stocks initiated by other analyst types. The number of institutional owners is also relatively low at only 11.2. These stocks best fit the profile of neglected stocks. Presumably, the characteristics of these stocks were such that analysts had to be paid to provide coverage as a result of inadequate trading interest or investment banking business potential. F. Initial Analyst Recommendation Ratings I/B/E/S uses an algorithm to translate different ratings from many analysts into one of the ratings in its five-scale rating system (1 = strong buy, 2 = buy, 3 = hold, 4 = sell, 5 = strong sell). Unfortunately, the translated ratings are not fully standardized. For example, many analyst rating scales have only three possible ratings: 1) buy (outperform), 2) hold (neutral), and 3) sell 17 The experiences of the brokerage firm and the analyst are alternative proxies for the informativeness of the initial report. However, these variables are left truncated and, thus, acquire higher values for later recommendations. Also, they are highly correlated with brokerage firm size. Therefore, we do not report results based on these measures. 18 Trading volumes reported in CRSP are divided by two for NASDAQ firms due to double reporting of trades. This correction, however, is imprecise. The important results in the paper are not dependent on trading volume statistics. 19 Number of trades and bid-ask spread quotes are taken from TAQ data.

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 565 (underperform). This is particularly true after the adoption of Rule 2711 in September 2002. The rule requires brokers to disseminate their ratings on a three-point scale, although it does not prohibit them from also providing a more detailed scale (e.g., outperforms can be split into strong buys and buys ). Unfortunately, I/B/E/S uses an inconsistent coding for firms that use only a three-point scale. For example, buy-hold-sell ratings from some brokers (e.g., Merrill Lynch) are translated by I/B/E/S as 1-3-5, whereas the same ratings from others (e.g., Goldman Sachs) are translated as 2-3-4. In fact, there is no real distinction between a 1 from Merrill and a 2 from Goldman Sachs. 20 This problem is not isolated to the post-september 2002 period. Prior to this time, certain brokerage firms had only one outperform (buy) rating, and the I/B/E/S classifications are also inconsistent for these cases. In order to fix this bug in I/B/E/S ratings, we manually searched Investext and Factiva and adjusted the I/B/E/S ratings when necessary. We refer to a buy rating for firms on a three-point scale (buy, hold, sell) as a three-scale buy. We converted 47 buy and 109 strong buy ratings in I/B/E/S to three-scale buys. If the brokerage firm distinguishes between buys and strong buys, we keep the buy or strong buy designations. We also checked cases where the rating in I/B/E/S differed from the rating in First Call and, once again, manually searched Investext and Factiva to ascertain which data vendor has the true rating. Consequently, we converted 10 I/B/E/S buy ratings to strong buy and nine I/B/E/S strong buy ratings to buy. Finally, we eliminated four sell recommendations from the sample. 21 Panel A of Table III presents the strength of the recommendation ratings for the entire sample and by the affiliation of the analyst providing coverage. Approximately 89% of the recommendations in our sample are buys, three-scale buys, or strong buys. These are optimistic ratings relative to those generally observed. For instance, during this period, sell-side analysts typically had some type of buy rating on approximately 55% to 65% of all stocks (Barber, Lehavy, and Trueman, 2007; Agrawal and Chen, 2008). The total sample includes 61 hold ratings (about 11% of the sample). If one believes that analysts only issue initiations when they have something good to say (Lin and McNichols, 1998), it is not clear why an analyst would initiate coverage with a hold. To learn more about these cases, we search Investext for initiation reports with a hold rating. We find that some analysts are reluctant to issue optimistic recommendations for stocks with no other analyst coverage. One notable example is Morgan Keegan s initial report on Bio Reference Labs in June 2002. The analyst initiated coverage with a speculative market perform (I/B/E/S translates this to a hold) and noted that although the stock had good prospects, the lack of existing analyst coverage dissuaded him from issuing a more favorable rating. In addition, analysts sometimes initiate coverage with a hold to inform the market that the stock is added to their watch list and may become a good long-term investment if the company solves ongoing legal, managerial, or financial problems. For example, Roth Capital Partners initiated coverage on Checkers Drive-In Restaurants with a hold rating in November 2002. The analyst noted that although he had a positive opinion about the company s outlook, he issued a hold rating because he could not articulate the company s growth and earnings strategies due to the unwillingness of management to communicate with Wall Street analysts. Seven months later, when the company s board appointed a new CEO who chose to communicate with analysts, Roth Capital Partners upgraded the stock s rating to a buy. 20 We thank an anonymous referee for pointing this out. 21 Arguably, sell recommendations are very different in terms of the rationale for the analyst to provide coverage.

566 Financial Management Summer 2010 Table III. Distribution of Analyst Recommendations Ratings Categorized by Analyst Type and the Presence of Prior Investment Banking Relationships with the Covered Firm This table provides descriptive statistics regarding analyst recommendation ratings. Panel A presents the ratings based on our analyst categories. Panel B presents the ratings based on the affiliation of the analyst s firm with the covered firm for investment banks only. A prior relationship is defined as a situation where the analyst s firm has previously served as an underwriter or comanager for a public or private placement of debt or equity, an advisor in a merger, or an advisor on other investment banking matters in the past year. The period of analysis is from January 1, 1997 to May 31, 2005, and the sample is 549 stocks that received initial analyst coverage after having no research coverage for one year. Category/Affiliation N Ratings Fraction of Ratings Strong Buy 3-Scale Buy Buy Hold Panel A. By Analyst Category All analyst categories 549 0.281 0.282 0.326 0.111 Investment bank 445 0.281 0.301 0.317 0.101 Broker/independent research firm 58 0.362 0.328 0.121 0.190 Fee-based research firm 46 0.174 0.043 0.674 0.109 Panel B. By Analyst s Affiliation with the Covered Firm (Only Investment Bank Initiations Are Included) Prior relationship 119 0.361 0.219 0.328 0.092 No prior relationship 326 0.252 0.331 0.313 0.104 Table III also indicates that brokerage/independent research firms provide the most bullish ratings initiating coverage with a strong buy or three-scale buy rating 69% of the time. However, these firms also issue the highest proportion of hold ratings. Merely 21.7% of the ratings from fee-based research firms are strong buy or three-scale buy, in spite of the fee that the covered firms pay for coverage. Nevertheless, the fraction of hold ratings for the fee-based group is lower than that for the brokerage/independent research firms and similar to that for investment banks, consistent with the idea that coverage is not provided unless it is helpful to the client. The lower average ratings from fee-based firms may reflect the different nature of the firms they cover. Stocks covered by non-fee-based analysts may be selected for initiation primarily because they look attractive as investments, whereas fee-based analysts may be willing to cover marginally attractive investment candidates more frequently in return for a fee. In other words, the initial ratings issued by fee-based analysts could still be optimistically biased, although their average ratings are lower than those issued by other analysts. Panel B in Table III provides a comparison of the ratings issued by investment bank analysts based on the existence of a prior business relationship between the covered firm and the analyst s firm. The initiations from investment banks with prior relationships do not have more positive ratings. The fraction of hold ratings is almost identical for the two groups and the combined frequency of strong buys and three-scale buys, the highest ratings possible for an analyst, is virtually identical. This evidence appears inconsistent with the hypothesis that analysts associated with investment banks with preexisting relationships with initiated firms issue more optimistically biased ratings than other investment bank analysts. Again, however, this is not proof that these ratings are accepted in the same way by investors in terms of their credibility. Hence, we now turn to announcement returns.

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 567 II. Valuation, Institutional Ownership, and Liquidity Impacts of Initiations A. Short-Term Market Reaction to Analyst Initiations We first look at the general event study results to ascertain whether the first-time analyst coverage has a price impact for the covered firm s stock. We use size-adjusted returns as our measure of abnormal returns. Specifically, we assign each firm to a CRSP market capitalization decile according to its market capitalization at the end of the month prior to initiation and use the value-weighted return on this market capitalization portfolio as our size index. The size-adjusted abnormal return is defined as the buy-and-hold return on the stock minus the buy-and-hold return on the size index over Days 1to+1 where Day 0 is the initiation date. Table IV provides the average and the median abnormal returns for the entire sample and for various subsets of the sample based on analyst affiliation and the strength of the initial recommendation. The average event window abnormal return is +4.86% for the entire sample. 22 Also, consistent with investors valuing the information content of the initiation ratings, market reactions are higher for stronger ratings. The average abnormal return is +7.13% for strong buy recommendations, +5.61% for three-scale buy recommendations, +3.66% for buy recommendations, and +0.75% for hold recommendations. The median abnormal return is +2.26% for the entire sample and +4.07% for the strong buy initiations. The difference between the mean and the median returns is due to a number of large positive announcement returns. 23 With the exception of coverage provided by brokerage/independent research firms, the market reactions tend to be in line with the strength of the recommendation. Unconditional on the strength of the recommendation, initiations made by brokerage/independent research firms result in the lowest returns. The returns are the highest for strong buy recommendations made by fee-based research firms, but the sample size is too small to generalize this finding. As demonstrated in Panel B of Table IV, the valuation impact of recommendations from investment banks is significantly smaller when the investment bank has a prior business relationship with the covered firm. Strong buy recommendations result in an average +3.58% abnormal return for cases with an investment banking relationship versus +9.44% for cases with no investment banking relationship. The difference is significant at the 1% level. This finding is consistent with the conflict of interest hypothesis that suggests that the market puts less weight on optimistic initiations from analysts employed by investment banks that have a higher perceived conflict of interest. Abnormal returns associated with three-scale buy, buy, and hold recommendations are not significantly related to the existence of a prior investment banking relationship. A couple of issues are worth noting about the event study results. First, they are not driven by confounding news announcements during the event window. Altinkilic and Hansen (2009) claim that most, if not all, of the positive returns on recommendation rating upgrades and downgrades are due to news announcements just prior to analyst revisions and that analysts are merely piggybacking on good or bad news. Only 8.74% (5.65%) of our observations had what 22 We also calculated announcement returns using midpoints of daily closing quotes from CRSP and adjusting for stock splits and dividend payments. The average initiation announcement return based on quote midpoints is 4.49% (merely 37 basis points below the average return based on trade prices). This implies that bid-ask bounce explains only a small portion of the announcement returns that we document. 23 For instance, when Miller, Johnson, and Kuehn initiated Insignia Systems with a strong buy on May 16, 2000, the stock price surged by 65%. Similarly, when BancBoston Robertson Stephens initiated coverage on Netegrity, Inc. in April 27, 1999 with a strong buy rating, the stock price jumped about 46% around the announcement. We searched Factiva and LexisNexis for confounding announcements around these initiations and found none.

568 Financial Management Summer 2010 Table IV. Mean and Median Three-Day Announcement Returns for Initiated Stocks Categorized by Analyst Type and the Presence of Prior Investment Banking Relationships with the Covered Firm This table provides information about the average buy-and-hold size-adjusted abnormal return by the recommendation rating and the type of firm the analyst is affiliated with (Panel A) and the existence of a prior business relationship between the covered firm and the analyst s investment bank (Panel B). A prior relationship is defined as a situation where the analyst s firm has previously served as an underwriter for a public or private placement of equity or as an advisor in a merger in the past year. Analyst coverage data for January 1, 1997-May 31, 2005 are from the I/B/E/S recommendation files. Abnormal returns are calculated in the ( 1, +1) trading day window surrounding the announcement date of the analyst report. The top rows provide the relevant sample mean returns, the second rows provide the medians (italic), and the bottom rows provide the number of observations. Significance levels denote differences from zero for the means and medians (in italics). All Rating t-stat (Z-score) Strong Buy 3-Scale Buy Buy Hold for Differences in Means (Medians) of Any Buyand-Holds Panel A. By Analyst Category (Mean and Median Returns) All analyst categories 4.86% 7.13% 5.61% 3.66% 0.75% 5.87 2.26% 4.07% 3.22% 1.06% 0.32% 2.73 549 154 155 179 61 Investment bank 5.10% 7.43% 5.50% 3.84% 1.39% 4.37 2.59% 4.61% 3.20% 1.06% 1.23% 3.61 445 125 134 141 45 Broker/independent research firm 2.83% 2.18% 5.99% 4.06% 2.17% 3.87 0.80% 0.91% 3.94% 3.90% 1.13% 2.59 58 21 19 11 11 Fee-based research firm 5.07% 15.41% 9.37% 2.73% 1.35% 1.98 1.74% 15.04% 9.37% 1.17% 1.58% 0.30 46 8 2 31 5 (Continued)

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 569 Table IV. Mean and Median Three-Day Announcement Returns for Initiated Stocks Categorized by Analyst Type and the Presence of Prior Investment Banking Relationships with the Covered Firm (Continued) All Rating t-stat (Z-score) Strong Buy 3-Scale Buy Buy Hold for Differences in Means (Medians) of Any Buyand-Holds Panel B. By Analyst s Affiliation with the Covered Firm (Mean and Median Returns) (Only Investment Bank Initiations Are Included) Prior relationship 3.50% 3.58% 5.48% 2.52% 1.97% 0.80 1.14% 2.54% 2.93% 0.56% 1.23% 0.47 119 43 26 39 11 No prior relationship 5.68% 9.44% 5.50% 4.34% 1.21% 4.69 2.95% 5.49% 3.35% 1.61% 1.10% 2.97 326 82 108 102 34 t-stat (Z-score) for differences in 2.21 2.96 0.01 1.07 0.36 means (medians) of investment 2.06 2.48 0.81 0.72 0.00 banks with prior vs. no relationship Significant at the 0.01 level. Significant at the 0.05 level. Significant at the 0.10 level.

570 Financial Management Summer 2010 we interpreted as a significant good (bad) news event during our event windows (see the Data Appendix for a definition of good and bad news). The average announcement return for firms with no confounding events is +4.85%, only 1 basis point lower than for the entire sample. Second, the initial event study results are far larger than those reported in most prior papers on analyst initiations. For example, using a sample of 1995 initiations, Irvine (2003) reports announcement-period abnormal returns of +0.75% for the average analyst initiation and +1.49% for strong buy initiations. His sample, however, includes all initiations unconditional on prior coverage. For strong buy initiations on stocks with one to three existing analysts, returns increase with a +2.61% average announcement abnormal return. Our results are consistent with the notion that less coverage implies larger initiation impacts. B. Institutional Ownership Changes One implication of the returns evidence is that the initiations cause some investors to increase their dollar investment in the initiated stock. This could occur because those owning the stock continue to hold as the price rises. More likely, the initiation induces some investors to take or increase a share position in the stock (Malmendier and Shanthikumar, 2007). Under the investor recognition hypothesis (Merton, 1987), simply becoming aware of a stock causes an increase in holdings by new investors. Miller (1977) argues that new investors may initiate purchases of a stock because an analyst s recommendation causes them to value the stock more highly relative to other market participants. In either case, the extra demand lifts share prices given a downward-sloping demand curve for the stock. While we cannot track the activities of retail investors, we can observe changes in institutional holdings, though only with considerable lead and lag. Using institutional ownership data based on 13-F filings recorded by Thomson Financial on a quarterly basis, we can compare institutional holdings for the most recent date before and after an initiation. Table V contains data reporting the number of new institutional investors that hold the stock after the initiation, the amount (percentage) of the stock new investors hold, the number of institutional investors that exit the stock entirely after an initiation, the change in the amount (percentage) of the firm s stock held after the initiation by those who held it prior to the initiation, and the change in percentage holdings for all institutional investors combined. We compare each initiated firm to a control group of stocks based on market capitalization, three-month preinitiation stock price returns, and trading volume. We find that for strong buy and three-scale buy recommendations, there is a greater increase in new institutional investors for the initiated stocks than for the control group and that the increase in the amount of stock they own is greater. Both differences are statistically significant at the 1% level based on Wilcoxon rank-sum tests. Hence, positive recommendations attract more institutional investors to a stock. This is consistent with Miller (1977) and Merton (1987) and also with Irvine (2003) who finds increases in institutional holdings after an initiation. We do not, however, find any significant increases for new or total institutional holdings after an initial hold recommendation relative to a control group. Therefore, only positive initiations are followed by increased institutional holdings. While we do not report the results, we also made comparisons in increases in new institutional holders and percentages held by new institutional holders based on analyst category. Based on Wilcoxon signed-rank tests of paired observations with control group stocks, we found that all categories had statistically significant (at 5% or lower) increases in both the number of new institutional investors and the amount held by those investors, except for the fee-based category. This group had no measurable increases in new institutional holdings relative to the control group. Given that these stocks had much smaller market capitalizations, it is plausible that institutions

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 571 Table V. Postinitiation Institutional Ownership Changes for Initiated Stocks Categorized by Recommendation Rating This table presents institutional ownership changes after analyst coverage initiations for previously uncovered stocks by recommendation rating.analyst coverage data for January 1, 1997-May 31, 2005 are from the I/B/E/S recommendation files. For each stock in the initiation sample, we identify potential control stocks that are in the same CRSP market capitalization, volume, and three-month run-up decile as the sample stock. Among the potential controls, we choose the one that has the closest run-up to our sample stock as the control stock. The top rows provide the relevant sample mean returns and the bottom rows provide the medians (in italics). We use paired t-tests and nonparametric Wilcoxon rank-sum tests to compare the means and medians, respectively, of the sample and control firms. Significance levels denote differences between the sample mean or median (in italics) and the control means or medians. Strong Buy 3-Scale Buy Buy Hold Sample Control Sample Control Sample Control Sample Control Number of new institutional owners 5.89 4.09 6.06 3.90 6.13 4.63 4.57 6.48 3.00 2.00 4.00 2.00 3.00 2.00 2.00 2.00 Number of institutions that entirely sell out 2.07 3.37 2.41 3.78 2.24 3.20 2.05 3.85 1.00 1.00 2.00 2.00 1.00 2.00 1.00 1.00 Change in ownership fraction of existing inst. (%) 0.89 1.32 1.05 1.76 0.70 1.82 0.72 2.12 0.20 0.23 0.30 0.47 0.10 0.38 0.00 0.43 Ownership fraction of new institutions (%) 4.53 2.39 4.14 1.75 4.06 3.57 2.40 2.73 1.10 0.41 1.30 0.43 0.60 0.49 0.20 0.29 Change in total institutional ownership (%) 3.64 1.07 3.09 0.01 3.36 1.76 1.68 0.61 1.00 0.05 1.20 0.01 0.50 0.16 0.30 0.28 Firms with increases in number of inst. owners (%) 69.28 43.14 67.10 34.84 56.98 45.25 57.38 53.33 Firms with increases in percent inst. ownership (%) 73.86 51.63 69.68 50.32 65.36 60.89 63.93 56.67 Significant at the 0.01 level. Significant at the 0.05 level. Significant at the 0.10 level.

572 Financial Management Summer 2010 Table VI. Descriptive Statistics for Postinitiation Liquidity Changes Categorized by Analyst Type and Recommendation Rating This table provides liquidity changes after analyst coverage initiations for previously uncovered firms by recommendation rating and analyst classification. Change in logged average daily split-adjusted volume, change in logged average daily number of trades, and percentage change in average daily quoted spread are measured from +6 to+68 versus 68 to 6. Change in log average daily volume net of index volume change is defined as the change in logged average daily volume less the change in logged average daily volume for a set of firms in the same volume decile as the covered firm in the period 68 to 6. Panel A. Descriptive Statistics Mean Median StdDev. Min Max Change in log volume 0.1516 0.1226 0.7657 2.6280 2.1290 Adjusted change in log volume 0.1171 0.0699 0.7167 2.4120 2.6000 Change in log number of trades 0.2415 0.1691 0.7486 3.2470 1.6000 Change in % quoted spread 0.0031 0.0021 0.0184 0.1149 0.0831 All Strong Buy 3-Digit Buy Buy Hold Panel B. Adjusted Change in Log Volume All analyst categories 0.1171 0.2802 0.1755 0.0410 0.2199 Investment bank 0.1243 0.2726 0.2027 0.0408 0.2599 Broker/independent research firm 0.1102 0.2703 0.0409 0.1611 0.0969 Fee-based research firm 0.0564 0.4245 0.3631 0.0874 0.5566 Panel C. Change in Log Number of Trades All analyst categories 0.2415 0.3841 0.3216 0.1360 0.0128 Investment bank 0.2615 0.3813 0.3540 0.1668 0.0324 Broker/independent research firm 0.2131 0.3748 0.1300 0.0531 0.2052 Fee-based research firm 0.0838 0.5366 0.0286 0.0386 0.3158 Panel D. Change in % Quoted Spread All analyst categories 0.0031 0.0050 0.0035 0.0033 0.0034 Investment bank 0.0035 0.0053 0.0037 0.0029 0.0005 Broker/independent research firm 0.0009 0.0048 0.0025 0.0148 0.0185 Fee-based research firm 0.0020 0.0007 0.0014 0.0021 0.0033 Significant at the 0.01 level. Significant at the 0.05 level. Significant at the 0.10 level. still do not find these stocks suitable for investment or do not place much weight on fee-based recommendations. Hence, the appeal of fee-based recommendations might be greater among retail investors. C. Liquidity Changes around Initiations Prior research has demonstrated that initiation of coverage by an analyst is followed by an increase in a stock s liquidity (Irvine, 2003). Table VI reports postinitiation changes in the trading volume (adjusted for stock splits), the number of trades, and the effective bid-ask spread. Change

Demiroglu & Ryngaert The First Analyst Coverage of Neglected Stocks 573 in the log of average daily trading volume equals 0.1516 for the period +6 to+68 trading days after initiation relative to 68 to 6 trading days before initiation. The difference is significantly different from zero at the 1% significance level. The results are similar when we adjust for changes in log average daily trading volume for firms in the same CRSP decile as our firms. The index adjusted change is 0.1171. We use two other liquidity measures to examine changes in liquidity around our sample initiations. The average change in the log daily average number of trades equals 0.2415 and the change in the percentage bid-ask spread is equal to 31 basis points. Both of these are statistically significant at the 1% level. Therefore, consistent with the liquidity hypothesis, all our measures indicate increased liquidity subsequent to analyst initiations. Since we know that initiated stocks may be selected based on the prospect of increased trading, we also examine whether the liquidity changes in our sample stocks are any different from other stocks that have similar liquidity levels and similar recent share price increases. For each stock in our initiation sample, we identify a control stock with similar market capitalization (at 6 trading days before initiation), and similar preinitiation number of trades and stock returns (68 to 6 trading days prior to the initiation announcement). We then measure the change in log average daily number of trades for the sample and the control stocks. The average change in log average number of trades is 0.0319 (insignificant) for the control group. The average paired difference between the initiation group and the control group log average daily number of trades is 0.2117 (significant at the 1% level). This suggests that liquidity increases in our sample of initiations are not driven by observable preinitiation stock characteristics. Panels B, C, and D present how the liquidity improvements vary by the type of initiating analyst and the strength of recommendation rating. Initiations of analysts employed by investment banks are associated with relatively larger liquidity improvements. In addition, liquidity increases are positively correlated with the strength of the recommendation rating. Strong buy ratings are associated with the largest increases in trading and the largest decreases in percentage bid-ask spreads. Three-scale buy ratings are also associated with statistically significant increases in the number of trades and decreases in the percentage quoted spread, but this is primarily driven by investment bank initiations. Firms initiated with a hold rating experience modest decreases in liquidity. This is inconsistent with Irvine (2003) who reports increases in liquidity for stocks that have an analyst initiation with a hold. To sum up, liquidity changes are greatest for the strongest buy recommendations and for investment bank initiations. D. Initiation Announcement Abnormal Return Regressions The results presented in Table IV suggest that returns are higher for more positive recommendations and lower when the initiating analyst is affiliated with a firm that has a prior investment banking relationship with the covered firm. In this section, we use regression analysis to control for all the determinants of initiation abnormal returns. In all of the specifications, we include dummy variables for the strength of recommendation rating and the type of firm the initiating analyst is affiliated with. We also add a dummy variable, Conflict, set equal to one if a preinitiation investment banking relationship exists between the analyst s firm and the covered firm. Additionally, we control for firm size and preinitiation volatility of the covered firm s stock. Volatility equals the standard deviation of the firm s daily size-adjusted abnormal stock return for the period 68 to 6 trading days relative to the initiation date and proxies for elasticity of demand (Wurgler and Zhuravskaya, 2002; Merton, 1987). We winsorize this variable at the 1% and 99% levels. Also, we include a dummy variable that equals one if there are multiple initiations

574 Financial Management Summer 2010 in the event window and all those ratings are positive. 24 Finally, we include dummy variables for the presence of negative and positive confounding events. 25 Panel A of Table VII presents the regression results for the entire sample. The dependent variable is the percentage three-day buy-and-hold size-adjusted return. In Regression (1), we include the above-mentioned dummy variables, firm size, and volatility. We find that the returns increase with the strength of the recommendation. For example, strong buy recommendations are associated with 5.54% higher announcement returns (significant at the 1% level) than hold recommendations (the omitted rating group), holding all else constant. The evidence supports the view that it is not coverage per se but coverage with positive private information that causes the large valuation increases at the announcement of first initiations. We also find that the returns are 2.28% lower (significant at the 5% level) when a prior investment banking relationship exists between the analyst s firm and the covered firm, suggesting that investors discount ratings by investment banks that have incentives to support the covered stocks. The evidence is consistent with Michaely and Womack (1999) and McNichols, O Brien, and Pamukcu (2007) who find that announcement returns are lower for initiations by analysts affiliated with the underwriters of a covered firm s recent IPO. Conversely, the evidence is inconsistent with Lin and McNichols (1998), Bradley, Jordan, and Ritter (2003, 2008), and Iskoz (2003) who find that positive initiations by analysts whose firms provided underwriting services to the covered firms are not viewed more skeptically. After accounting for the existence of a prior relationship with the covered firm, initiations from investment banks (the omitted group) seem to create greater share price increases than initiations from brokerage/independent research firms and fee-based research firms, though only the coefficient on the brokerage/independent research firm dummy is statistically significant (at the 5% level). Thus, we fail to reject the hypothesis that fee-based firms recommendations are viewed as being less credible than other sell-side recommendations, in spite of the apparent possibilities for conflict of interest. Also, the evidence suggests that recommendations from brokerage/independent research firms are not treated as more independent by market participants. An alternative interpretation is that investment banks and brokerage/independent research firms differ in terms of the quality and visibility of research they produce. In order to distinguish between these two accounts, in Specification (2), we include a proxy for brokerage firm size, the natural log of the number of analysts affiliated with the analysts firm covering stocks as reported by I/B/E/S in the year of initiation. Larger brokerage firms should have larger client bases, so initiations from these firms reach more investors and are more likely to result in larger share price increases. Also, initiations from large brokerage firms might be perceived as more informative as these firms are likely to attract more skilled analysts and tend to have larger research budgets. Consistent with these views, we find that brokerage firm size is positively related to initiation announcement returns (significant at the 1% level). A one standard deviation increase in LN (number of analysts) is associated with a 1.43% increase in the returns, holding all else constant. Also, when we control for brokerage firm size, the coefficient on the brokerage/independent research firm dummy becomes insignificant, suggesting that part of the difference in the price impact of initiations from brokerage/independent research firms versus investment banks is due to the better quality and/or greater visibility of analyst research at investment banks. 24 In 13 cases, there are multiple analyst initiations in the event window. These initiations might be considered more bullish than a single rating if all ratings are positive. In 9 out of the 13 cases, all recommendations are buys or strong buys. 25 The definitions of confounding events are provided in the Data Appendix.