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Do record earnings affect market reactions to earnings news?

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Abstract

We find evidence that a firm’s record earnings influence market response to earnings news. Our results show that the proximity of the firm’s earnings to its record earnings leads to investors’ underreaction following earnings announcements, exacerbating post-earnings-announcement drift. Such biased behavior is more pronounced in low-growth firms and firms with low institutional ownership. Meanwhile, analysts are not subject to this anchoring bias when a firm’s earnings are close to its record earnings. Overall, we find that a firm’s record earnings play an important role as an anchor when market participants evaluate the firm’s earnings news.

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Notes

  1. See the Wall Street Journal article “Amazon Posts Another Blockbuster Profit” released on July 28, 2016, at http://www.wsj.com/articles/amazon-posts-another-blockbuster-profit-1469736704.

  2. See the Wall Street Journal article “Tyson Foods Projects Record Profits; Shares Hit All-Time High” released on February 5, 2016, at http://www.wsj.com/articles/tyson-foods-beats-profit-expectations-boosts-outlook-1454678628.

  3. In the literature, a measure of standardized unexpected earnings (SUE) is typically estimated in two ways, depending on how to calculate predicted earnings. First, it is calculated as the difference between actual earnings and earnings predicted by a seasonal random walk model (Bernard and Thomas 1990; Battalio and Mendenhall 2005). Second, it is measured as the difference between actual earnings and the median value of analysts’ forecast estimates (Livnat and Mendenhall 2006).

  4. Several financial websites such as MarketWatch (https://www.marketwatch.com/investing/stock), Morningstar (https://financials.morningstar.com), and NASDAQ (http://www.nasdaq.com), provide 5- or 10-year financial data including historical net income and earnings per share (EPS). Given this data availability, we exclude firms whose record earnings did not change for more than 10 years (40 fiscal quarters).

  5. Prior literature shows that different anchors lead to different reactions from investors or managers and subsequent return patterns. For instance, in addition to stock price anchors, Campbell and Sharpe (2009) show that experts’ consensus forecasts of macroeconomic data are biased towards the values of the previous month. Dougal et al. (2015) find that a firm’s borrowing rate on its most recent loan plays a role as an anchor for the firm’s borrowing costs on new loans. These findings reveal that anchoring effects heavily rely on types of anchors used by investors or managers, rather than cross-sectional variations in equity markets or corporate conditions. Since record earnings are a new anchor that has not been investigated in the literature, whether or how investors react to this anchor could still be an empirical issue. We thank our referee for bringing up this point.

  6. Many studies attempt to find out why PEAD appears. Bernard and Thomas (1989) propose several possible explanations on the occurrence of PEAD, such as the existence of transaction costs or flawed asset pricing models. Some studies suggest behavioral explanations, such as investor conservatism (Barberis et al. 1998) and investor overconfidence (Daniel et al. 1998). Despite these efforts, there is no clear explanation about the cause of the drift in the literature (Jacob et al. 2000).

  7. The COMPUSTAT database starts from 1961. Therefore, due to the unavailability of data, we do not consider record high earnings before 1961 for our analysis.

  8. We separately analyze firms with RH ratios that are equal to or greater than one in Sect. 5.2.

  9. In unreported tables, we additionally repeat the analysis after (1) including all observations and (2) excluding firms whose record earnings last for more than 5 years. Overall, the results remain unchanged in terms of magnitude and significance.

  10. The RH ratio is lower than the mean values of the nearness of a stock price to its reference prices reported in Lee and Piqueira (2017). They show that the average distance of the stock price to its 52-week high is 83%, while the average distance to its historical high is 49%. Such differences could be attributed to the frequency of data. While the distance of a stock price to its past high price is measured from relatively high-frequency market data, the RH ratio is calculated based on quarterly financial statements data.

  11. See Fama and French (2015) for the estimation of factor loadings.

  12. We define as day 0 the next day following an earnings announcement in case of after-hours announcements. This treatment mitigates the concern that return on day t + 1 indicates earnings surprises, especially when a majority of firms tend to release earnings after trading hours. For robustness checks, we re-estimate returns for the same time windows starting day t + 2. Results remain significant, although the magnitudes of cumulative abnormal returns are smaller.

  13. To check whether our results are robust to the use of different benchmarks in computing CARs, we repeat the analysis using CARs based on CRSP equal-weighted market returns and Fama–French (1993) size and market-to-book adjusted returns. The results are unchanged in terms of significance (unreported). We mainly report CARs based on CRSP value-weighted market returns hereafter. Results with different CARs are available upon request.

  14. For robustness checks, we repeat the analysis for firms with negative record earnings. In unreported tables, we find that CARs are higher when firms’ earnings are closer to their record earnings (low RH portfolio), but the return difference between the highest and lowest RH portfolios is not statistically significant. When a firm’s earnings are the same as its negative record earnings, subsequent returns increase sharply and are significantly different from those for the highest and lowest RH portfolios. When current earnings hit a new record, subsequent returns are significantly higher than those for the highest RH portfolios, while the returns are not significantly different from those for the lowest RH portfolios. Overall, the results are robust with negative record earnings but relatively weaker compared to the results based on positive record earnings.

  15. We also perform the test for firms with negative record low earnings and record low ratios greater than one. The results are consistent with our findings in this section (unreported).

  16. We also repeat the tests using average 52-week high ratios for different event windows around earnings announcements. Overall results are unchanged.

  17. Since the sentiment index is constructed on a monthly basis, we still estimate Eq. (4) with year-quarter fixed effects in this section. We also run the regression without year-quarter fixed effects, given the possibility that the sentiment effect could be washed out due to the inclusion of time fixed effects. It turns out that the results without year-quarter fixed effects are similar to those in Table 10.

References

  • Baker M, Wurgler J (2006) Investor sentiment and the cross-section of stock returns. J Finance 61:1645–1680

    Google Scholar 

  • Baker M, Pan X, Wurgler J (2012) The effect of reference point prices on mergers and acquisitions. J Financ Econ 106:49–71

    Google Scholar 

  • Ball R, Brown P (1968) An empirical evaluation of accounting income numbers. J Account Res 6:159–178

    Google Scholar 

  • Barberis N, Shleifer A, Vishny R (1998) A model of investor sentiment. J Financ Econ 49:307–343

    Google Scholar 

  • Basu S (1983) The relationship between earnings’ yield, market value and return for NYSE common stocks: further evidence. J Financ Econ 12:129–156

    Google Scholar 

  • Battalio R, Mendenhall R (2005) Earnings expectations, investor trade size, and anomalous returns around earnings announcements. J Financ Econ 77:289–319

    Google Scholar 

  • Bernard VL, Thomas JK (1989) Post-earnings-announcement drift: delayed price response or risk premium? J Account Res 27:1–36

    Google Scholar 

  • Bernard VL, Thomas JK (1990) Evidence that stock prices do not fully reflect the implications of current earnings for future earnings. J Account Econ 13:305–341

    Google Scholar 

  • Birru J (2015) Psychological barriers, expectational errors, and underreaction to news. Working paper. Ohio State University

  • Boni L, Womack L (2006) Analysts, industries, and price momentum. J Financ Quant Anal 41:85–109

    Google Scholar 

  • Campbell S, Sharpe S (2009) Anchoring bias in consensus forecasts and its effect on market prices. J Financ Quant Anal 44:369–390

    Google Scholar 

  • Chu J, Dechow P, Hui KW, Wang AK (2019) Maintaining a reputation for consistently beating earnings expectations and the slippery slope to earnings manipulation. Contemp Account Res 36:1966–1998

    Google Scholar 

  • Daniel K, Hirshleifer D, Subrahmanyam A (1998) A theory of overconfidence, self-attribution, and security market under- and overreactions. J Finance 53:1839–1886

    Google Scholar 

  • Degeorge F, Patel J, Zeckhauser R (1999) Earnings management to exceed thresholds. J Bus 72:1–33

    Google Scholar 

  • DeHaan E, Madsen J, Piotroski JD (2017) Do weather-induced moods affect the processing of earnings news? J Account Res 55:509–550

    Google Scholar 

  • Ditmar A, Duchin R, Zhang S (2019) The timing and consequences of seasoned equity offerings: A regression discontinuity approach. J Financ Econ, forthcoming

  • Dougal C, Engelberg J, Parsons CA, Van Wesep ED (2015) Anchoring on credit spreads. J. Finance 70:1039–1080

    Google Scholar 

  • Driessen J, Lin TC, Van Hemert O (2013) How the 52-week high and low affect option-implied volatilities and stock return moments. Rev Finance 17:369–401

    Google Scholar 

  • Fama E, French K (1993) Common risk factors in the returns of stocks and bonds. J Financ Econ 33:3–56

    Google Scholar 

  • Fama E, French K (2015) A five-factor asset pricing model. J Financ Econ 116:1–22

    Google Scholar 

  • Feng L, Seasholes M (2005) Do investor sophistication and trading experience eliminate behavioral biases in financial markets? Rev Finance 9:305–351

    Google Scholar 

  • Foster G, Olsen C, Shevlin T (1984) Earnings releases, anomalies, and the behavior of security returns. Account Rev 59:574–603

    Google Scholar 

  • George T, Hwang CY (2004) The 52-week high and momentum investing. J Finance 59:2145–2175

    Google Scholar 

  • George TJ, Hwang CY, Li Y (2015) Anchoring, the 52-week high and post earnings announcement drift. Working paper. University of Houston

  • George TJ, Hwang CY, Li Y (2018) The 52-week high, q-theory, and the cross section of stock returns. J Financ Econ 128:148–163

    Google Scholar 

  • Grinblatt M, Keloharju M (2001) What makes investors trade? J Finance 51:589–616

    Google Scholar 

  • Heath C, Huddart S, Lang M (1999) Psychological factors and stock option exercise. Q J Econ 114:601–627

    Google Scholar 

  • Hong H, Stein J (1999) A unified theory of underreaction, momentum trading and overreaction in asset markets. J Finance 54:2143–2184

    Google Scholar 

  • Hong H, Lim T, Stein J (2000) Bad news travels slowly: size, analyst coverage, and the profitability of momentum strategies. J Finance 55:265–295

    Google Scholar 

  • Hong X, Jordan B, Liu M (2015) Industry information and the 52-week high effect. Pac Basin Financ J 32:111–130

    Google Scholar 

  • Huddart S, Lang M, Yetman MH (2009) Volume and price patterns around a stock’s 52-week highs and lows: theory and evidence. Manag Sci 55:16–31

    Google Scholar 

  • Ikenberry D, Lakonishok J, Vermaelen T (1995) Market underreaction to open market share repurchases. J Financ Econ 39:181–208

    Google Scholar 

  • Ivkovic Z, Jegadeesh N (2004) The timing and value of forecast and recommendation revisions. J Financ Econ 73:433–463

    Google Scholar 

  • Jacob J, Lys T, Sabino J (2000) Autocorrelation structure of forecast errors from time-series models: alternative assessments of the causes of post-earnings announcement drift. J Account Econ 28:329–358

    Google Scholar 

  • Jegadeesh N, Kim J (2006) Value of analyst recommendations: international evidence. J Financ Mark 9:274–309

    Google Scholar 

  • Jegadeesh N, Kim J (2010) Do analysts herd? An analysis of recommendations and market reactions. Rev Financ Stud 23:901–937

    Google Scholar 

  • Jegadeesh N, Kim J, Krisch S, Lee C (2004) Analyzing the analysts: when do recommendations add value? J Finance 59:1083–1124

    Google Scholar 

  • Kasznik R, McNichols MF (2002) Does meeting earnings expectations matter? Evidence from analyst forecast revisions and share prices. J Account Res 40:729–759

    Google Scholar 

  • Lakonishok J, Shleifer A, Vishny R (1994) Contrarian investment, extrapolation, and risk. J Finance 49:1541–1578

    Google Scholar 

  • LaPorta R, Lakonishok J, Schleifer A, Vishny R (1997) Good news for value stocks: further evidence on market efficiency. J Finance 52:859–874

    Google Scholar 

  • Lee E, Piqueira N (2017) Short selling around the 52-week and historical highs. J Financ Mark 33:75–101

    Google Scholar 

  • Li J, Yu J (2012) Investor attention, psychological anchors, and stock return predictability. J Financ Econ 104:401–419

    Google Scholar 

  • Li F, Lin C, Lin TC (2020) Salient anchor, limited attention, and analyst recommendation changes. Working paper. Deakin University

  • Livnat J, Mendenhall R (2006) Comparing the post-earnings announcement drift for surprises calculated from analyst and time series forecasts. J Account Res 44:177–205

    Google Scholar 

  • Ljungqvist A, Wilhelm WJ (2005) Does prospect theory explain IPO market behavior? J Finance 60:1759–1790

    Google Scholar 

  • Loughran T, Ritter J (2002) Why don’t issuers upset about leaving money on the table in IPOs? Rev Financ Stud 15:413–444

    Google Scholar 

  • Ma Q, Whidbee DA, Zhang W (2019) Acquirer reference prices and acquisition performance. J Financ Econ 132:175–199

    Google Scholar 

  • Mian GM, Sankaraguruswamy S (2012) Investor sentiment and stock market response to earnings news. Account Rev 87:1357–1384

    Google Scholar 

  • Myers JN, Myers LA, Skinner DJ (2007) Earnings momentum and earnings management. J Account Audit Finance 22:249–284

    Google Scholar 

  • Poteshman AM, Serbin V (2003) Clearly irrational financial market behavior: evidence from the early exercise of exchange traded stock options. J Finance 58:37–70

    Google Scholar 

  • Sapp TA (2011) The 52-week high, momentum, and predicting mutual fund returns. Rev Quant Finance Account 37:149–179

    Google Scholar 

  • Skinner DJ, Sloan RG (2002) Earnings surprises, growth expectations, and stock returns or don’t let an earnings torpedo sink your portfolio. Rev Account Stud 7:289–312

    Google Scholar 

  • Stambaugh RF, Yu J, Yuan Y (2012) The short of it: investor sentiment and anomalies. J Financ Econ 104:288–302

    Google Scholar 

  • Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Science 185:1124–1131

    Google Scholar 

  • White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48:817–838

    Google Scholar 

Download references

Acknowledgements

We thank the editor Cheng-Few Lee, an anonymous referee, Jared DeLisle, Tunde Kovacs, and participants of the 2017 Financial Management Association Annual Meeting and the 2017 Southern Finance Association Annual Meeting for their helpful comments and suggestions.

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Authors and Affiliations

  1. University of Massachusetts Lowell, 72 University Avenue, Lowell, MA, 01854, USA

    Juwon Jang & Eunju Lee

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Correspondence to Eunju Lee.

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Appendices

Appendix 1: Sample analysis

This table reports the breakdown of the sample based on the signs of record earnings and the magnitudes of RH ratios.

Variable

Number of firm-quarter observations

 

HEPSt > 0

132,924

96.45%

 RHratiot < 1

123,124

92.63%

 RHratiot = 1

1144

0.86%

 RHratiot > 1

8656

6.51%

HEPSt < 0

4896

3.55%

 RHratiot < 1

691

14.11%

 RHratiot = 1

111

2.27%

 RHratiot > 1

4094

83.62%

Total

137,820

100%

Appendix 2: Variable definitions

Variable

Definition

bidaskt,t + n

Bid-ask spread, the difference between bid and ask prices scaled by the bid-ask midpoint, averaged over n days

bmratioq

Book value of equity (book value of stockholder’s equity plus balance sheet deferred taxes minus the book value of preferred stock) divided by the market value of equity at the end of quarter q

CARt + 1, t + n

Cumulative abnormal return, which is calculated as the sum of stock returns minus benchmark returns from day t + 1 to day t + n. The benchmark returns are CRSP value-weighted market returns

EPSq

Earnings per share (EPS) in quarter q

Fcerrt − 1

Lagged value of analysts’ forecast errors, which are defined as the absolute values of differences between median forecasts made by analysts within 2 weeks following earnings announcements and actual earnings for the following quarter

HEPSq

Record high EPS in a given firm’s history at the beginning of quarter q

levq

The sum of long-term debt and debt in current liabilities divided by total assets at the end of quarter q

lnmcapq

The logarithm of market capitalization, which is calculated as monthly stock price times the number of shares outstanding at the end of quarter q

PEratioq

Stock price at the end of quarter q divided by quarter-q earnings per share

rett

Daily stock return

RHratioq

Record high (RH) ratio, which is current EPS divided by record high EPS at the beginning of quarter q

RH_H

A dummy variable that equals one if a firm is in the top two RH quintiles and zero otherwise

RH_L

A dummy variable that equals one if a firm is in the bottom two RH quintiles and zero otherwise

RLratioq

Record Low (RL) ratio, which is record low EPS at the end of the previous quarter divided by current EPS

ROAq

Operating income before depreciation divided by book value of assets at the end of quarter q

RRratioq

Record range ratio, which is the difference between record high earnings and current earnings divided by the difference between record high and low earnings at the beginning of quarter q

σt,t + n

Difference between the high and low price divided by the high price averaged over n days

Sentm

Monthly sentiment index constructed by Baker and Wurgler (2006). This is established based on the first principal component of five sentiment proxies—value-weighted dividend premium, first-day returns on IPOs, IPO volume, closed-end fund discount, and new equity issues. These proxies are orthogonalized in terms of several macroeconomic indicators. Please see Baker and Wurgler (2006) for the detailed description

SUEq

Standardized unexpected earnings, calculated as the difference between actual earnings and the median value of analysts’ forecasts, scaled by quarter-end stock price

SUE_H

A dummy variable that equals one if a firm is in the top two SUE quintiles and zero otherwise

SUE_L

A dummy variable that equals one if a firm is in the bottom two SUE quintiles and zero otherwise

turnovert,t + n

Daily trading volume scaled by the number of shares outstanding averaged over n days

52wkHt

Daily stock price divided by the highest price achieved within the past 52 weeks

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Jang, J., Lee, E. Do record earnings affect market reactions to earnings news?. Rev Quant Finan Acc 56, 1259–1287 (2021). https://doi.org/10.1007/s11156-020-00927-4

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