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Does the market overweight imprecise information? Evidence from customer earnings announcements

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Abstract

We examine how supplier-firm shareholders respond to the earnings announcements of their major customers to test the moderated confidence hypothesis, which predicts overreaction to imprecise signals. In our setting, the moderated confidence hypothesis predicts that supplier shareholders will overreact to customer earnings news because that news contains imprecise information about the suppliers’ future cash flows. We find evidence that supplier earnings announcement abnormal returns are negatively correlated with supplier abnormal returns at the earlier customers’ earnings announcements, consistent with supplier overreaction. We also find evidence that the overreaction declines with the strength of the economic ties between the supplier and the customer.

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Notes

  1. Note that our definition of imprecision of customer’ news is with respect to the supplier’s future cash flows. The imprecision can be referred to both (i) noise in the relation between the fundamentals of the customer and the fundamentals of the supplier and (ii) noise in the customer’s own earnings. Our paper focuses on the former. We use the economic link between a supplier and its customer to reflect the precision in the customers’ news with respect to the supplier’s future cash flows.

  2. See Hirshleifer et al. (2011) for another theory that can explain both under and overreactions in the context of earnings news.

  3. Daniel et al. (1998) predict that investors will overestimate the precision of self-generated information, resulting in overreactions to private signals. The moderated confidence hypothesis predicts investors will overreact to imprecise information. Both theories suggest overreaction is related to imprecision. In the supplier chain’s information-transfer setting, investors need to conduct private information search when evaluating the implication of customer’s earnings to supplier’s performance. Accordingly, from the overreactions-to-private-signals point of view, customer earnings can be considered as private signals for supplier’s performance. This paper focuses on the perspective of information precision rather than private versus public signals.

  4. Specifically, they find that the stock prices of a firm’s blockholder underreact to the firm’s earnings news (a firm’s earnings is precise with respect to its blockholder’s earnings) but the stock prices of the firm overreact to its blockholder’s earnings news (a blockholder’s earnings is imprecise with respect to its firm’s earnings).

  5. We partition the sample into five portfolios based on the supplier’s stock price reaction to the customer’s earnings announcement and then observe the suppliers’ returns during their subsequent earnings announcements.

  6. In a related study, Ramnath (2002) finds that investors underreact to the first earnings announcement of the quarter in a given industry.

  7. Thomas and Zhang (2008) state: “Our review of the behavioral finance literature suggests that while different theories can explain different aspects of our results, it is difficult to combine those theories in a meaningful way.” (p. 938).

  8. Unlike real coins, these coins do not have a 50 % chance of landing on tails. Some coins have a greater likelihood of landing on tails than other coins. Participants in the experiment do not know which coins have the higher likelihood of landing on tails; they must use the information given to estimate which coins will do better than others.

  9. The earnings announcement of the firm provides precise information to the market regarding the blockholder’s profitability, so the stock prices of the blockholder underreact. On the other hand, the earnings information of the blockholders only has vague (imprecise) implications for the firm’s profitability; according the moderated confidence hypothesis, the stock prices of the firm overreact to the blockholder’s earnings announcement.

  10. This is likely because demand driven effects from customer to supplier are clearer than from supplier to customer. When the end users of a product reduce their consumption, the customer firm’s earnings will be affected, which will then affect the supplier’s earnings. It is much more difficult to imagine a scenario in which a shock in demand for the product affects the supplier’s earnings before it affects the customer firm’s earnings.

  11. Although the FASB rules do not require the disclosure of the identity of a firm’s major customers, Regulation S–K (17 CFR 229.101(c)(1)(vii)) of the Securities and Exchange Commission does require this disclosure.

  12. There may still be cases of overlapping return windows in the case of a weekend and a national holiday occurring in between the two earnings announcements. We have tried requiring the two announcements to be 5, 6, 7, or 8 days apart. The results are qualitatively similar.

  13. In untabulated analyses, we find that, consistent with our expectations, the overreaction is weaker (albeit still significant at the 1 % level) when retaining these observations.

  14. See Fig. 1 in Ramalingegowda et al. (2012) for its empirical design.

  15. Cohen and Frazzini (2008) document a long window underreaction to customer return information. We reconcile our findings with those of Cohen and Frazzini in Sect. 6.3.

  16. We estimate the model separately for each year rather than separately for each quarter to obtain a reasonable number of observations for each cross-section. We require at least 100 observations each year. Results are robust to estimating the model using panel data with year fixed effects and standard errors clustered by firm and year (Peterson 2009).

  17. All results are qualitatively similar if we do not winsorize any variables.

  18. This method reduces the basic sample to 35,666 supplier-quarter observations. The results are stronger using this approach (untabulated).

  19. The 0.61 % is equivalent to around 2.5 % over four quarters, and the economic significance is not large. We do not attempt to show that this pattern represents a profitable trading strategy. To show that, we would need to demonstrate that the strategy earns abnormal returns exceeding transaction costs and takes positions based on expected earnings announcement dates, since the actual announcement dates may not be known when initially taking the position. This paper’s focus is on price discovery as predicted by the moderated confidence hypothesis.

  20. There are significantly fewer observations for this model because we require the statement of cash flows to calculate TACC. The statement of cash flows was not available before 1988.

  21. Blockholder data is obtained from WRDS, which contains standardized data for blockholders of 1913 companies for the period 1996–2001. The data cleaning procedure is explained in detail by Dlugosz et al. (2006). Accordingly, we restrict this analysis to the period from 1996 to 2001. Industries are defined using the Fama and French (1997) 48-industry classification scheme. We also measure industry using two-digit SIC codes, and we continue to find similar results.

  22. Note that this sample is reduced considerably, as we require there to be a month between the customer’s earnings announcement and the supplier’s earnings announcement, consistent with Cohen and Frazzini’s (2008) 1-month gap.

  23. Results are similar if we instead perform a portfolio test on this sample.

  24. The bid-ask bounce is the short-term price reversal caused by stocks that are not traded. A stock that has not been traded has an equal likelihood of opening the next day at the bid or the ask price. The stock price fluctuating between the bid price on one day and the ask price on the following day creates the illusion of stock return reversals. This is often called the bid-ask bounce. See Brown and Warner (1985).

  25. Note that other time-sensitive variables such as \(SRET1\), \(CRET1\), \(SRET6\), \(SRETQEA1\), and \(SRETQEA4\) are re-calculated using the stock returns on the new dates.

  26. We obtain similar results if we perform a portfolio test using pseudo-event dates.

  27. We have conducted additional robustness checks, including using different abnormal return measures such as the Fama and French three- and four-factor adjusted returns and industry-adjusted returns. We have conducted separate analyses for profit and loss firms and have tried alleviating the restriction that the two firms’ earnings announcements be no more than four weeks apart. We continue to find that suppliers’ stock prices overreact to customer earnings news.

  28. The three-day return window covers days −1, 0, and +1, where day 0 is the earnings announcement day. As discussed in Fama (1998) and Kothari (2001), the choice of the expected return model is less important in short-window studies because the expected daily return is approximately zero. Nevertheless, we have tried using industry-adjusted stock returns as well as size-adjusted stock returns and the results are similar.

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Acknowledgments

We thank Scott Richardson (editor), an anonymous reviewer, Hsihui Chang, Peng Guo, Shuo Li, J.C. Lin, Ken Reichelt, Jared Soileau, Avanidhar Subra, Ivy Zhang and Tony Zhang, workshop participants at the 2012 AAA Midwest meeting, the 2013 AAA annual meeting, the 2013 Review of Accounting Studies conference, and all workshop participants at Louisiana State University, Hong Kong Polytechnic University, and the University of Washington at Bothell. All errors that remain are our own.

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Correspondence to C. S. Agnes Cheng.

Appendix: Variable definitions

Appendix: Variable definitions

This section contains variable definitions with Compustat and CRSP mnemonics. The definitions are listed in alphabetical order.

CRET C-EA  = The market-adjusted stock return of the customer firm during its own 3-day earnings announcement window. The market adjusted return is the raw return less the return on CRSP’s value-weighted index (ret - vwretd).Footnote 28

CRET1 = the 1-month stock return of the customer firm ending 1 week prior the supplier’s earnings announcement (excluding the 3-day window of the customer’s earnings announcement).

\(LOW\_DEPENDENCE =\) 1 if the supplier’s sales to the customer divided by the customer’s cost of goods sold is lower than the median for the quarter, zero otherwise.

LOW_PCT_SALE =  1 if the supplier’s sales to the customer divided by the supplier’s total sales is lower than the median for the quarter, zero otherwise.

logBM =  The natural logarithm of the book-to-market ratio. Book value is defined as common equity (ceq), set equal to missing if negative. Market value is defined as price times shares outstanding (|prc| × shrout). Book value is measured at the previous fiscal-year end, while market value is measured as of the month prior to the customer’s earnings announcement.

logMV =  The natural logarithm of the market value of equity. Market value is prices times shares outstanding (|prc| × shrout), measured one month prior to the month of the customer’s earnings announcement.

SRET1 =  The 1-month stock return of the supplier firm ending 1 week prior to the supplier’s earnings announcement (excluding the 3-day window of the customer’s earnings announcement).

SRET6 =  The 6-month stock return of the supplier firm ending 1 week prior to the supplier’s earnings announcement. This controls for the momentum effect of Jegadeesh and Titman (Jegadeesh and Titman 1993).

SRET C-EA  =  The market-adjusted stock return of the supplier firm during the three-day window surrounding its customer’s quarterly earnings announcement.

SRET S-EA  =  The market-adjusted stock return of the supplier firm during the three-day window surrounding its own firm’s quarterly earnings announcement, occurring after its customer’s earnings announcement.

SRETQEA1 =  The supplier’s 3-day market-adjusted stock return during its last quarterly earnings-announcement window. The market adjusted return is the raw return less the return on CRSP’s value-weighted index (ret - vwretd).

SRETQEA4 =  The supplier’s 3-day market-adjusted stock return during its quarterly earnings-announcement window occurring four quarters prior to the current quarter. The market adjusted return is the raw return less the return on CRSP’s value-weighted index (ret − vwretd).

TACC = Total accruals of the supplier firm. Total accruals equal net income (ni) less operating cash flows (oancf) scaled by average total assets. This variable is measured using annual data from the previous fiscal year to ensure the market had access to this information.

UE = The unexpected earnings of the supplier, defined as quarterly earnings (ibq) less earnings four quarters ago, all scaled by beginning of quarter market value of equity (prccq × cshoq).

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Cheng, C.S.A., Eshleman, J.D. Does the market overweight imprecise information? Evidence from customer earnings announcements. Rev Account Stud 19, 1125–1151 (2014). https://doi.org/10.1007/s11142-014-9293-8

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