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Managers’ use of humor on public earnings conference calls

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Abstract

Despite the prevalence and importance of humor in interpersonal communication, the disclosure literature is silent on the use of humor in the context of corporate communication. Using a sophisticated machine learning algorithm, we identify managers’ successful uses of humor during public earnings conference calls. When managers use humor on an earnings call, stock market returns and analyst forecast revisions following the call are more positive, primarily because of a muted response to negative earnings news. Consistent with managers’ successful use of humor being a favorable signal of future firm performance, we find no evidence of a return reversal over the subsequent quarter, and managers’ use of humor predicts more favorable news at the subsequent quarter’s earnings announcement. Our study provides new evidence on the use of humor in corporate disclosures, and our findings indicate that humor can meaningfully influence the market response to public earnings conference calls.

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Data Availability

All data used in this study are available in the databases referenced in the text.

Notes

  1. The power and importance of humor for managers is taught in a popular MBA elective at Stanford Graduate Business School (Stanford Graduate Business School 2017).

  2. We acknowledge that our proxy captures successful uses of humor with error. Laughter could result from something other than humor (e.g., awkward laughter), but our manual review of the conference call audio files suggests we captured intentional and successful attempts at humor. Further, any measurement error due to unidentified instances of humor, awkward laughter, or courtesy laughter is unlikely to relate systematically to our outcome measures.

  3. For additional examples of humor in conference calls, refer to Appendix A.

  4. We also performed an out-of-sample test on a random sample of 100 conference call audio files with laughter coded by Mechanical Turk (Mturk) workers and obtained precision of 100 percent and recall of 37 percent.

  5. Jennings et al., (2022) show that measurement error can bias in favor of falsely rejecting a true null hypothesis in the presence of high-dimensional fixed effects. We therefore re-estimate our analyses excluding fixed effects and find that our results are robust to this alternative specification.

  6. We use the absolute value of negative earnings surprises (|NegEarnSurp|), so each measure of firm news captures the magnitude of the positive or negative earnings news.

  7. While our primary tests utilize a logistic regression model, our results are robust to estimating a linear probability model using OLS.

  8. In an untabulated test, we find that managers use humor in approximately 13 percent of fourth quarter earnings conference calls, which is significantly greater than their use of humor in 11.5 percent of other quarterly earnings conference calls (p < 0.05).

  9. In an untabulated test, we estimate a model with fully standardized coefficients to capture the relative importance of the determinants in our model. The results of this test indicate that LagHumor_Manager, ln(#Partic), AvgRec, Tone_Manager, |NegEarnSurp|, Humor_AnalystFirst, and Momentum are the most significant determinants, followed by NegGuidance, Tone_Analyst, and FourthQuarter.

  10. As an additional control for the general sentiment at the time of the call, we include the tone of the firm’s earnings press release, which we retrieve from RavenPack. Our inferences are robust to the inclusion of this additional control variable (untabulated).

  11. In an untabulated test, we find that the sum of the coefficients on |NegEarnSurp| and Humor_Manager × |NegEarnSurp| is not significantly different from zero.

  12. As an additional robustness test, we run a fully interacted model where humor is interacted with each of the independent variables. Using this specification, we continue to find evidence of a muted analyst reaction to negative firm news (p < 0.05).

  13. We re-run these analyses using returns over the two to 60 trading days (i.e., approximately one calendar quarter) following the earnings conference call and similarly find no evidence of returns reversal in this window (untabulated).

  14. Following Clement and Tse (2003, 2005), we calculate these abnormal variables as the raw value minus the minimum value across all other analysts following firm i in quarter q, with this difference scaled by the range in the values across all other analysts following firm i in quarter q.

  15. To control for time-invariant analyst characteristics (e.g., analyst personality or natural communication skills), we rerun Eq. (6) using analyst fixed effects, instead of analyst-firm fixed effects. We also rerun Eq. (6) without any fixed effects. Our inferences are unchanged.

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Author information

Authors and Affiliations

  1. Arizona State University, Tempe, AZ, USA

    Andrew C. Call

  2. London Business School, London, UK

    Rachel W. Flam

  3. Brigham Young University, Provo, UT, USA

    Joshua A. Lee

  4. Texas A&M University, College Station, TX, USA

    Nathan Y. Sharp

Authors
  1. Andrew C. Call
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  2. Rachel W. Flam
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  3. Joshua A. Lee
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  4. Nathan Y. Sharp
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Corresponding author

Correspondence to Nathan Y. Sharp.

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Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

We appreciate helpful comments from Kris Allee, Lisa Anderson, Justin Blann, Jim Cannon, Ryan Cating, Dane Christensen, Elizabeth Cowle, Dieudonne Dusenge, Scott Emett, Andrew Grice, Zhang Huai, Rachel Martin, Chris Park, Lynn Rees, Anup Srivastava (discussant), Sam Yam, and workshop participants at the 2019 AAA Annual Meeting, the University of Kentucky, Kent State University, Nanyang Technological University, National University of Singapore, The University of Adelaide, and Utah State University.

Appendices

Appendix A

Examples of Conference Call Humor.

Chipotle Mexican Grill Q2 2011 (July 19, 2011)

Montgomery Moran – co-chief executive officer, secretary, and director

Our sales have gotten so much better. But when sales increase that much, sometimes we just don’t keep pace with the sort of techniques that we’re capable of in throughput to keep up with the greater sales. We see that we are … we see our capabilities in what some of our best stores do. And we still have restaurants … In fact, I just saw a record the other day came in from a restaurant that achieved 350 transactions in one hour.

John Hartung – chief financial officer and principal accounting officer

That’s [Sharon’s] restaurant. It’s very notable.

Montgomery Moran

Yes. So, well if you’re finding that one to be slow, Sharon, I don’t have much for you. [laughter].

Cimarex Energy First Quarter 2013 (May 7, 2013)

Brian Gamble, analyst, Simmons & Company International

Hey, everybody. I wanted to focus on the production side for a minute, I think Paul had alluded to it, the continued wide, I guess, train-sized gap you've got for a low-end and high-end production Is it safe to assume –.

Paul Korus – chief financial officer and senior vice president

That was a truck. That wasn’t a train; it was a truck. [laughter].

Brian Gamble

I'm sorry, Paul, I didn’t mean to put words in your mouth. We will call it a truck-sized hole.

Arista Networks Inc. Second Quarter 2016 (August 4, 2016)

Steve Milunovich – analyst, UBS

Regarding switching Cisco’s reported fairly strong data center orders last quarter, Juniper’s released the QFX10000 spine switch, are you seeing any change in the competitive environment or pricing as a result of this?

Jayshree Ullal – president, chief executive officer, and director

The short answer, Steve, is no.

Steve Milunovich

What is the long answer?

Jayshree Ullal

No, twice. [laughter] No, kidding aside, I think I’ve always said this, Steve, and I’ll reiterate that our competitive landscape has always been extremely strong and dynamic.

Appendix B. Variable Definitions

Variable

Definition

Firm Variables:

  AnalystFolli,q

The number of analysts providing an earnings per share for firm i in quarter q

  AvgAccuracyi,q

The mean of Accuracya,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgBSizei,q

The mean of BSizea,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgCompaniesi,q

The mean of Companiesa,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgReci,q

The mean of Reca,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgFirmExpi,q

The mean of FirmExpa,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgForFreqi,q

The mean of ForFreqa,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgGenExpi,q

The mean of GenExpa,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgIndustriesi,q

The mean of Industriesa,i,q for all analysts participating in the conference call of firm i in quarter q

  AvgRecHorizoni,q

The mean of RecHorizona,i,q for all analysts participating in the conference call of firm i in quarter q

  BTMi,q

The book-to-market ratio of firm i in quarter q, calculated as the book value of common equity divided by the market value of equity (MVEi,q) as of the fiscal quarter-end of firm i in quarter q

  CAR[0, + 1]i,q

The cumulative abnormal size-decile adjusted return for firm i during the [0, + 1] trading day window surrounding firm i’s conference call in quarter q

  CAR[+ 2, + 30]i,q

The cumulative abnormal size-decile adjusted return for firm i during the [+ 2, + 30] trading day window following firm i’s conference call in quarter q

  ChgForecasti,q

The change in the consensus analyst forecast of firm i’s earnings per share in quarter q + 1. The consensus forecast before (after) the conference call includes the latest forecasts of all analysts following firm i as of 1 trading day prior to (10 trading days following) the conference call date

  EarnSurpi,q

The earnings surprise for firm i in quarter q, calculated as the actual IBES earnings per share for firm i in quarter q less the mean consensus IBES analyst estimate of earnings per share for firm i in quarter q, with this difference scaled by the stock price for firm i two days prior to the conference call date in quarter q

  FourthQuarteri,q

An indicator variable equal to 1 if the conference call of firm i in quarter q is the firm’s fourth quarter and equal to 0 otherwise

  FutureEarnSurpi,q

The earnings surprise for firm i in quarter q + 1, calculated as the actual IBES earnings per share for firm i in quarter q + 1 less the mean consensus IBES analyst estimate of earnings per share for firm i in quarter q + 1 prior to the quarter q earnings announcement date, with this difference scaled by the stock price for firm i two days prior to the conference call date in quarter q + 1

  Humor_AnalystFirsti,q

An indicator variable equal to 1 if an analyst elicits laughter during the conference call of firm i in quarter q before a manager elicits laughter during the conference call and equal to 0 otherwise

  Humor_Analysti,q

An indicator variable equal to 1 if an analyst elicits laughter during the conference call of firm i in quarter q and equal to 0 otherwise

  Humor_Manageri,q

An indicator variable equal to 1 if a manager elicits laughter during the conference call of firm i in quarter q and equal to 0 otherwise

  LagHumor_Analysti,q

An indicator variable equal to 1 if an analyst elicits laughter during the previous conference call of firm i prior to quarter q and equal to 0 otherwise

  LagHumor_Manageri,q

An indicator variable equal to 1 if a manager elicits laughter during the previous conference call of firm i prior to quarter q and equal to 0 otherwise

  Momentumi,q

The cumulative abnormal size-decile adjusted return for firm i during the [-30,-2] trading window prior to firm i’s conference call in quarter q

  MVEi,q

The market value of equity of firm i in quarter q, calculated as the number of shares outstanding multiplied by the stock price as of the fiscal quarter-end of firm i in quarter q

  |NegEarnSurpi,q|

The absolute value of EarnSurpi,q if EarnSurpi,q is less than 0 and equal to 0 otherwise

  NegGuidancei,q

An indicator variable equal to 1 if firm i releases guidance below analyst consensus for quarter q + 1 during the [-1, + 1] window surrounding firm i’s conference call in quarter q and equal to 0 otherwise

  #Partici,q

The number of analysts who ask questions during the conference call of firm i in quarter q

  PosEarnSurpi,q

The absolute value of EarnSurpi,q if EarnSurpi,q is greater than or equal to 0 and equal to 0 otherwise

  PosGuidancei,q

An indicator variable equal to 1 if firm i releases guidance above analyst consensus for quarter q + 1 during the [-1, + 1] window surrounding firm i's conference call in quarter q and equal to 0 otherwise

  RetVoli,q

Daily return volatility for firm i in the three months prior to firm i’s conference call in quarter q

  Tone_Analysti,q

The tone of analyst statements during firm i’s conference call in quarter q. Tone is calculated as the total number of positive words less the total number of negative words scaled by the sum of the number of positive words and negative words using a modified version of the Loughran and McDonald (2011) dictionary, which excludes the words “question” and “questions” from the negative lists

  Tone_Manageri,q

The tone of manager statements during firm i’s entire conference call in quarter q. Tone is calculated as the total number of positive words less the total number of negative words scaled by the sum of the number of positive words and negative words using a modified version of the Loughran and McDonald (2011) dictionary, which excludes the words “question” and “questions” from the negative lists

  WCQ&Ai,q

The number of words spoken during the question-and-answer session of the conference call of firm i in quarter q

Analyst Variables:

  #Callsa,i,q

Analyst a’s participation on other firms’ conference calls, calculated as the number of conference calls for any firm in the 12 months prior to the conference call date for firm i in quarter q in which analyst a asks a question

  #Switchesa,i,q

Number of analyst-manager switches during managers’ interactions with analyst a during firm i’s conference call in quarter q, where an analyst-manager switch is counted for each time the speaker on the conference call switches between a manager and the analyst during a given exchange

  Abn#Callsa,i,q

Abnormal participation of analyst a on other firms’ conference calls, calculated as #Callsa,i,q less the smallest #Callsa,i,q for all analysts participating on the conference call of firm i in quarter q, with this difference scaled by the range in #Callsa,i,q for all analysts participating on the conference call of firm i in quarter q

  Abn#Switchesa,i,q

Abnormal number of analyst-manager switches, calculated as #Switchesa,i,q for analyst a minus the smallest #Switchesa,i,q for all analysts participating on the conference call of firm i in quarter q, with this difference scaled by the range in #Switchesa,i,q for all analysts participating on the conference call of firm i in quarter q

  AbnBSizea,i,q

Abnormal brokerage size of analyst a in quarter q, calculated as BSizea,i,q for analyst a minus the smallest BSizea,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in BSizea,i,q for all analysts following firm i in quarter q

  AbnCompaniesa,i,q

Abnormal number of companies covered by analyst a in quarter q, calculated as Companiesa,i,q for analyst a minus the smallest Companiesa,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in Companiesa,i,q for all analysts following firm i in quarter q

  AbnFirmExpa,i,q

Abnormal firm experience for analyst a following firm i in quarter q, calculated as FirmExpa,i,q for analyst a minus the smallest FirmExpa,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in FirmExpa,i,q for all analysts following firm i in quarter q

  AbnFollowUpa,i,q

Abnormal follow up, calculated as FollowUpa,i,q for analyst a minus the mean of FollowUpa,i,q for all other analysts participating on the conference call of firm i in quarter q

  AbnForFreqa,i,q

Abnormal forecasting frequency of analyst a in quarter q, calculated as ForFreqa,i,q for analyst a minus the smallest ForFreqa,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in ForFreqa,i,q for all analysts following firm i in quarter q

  AbnGenExpa,i,q

Abnormal general experience for analyst a following firm i in quarter q, calculated as GenExpa,i,q for analyst a minus the smallest GenExpa,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in GenExpa,i,q for all analysts following firm i in quarter q

  AbnIndustriesa,i,q

Abnormal industry coverage of analyst a in quarter q, calculated as Industriesa,i,q for analyst a minus the smallest Industriesa,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in Industriesa,i,q for all analysts following firm i in quarter q

  AbnReca,i,q

Abnormal recommendation level of analyst a in quarter q, calculated as Reca,i,q for analyst a minus the smallest Reca,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in Reca,i,q for all analysts following firm i in quarter q

  AbnRecHorizona,i,q

Abnormal horizon of analyst a’s outstanding recommendation for firm i in quarter q, calculated as RecHorizona,i,q for analyst a minus the smallest RecHorizona,i,q for any analyst following firm i in quarter q, with this difference scaled by the range in RecHorizona,i,q for all analysts following firm i in quarter q

  AbnTone_Analysta,i,q

The abnormal tone of analyst a during firm i’s conference call in quarter q, calculated as the tone of analyst a during the conference call of firm i in quarter q less the tone of all other analysts during the conference call of firm i in quarter q. Tone is calculated as the total number of positive words less the total number of negative words scaled by the sum of the number of positive words and negative words using a modified version of the Loughran and McDonald (2011) dictionary, which excludes the words “question” and “questions” from the negative lists

  AbnWC_Analysta,i,q

Abnormal word count of analyst a during firm i’s conference call in quarter q, calculated as WC_Analysta,i,q for analyst a minus the smallest WC_Analysta,i,q for all analysts participating in the conference call of firm i in quarter q, with this difference scaled by the range in WC_Analysta,i,q for all analysts participating in the conference call of firm i in quarter q

  AbnWC_Managera,i,q

Abnormal word count of managers’ responses to questions asked by a during firm i’s conference call in quarter q, calculated as AbnWC_Managera,i,q for analyst a minus the smallest AbnWC_Managera,i,q for all analysts participating in the conference call of firm i in quarter q, with this difference scaled by the range in AbnWC_Managera,i,q for all analysts participating in the conference call of firm i in quarter q

  Accuracya,i,q

The abnormal absolute forecast accuracy of analyst a’s EPS forecast for firm i in quarter q. Abnormal absolute forecast accuracy is calculated as the largest forecast error by any analyst following firm i in quarter q minus the absolute forecast error by analyst a for firm i in quarter q, with this difference scaled by the range in the absolute forecast errors for all analysts following firm i in quarter q

  BSizea,i,q

The brokerage size of analyst a in quarter q, calculated as the total number of analysts employed by the brokerage of analyst a in 12 months prior to the conference call for firm i in quarter q

  Companiesa,i,q

The total number of firms covered by analyst a in the 12 months prior to the conference call for firm i in quarter q

  FirmExpa,i,q

The firm experience of analyst a following firm i in quarter q, calculated as the difference between the conference call date for firm i in quarter q and the date of the first forecast issued by analyst a for firm i, divided by 365

  FollowUpa,i,q

An indicator equal to 1 if analyst a asks a follow-up question on the conference call of firm i in quarter q and equal to 0 otherwise. Follow-up questions are defined as questions asked by an analyst after a different analyst is permitted to ask a question during the conference call

  ForFreqa,i,q

The forecasting frequency of analyst a in quarter q, calculated as the total number of quarterly earnings per share forecasts issued by analyst a for any firm in the 12 months prior to the conference call date for firm i in quarter q

  GenExpa,i,q

The general experience of analyst a following firm i in quarter q, calculated as the difference between the conference call date for firm i in quarter q and the date of the first forecast issued by analyst a for any firm, divided by 365

  Humor_Analysta,i,q

An indicator variable equal to 1 if analyst a elicits laughter during the conference call of firm i in quarter q and equal to 0 otherwise

  Industriesa,i,q

The total number of two-digit SIC industries covered by analyst a in the 12 months prior to the conference call for firm i in quarter q

  LagHumor_Analysta,i,q

An indicator variable equal to 1 if analyst a elicits laughter during the previous conference call of firm i in quarter q and equal to 0 otherwise

  LagPartic_Analysta,i,q

An indicator variable equal to 1 if analyst a asks a question on the previous conference call of firm i prior to quarter q and equal to 0 otherwise

  LeadPartic_Analysta,i,q

An indicator variable equal to 1 if analyst a asks a question on the next conference call of firm i following quarter q and equal to 0 otherwise

  Reca,i,q

Recommendation level of analyst a’s outstanding stock recommendation for firm i in quarter q equal to 5 for strong buy, 4 for buy, 3 for hold, 2 for sell, and 1 for strong sell

  RecHorizona,i,q

The horizon of analyst a’s outstanding recommendation for firm i in quarter q, calculated as the difference between the conference call date for firm i in quarter q minus the date of analyst a’s outstanding recommendation as of the conference call date for firm i in quarter q, with this difference scaled by 365

  Tone_Analysta,i,q

The tone of analyst a during firm i’s conference call in quarter q. Tone is calculated as the total number of positive words less the total number of negative words scaled by the sum of the number of positive and negative words using a modified version of the Loughran and McDonald (2011) dictionary, which excludes the words “question” and “questions” from the negative lists

  WC_Analysta,i,q

Word count of analyst a during firm i’s conference call in quarter q excluding words from sentences preceding laughter elicited by analyst a during the conference call

  WC_Managera,i,q

Word count of managers’ responses to questions asked by analyst a during firm i’s conference call in quarter q

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Call, A.C., Flam, R.W., Lee, J.A. et al. Managers’ use of humor on public earnings conference calls. Rev Account Stud (2023). https://doi.org/10.1007/s11142-023-09764-x

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