Does sell-side debt research have investment value?

Abstract

This study examines whether sell-side debt research has investment value for debt investors. We find that both the levels of and changes in recommendations are associated with event-time abnormal bond returns, and that changes in recommendations (i.e. upgrades and downgrades) are associated with stronger price reactions. More importantly, we find that changes in recommendations are associated with a significant post-event bond price drift, suggesting delayed market reactions to recommendation changes. The calendar-time portfolio approach of buying (selling) bonds following upgrades (downgrades) generates significant abnormal bond returns. In addition, we present new evidence that debt analysts often provide different recommendations for bonds issued by a firm to reflect different bond-specific characteristics. Overall, our results suggest that debt analysts’ recommendations have investment value.

Keywords:

• bond returns
• debt analysts
• market efficiency
• recommendations

Acknowledgements

We are grateful for helpful comments and suggestions from Mark Clatworthy (editor) and two anonymous reviewers. We also appreciate the constructive feedback from Stefano Bonini (discussant), Lee-Seok Hwang, Gi Kim, Sangwan Kim, Yun Ke (discussant), Yun Lee (discussant), and participants at the 2018 Financial Management Association Annual Meeting, the 2018 American Accounting Association Annual Meeting, the 2018 European Accounting Association Annual Meeting, the 2018 Canadian Accounting Association Annual Meeting, and the seminar at Seoul National University. Sunhwa Choi appreciates support from the Institute of Management Research at Seoul National University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 For example, bond investors, relative to equity investors, have a greater demand for negative information and for financially distressed firms, because bonds have limited upside potential and bond prices are more sensitive to the change in firm value for financially distressed firms (De Franco et al. 2009, Johnston et al. 2009, Wang 2019). This asymmetric demand for negative information in debt markets affects firms’ financial reporting practices to accelerate the recognition of bad news, and hence, accounting conservatism (Ball et al. 2008). See Section 2 for more discussions on the differences between debt and equity markets (securities).

2 Recommendations are derived from all available sources of information (e.g., public and private, quantitative and qualitative). In addition, while other information in debt reports requires user-side interpretation, recommendations are clear investment signals that are directly communicated to investors (Elton et al. 1986). The lack of research on debt recommendations is in sharp contrast to abundant research on the properties and profitability of equity analysts’ recommendations (e.g., Stickel 1995, Womack 1996, Barber et al. 2001, Bradshaw 2011).

3 Our study is also different from De Franco et al. (2009) in that we use bond-specific (rather than firm-level) recommendations and returns. We report new findings that debt analysts often provide recommendations only for a subset of bond issues of a firm and that they sometimes provide different recommendations for the bonds issued by the firm, which suggests that they incorporate different bond-specific characteristics (e.g., maturity, seniority, collateral, and liquidity) into their recommendations. In addition, we provide descriptive evidence on the cited reasons for recommendation changes and for issuing different recommendation for bonds of a firm, which would help readers better understand the nature of information contained in debt reports.

4 Note that the presence of post-revision drift, if any, does not necessarily indicate the profitability of debt analysts’ recommendations, because the drift can be too short-lived or its magnitude may be too small to be exploited in a profitable trading strategy.

5 Womack (1996) and Barber et al. (2001) find a price drift after the issuance of equity analysts’ recommendations. They also find that this drift is short-lived (long-lived) for upgrades (downgrades).

6 Based on the round-trip transaction costs of 0.48% (which we believe is a conservative estimate considering that the monthly transaction amount of our sample bonds is much larger than that of the TRACE sample bonds), the after-transaction-cost return is negative for the one-month holding period (0.38% − 0.48% = −0.10%) but is positive for the two-, three-, and six-month holding periods (0.33%, 0.73%, and 0.91%, respectively).

7 These bond-specific characteristics become particularly relevant for financially distressed firms because the recovery rate in the case of default varies significantly across bonds, according to their seniority, asset coverage, and covenant protections (Gillette 2016).

8 Relatedly, our finding of incomplete event reactions supplements the literature on investors’ underreactions to major announcements, such as earnings releases (Bernard and Thomas 1989), dividend initiation and omissions (Michaely et al. 1995), management earnings forecasts (Ng et al. 2013), and equity analysts’ recommendations (Womack 1996).

9 While debt analysts communicate with debt investors through debt reports, they can also interact with investors through other means. For example, Wang (2019) examines the effect of broker-hosted conferences that are credit investor oriented and finds that the bond market reacts to these credit conferences, particularly when the bonds have speculative grade credit ratings and short time-to-maturities.

10 Hugon et al. (2021) also find that the quality and informativeness of cash flow forecasts issued by equity analysts are higher when they have access to in-house sell-side debt research.

11 We standardize debt analysts’ recommendations into three categories of buy, hold, or sell (De Franco et al. 2009, 2014). For example, if the recommendation is ‘buy,’ ‘attractive,’ ‘overweight,’ or ‘overperform,’ we code them as ‘buy.’ If the recommendation is ‘sell,’ ‘unattractive,’ ‘underweight,’ or ‘underperform,’ we code them as ‘sell.’ If the recommendation is ‘hold,’ ‘neutral,’ ‘marketweight,’ ‘marketperform,’ or ‘core hold,’ we code them as ‘hold.’

12 Gurun et al. (2016) report that 37 percent of their sample debt reports do not induce any immediate debt trading. Although this result of inadequate initial reactions may imply a subsequent drift, it does not provide indications of the magnitude or the duration of the drift. In addition, note that Gurun et al. (2016) do not distinguish the debt reports with and without recommendation changes. Thus, it is possible that the lack of strong initial reactions in their study is mainly driven by the reports issuing reiterated recommendations.

13 However, Gillette (2016) examines individual debt reports for financially distressed firms and suggests that most reports simply reiterate information already available from other information sources.

14 Rebello and Wei (2014) examine the investment value of the research by buy-side equity analysts, who provide in-house research for fund management firms. They find that the excess return predicted by buy-side equity analysts has investment value over a one-year horizon.

15 Altinkilic et al. (2016) show that the trading strategy based on equity analysts’ recommendation revisions did not generate abnormal profits over 2003–2010, during which high frequency trading grew rapidly.

16 Soft dollars refer to the payment made by investment managers to their brokerage-dealer firms for their services (e.g., research) through commission revenues from directing trades to the brokerage-dealer firms, rather than through direct payments in cash (i.e., hard dollars).

17 http://www.integrity-research.com/eliminating-the-soft-dollar-subsidy.

18 Our sample period begins in July 2002 because the coverage of the Trade Reporting and Compliance Engine (TRACE) database begins in July 2002.

19 About 99.4% of our sample reports are from eight brokerage firms: Deutsche Bank (45.2%), Bear Stearns (19.8%), UBS (9.4%), Morgan Stanley (6.6%), Keybanc Capital (6.2%), JP Morgan (5.0%), RBC Capital Markets (4.9%), and CIBC Worked Markets (2.3%). Our sample size of 3,877 debt reports is relatively smaller than the sample size used in prior studies. For example, the number of debt reports used in Johnston et al. (2009) is 5,920 from 15 brokers during 1999–2004, and that in De Franco et al. (2009) is 15,918 from ten brokers for 2002–2006. Our correspondence with the authors of these papers and the researchers of Thomson ONE Banker (a provider of Investext) indicates that several banks have removed their reports from the database, resulting in a smaller number of reports in the database. We caution readers that to the extent that the coverage of a brokerage firm is systematically related to its performance, our results can overstate or understate the investment value of debt reports. Note that Table 2 presents the sample before we require non-missing bond returns for the main empirical analyses. The number of observations differs across the analyses because each analysis requires different measurement periods for bond returns.

20 De Franco et al. (2009) report that the percentage of recommendations for buy, hold, and sell is 39.1%, 47.3%, and 13.6%, respectively, which is similar to the distribution of recommendations reported here. Note that while De Franco et al. (2009) collect firm-level recommendations, we report bond-level recommendations.

21 The enhanced version of TRACE reports uncapped transaction volume data, whereas the trade sizes in the standard TRACE are capped at $5 million for investment-grade bonds (i.e., reported as ‘5MM+’) and $1 million for speculative-grade bonds (i.e., reported as ‘1MM+’), respectively. We follow Dick-Nielsen (2014) and Dick-Nielsen and Rossi (2019) to eliminate transactions known to be erroneous, agency transactions, and interdealer double-counted transactions.

22 To adjust for interest rate movement, we use T-bill-adjusted bond returns (i.e., the difference between the raw return and the return of the US 30-day T-bill) as an alternative measure of abnormal bond returns, and find that inferences are not altered (untabulated).

23 Thus, our returns over the (−2, +2) window measure bond price reactions over up to 11 days around the issuance date of debt reports. If we require that the bond prices be available on day −2 and day +2, we find similar results, although the sample size is reduced by 50%.

24 We also examine the bond returns over the (0, +2) period and find similar results.

25 Note that our extended period to calculate post-event bond returns does not include the extended event period that we use to calculate the five-day event-period bond returns.

26 In untabulated tests, we examine whether the magnitudes of event-time reactions and post-event drifts are affected by the number of cited reasons for recommendation changes. When multiple reasons are provided in debt reports to support the upgrades, the event-time bond price reaction tends to be greater and the post-event drift tends to be attenuated. For example, the upgrades that are accompanied by a single reason are associated with significant drifts over the (+6, +15) window, while those with multiple reasons (i.e., two, three, or four reasons) are not followed by significant drifts. The results for downgrades are mixed. The downgrades with multiple reasons receive stronger immediate price reactions over the (−2, +2) window, relative to those with a single reason. However, the downgrades with multiple reasons (e.g., two reasons) are still associated with significantly negative bond returns over the (+6, +15) window. While we are cautious in interpreting the results given the small sample for each analysis, we believe that we provide interesting empirical evidence on the effect of cited reasons.

27 Because our approach uses recommendations issued up to three months ago, we expect that this portfolio approach would yield more conservative estimates of portfolio returns than a strategy of using only recommendations issued very recently (e.g., within a month).

28 Debt analysts have greater incentives to issue reports for bonds in which the information demand is likely to be higher (Johnston et al. 2009).

29 Caution is required in interpreting the results because the sample size is small.

30 Note that the analysis is performed at the firm level (rather than at the bond level). If a firm receives multiple bond-level recommendation changes during the quarter, we calculate the average value of the bond-level recommendations (where upgrade = 1, downgrade = −1, reiteration = 0) for the firm and then classify it as an upgrade (downgrade) if the average value is greater (less) than zero, and as a reiteration otherwise. The number of observations with UPGRADE = 1 (DOWNGRADE = 1) is 137 (155), representing 8.4% (9.5%) of the sample.

31 The results are more pronounced for financially distressed firms (i.e., firms with non-investment grade ratings) (untabulated).