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Review of Accounting Studies

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11-07-2018

Manager-analyst conversations in earnings conference calls

Published in: Review of Accounting Studies | Issue 4/2018

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Abstract

Prior research finds that intraday stock prices move considerably during the discussion period of earnings conference calls. In this study, we explore what features of the manager-analyst dialogue during the discussion drive these price movements. We textually analyze the tone of managers and analysts and find that intraday prices react significantly to analyst tone, but not to management tone, for the full duration of the discussion. This effect strengthens when analyst tone is relatively negative. We then present intraday visual evidence that analysts are more neutral than managers over the call and that the tones of both parties drift downward as the call progresses. Overall, our findings illustrate how manager-analyst information exchanges evolve on earnings calls and indicate that analysts are the participants on earnings calls whose comments move stock prices during the discussion.

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See Appendix A for an illustration and Section 2 for more details.

Section 3 assesses in more detail the differential intraday returns effect for positive and negative analyst tone. Our motivation for this test is twofold. First, Davis et al. (2015) argue in their opening section that call participants face increased reputational costs for using negative language in the public earnings call. Second, Huang et al. (2014a) find that investors react more strongly to negative analyst reports than they react to positive reports.

Many institutions are clients of analysts who might act on their call remarks (e.g., Irvine et al. (2006)).

We discuss these additional results further in Section 3.4.

For example, the stock price could rise before the discussion in the presentation section (Matsumoto et al. 2011), which in turn makes analysts more positive on the call. This effect would show up in a two-day return window association test with analyst tone but not in the discussion-period return window. Or analyst tone could have no discussion-period reaction but could be correlated with some future analyst activity, such as a recommendation issued soon after the call. The market, unaware of this correlation, could respond only to the recommendation. This behavior would again show up in the two-day returns test but not in the intraday returns test.

In 2008 I/B/E/S stopped providing a matching table for analysts’ names, banks, and I/B/E/S identifiers in the earnings forecast file. We therefore limit our individual analyst earnings forecast tests to the years 2002-2007. Also, because our matching process relies on analyst and broker names from the conference call transcripts, and because these names do not always perfectly align with the I/B/E/S matching database (due to abbreviations, misspellings, etc.), we cannot match every analyst to I/B/E/S.

See http://www.nd.edu/~mcdonald/word_lists.html.

Larcker and Zakolyukina (2012) also focus on CEOs and CFOs. Including COOs and vice presidents (as well as including all company representatives on the call, regardless of their title) does not affect the mean or standard deviation of the management tone metric, nor does it affect our intraday returns results.

One potential concern with our tone measures is that they depend on the number of positive and negative words, not on the total number of words spoken by the analyst. Careful use of firm- and analyst-fixed effects partially control for such heterogeneity; however, there could still be within-firm variation in total words spoken on the call over time. Therefore, in untabulated tests, we construct alternative measures of tone that are identical to Eq. 1, except use as the denominator total words spoken by managers or analysts (depending on the measure). The intraday return results with this measure are similar in terms of sign, magnitude, and p-values. We also control for call length throughout our analysis.

Mayew (2008, p. 632) argues that, although management would like to favor pliant analysts on the call, capital market pressures can force management to give airtime to good independent analysts. In addition, Groysberg et al. (2011) document that analysts have strong incentives to be competent and accurate. These considerations further justify our decision to aggregate all analysts on the call.

As noted earlier, this sample only includes calls through 2007 for earnings forecasts. I/B/E/S stopped providing the analyst name to I/B/E/S ID matching file for earnings forecasts after this time.

The focus on earnings as the metric of financial information is standard in the empirical disclosure literature for two reasons: first, more disaggregated financial items (such as provisions) may vary in importance across firms; earnings by contrast represent a common and important aggregate performance measure for all firms. Second, there exist well-studied measures of analysts’ expected earnings, thus allowing one to compute earnings news.

For example, Altinkilic and Hansen (2009) argue that momentum effects could arise from pre-event-day news releases.

This data set is the focus of several studies, including Irvine et al. (2006), who describe it in detail.

Since we cannot directly uncover the covariance structure of the error terms, we have ensured that our results obtain with alternative clustering methods, including clustering by firm and two-way clustering by firm and year (Gow et al. 2010).

While a larger firm is likely to have more remarks, we assume that we can compare individual remarks across firms.

We find similar tone patterns across market-value deciles and the ten most populous two-digit SICs in our sample. Note that the very first remark by management is often introductory and thus more neutral than subsequent remarks. Also, the first analyst typically congratulates management on the quarter and is thus more positive than future analyst remarks.

By contrast, Jung et al. (2017, Table 6) find significant differences in the dialogue of sell- and buy-side analysts in the discussion period. For example, relative to sell-side analysts, buy-side analysts receive shorter replies from CEOs by a magnitude of about 10 words, on average. Also, sell-side analysts, who are the focus of this study, outnumber buy-side analysts by about a factor of 20 in the discussion period.

As described in Section 2, our future analyst revision measures are conservative because a significant portion of analysts make revisions on the conference call date and we measure future revisions from the end of the call date forward. This means that our measurement strategy will bias against finding significance.

To allow us to better interpret the economic significance of our results, we use level changes in EPS forecasts; however, our results are similar in sign and statistical significance when we scale EPS by stock price at the quarter’s fiscal end date. Also note that firm-fixed effects control for across-firm variation in EPS.

Another feature of our recommendation analysis is that we use OLS, which assumes that the difference between 1 and 0 (upgrade versus no change) is of the same economic magnitude as the difference between 0 and − 1 (no change versus downgrade). While this appears to be a reasonable assumption, we nonetheless replicate the recommendation analysis with ordered and multinomial logit regressions and find significance for the analyst tone measure. However, econometric and computational limitations prevent us from including analyst-firm fixed effects in these logit regressions (Greene 2004). We therefore do not tabulate these results. We also replicate the analysis and find similar results in sign and statistical significance for the full five-point recommendation scale in I/B/E/S, which ranges from sell to strong buy.

A potential concern is that returns measured during the Q&A may capture some residual trading from the presentation. Our analysis of the 30-minute period after the call helps to ensure that our findings are not driven by such residual information. In addition, we include management presentation tone as a regressor in all of our returns tests, which will eliminate any effect due to (potentially latent) trades based on the presentation tone.

An alternative explanation for the substantial returns results for analyst recommendations is offered by Loh and Stulz (2010), who find that these recommendations overlap with concurrent information events.

We recognize that investors may be unable to perfectly predict analysts’ future earnings forecasts, price targets, and recommendations. We therefore use the actual realization of these outputs as the best available proxies.

Our findings are similar when using an indicator for recommendation upgrades (as opposed to using the full five-point scale for recommendations).

There are significant differences in the nature of our information event and that studied by Tetlock (2007); we cannot execute his tests literally. For example, our interval duration, which we motivate using the argument in Tetlock et al. (2008, p. 1452), is different than that of Tetlock (2007). Furthermore, we use three future intervals, while Tetlock (2007) uses five. However, in untabulated tests, we find that the much longer window of daily returns is also positively correlated with analyst tone, providing further evidence of no reversals.

We acknowledge that some intraday time-stamps in I/B/E/S may be inaccurate. Bradley et al. (2014) find that recommendation time-stamps cannot be corrected without manually checking each analyst report, and therefore we do not attempt to adjust the times. However, they find that in their limited sample, time-stamps are delayed on average by 2.4 hours. We thus use three-hour windows when eliminating calls with concurrent analyst revisions.

Two realities are possible for analyses three and four: it could be that there is in general more information released on the calls, which might lead to stronger tone effects, or that the additional information substitutes for information on the call, which might lead to weaker tone effects.

One exception is our sample split on median management Q&A financial words: the analyst tone effect is marginally larger in the above-the-median sample (coefficient of 0.119 versus 0.086; 10% level).

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Title: Manager-analyst conversations in earnings conference calls
Publication date: 11-07-2018
Published in: Review of Accounting Studies / Issue 4/2018
Print ISSN: 1380-6653
Electronic ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-018-9453-3

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