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Valuation uncertainty and analysts’ use of DCF models

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Abstract

Using textual analysis for a large sample of analyst reports on U.S. firms, we find that analysts are more likely to use a discounted cash flow (DCF) model and to discuss more cash flow and discount rate information for firms with more uncertainty, as measured by earnings quality and firm risks. The market reactions to target price changes based on a DCF model are stronger, particularly for firms with greater valuation uncertainty and when the analysts present more cash flow and discount rate discussions. These results indicate that the analyst valuation process reflects investors’ information demand under uncertainty and has a bearing on the informativeness of analyst research.

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Notes

  1. The use of a DCF model increases from 2% to more than 10% during the same period and keeps increasing to around 30% by the end of 2002.

  2. See Bradshaw (2004) and Barniv et al. (2009, 2010).

  3. See Gleason et al. (2013) and Hand et al. (2017).

  4. In this study, we use price-to-earnings to indicate a broad definition of earnings-based multiples which include entity-level measures, such as EV/EBIT and EV/EBTDA.

  5. Of the 90% of reports that disclose any valuation models during our sample period, 98% and 38% of the reports mention a price-to-earnings model and a DCF model, respectively. Our main findings are qualitatively unchanged if we define the use of a DCF model as simply being mentioned in an analyst report.

  6. By “valuation uncertainty,” we mean analysts’ perceived uncertainty about the underlying firm’s fundamentals. In practice, “risk” and “uncertainty” go together (Miller 1977). We do not make a clear distinction between “risk” and “uncertainty,” because they are hard to empirically disentangle, as observed empirical constructs might capture both effects. For instance, Joos et al. (2016) use the difference in target price forecasts in bull and bear scenarios to capture analysts’ recognition of the underlying firm’s risk and uncertainty.

  7. See, for example, Campbell and Ammer (1993), Campbell and Shiller (1988), Campbell and Vuolteenaho (2004), Chen and Zhao (2009), and Bansal and Yaron (2004).

  8. See the example in Appendix 1.

  9. We observe a similar increasing trend of firms valued with a DCF model (an increase from 6% in 1997 to more than 50% in recent years) and analysts using a DCF model (an increase from 11% in 1997 to more than 50% in recent years).

  10. In addition to a short window of marker reaction, we also include a half-year window to test the informativeness of the analyst report, because the investment period of an analyst’s forecast is usually six to 12 months.

  11. Our findings in the subsample tests are qualitatively unchanged if we use CAR183 as the dependent variables.

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Author information

Authors and Affiliations

  1. China University of Mining and Technology-Beijing, Beijing, China

    Shengzhong Huang

  2. McGill University, Montreal, Canada

    Hongping Tan

  3. Zhongnan University of Economics and Law, Wuhan, China

    Xiongyuan Wang

  4. University of Manitoba, Winnipeg, Canada

    Changqiu Yu

Authors
  1. Shengzhong Huang
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  2. Hongping Tan
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  3. Xiongyuan Wang
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  4. Changqiu Yu
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Correspondence to Hongping Tan.

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We gratefully acknowledge financial support from the Social Sciences and Humanities Research Council of Canada (grant numbers 435-2022-0757, 435-2019-0425, 435-2016-1164) and the National Natural Science Foundation of China (grant numbers 71872154, 72172156, 71672191).

Appendices

Appendix 1 Anecdotal evidence on analysts’ use of valuation models

figure a

Appendix 2 Variable definitions

Variable

Definition and data sources

Dependent variables

DCF

Dummy equals one if analysts use DCF model as the dominant valuation model and zero otherwise. We use textual analysis of analyst reports from Investext to identify whether a DCF model is the dominant valuation model, with details in Section 3.2.

RepCF

The number of cash flow keywords discussed by analysts in their reports. The data is obtained through textual analysis of analyst reports from Investext. See Appendix 3 for the list of cash flow keywords.

RepDR

The number of discount rate keywords discussed by analysts in their reports. The data is obtained through textual analysis of analyst reports from Investext. See Appendix 3 for the list of discount rate keywords.

CARt

Market-adjusted cumulative abnormal return starting one day before to three days and 183 days after the issuance of an analyst report, multiplied by 100.

Independent variables

Earnmgmt

Abnormal accruals based on Modified Jones Model in year t-1.

Accrual

Absolute difference between net income before extraordinary items and operating cash flows divided by total assets in year t-1.

CF_std

Five years standard deviation of quarterly operating cash flows scaled by total assets before analyst report date.

Loss

An indicator of negative earnings in Compustat.

Retstd12

Standard deviation of daily stock return during the 12 months before an analyst report date, multiplied by 100. We obtain daily stock return data from CRSP.

TPchg

Change of analyst target price forecast scaled by the stock price at the beginning of the year. The target prices are extracted from analyst reports from Investext and stock price data is from CRSP.

Control variables

Logmv

The logarithm of firm market value in year t-1. The data source is CRSP.

Salesgrowth

Year t - 1 revenues less year t - 2 revenues scaled by year t - 2 revenues.

Beta

Market beta calculated from CAPM model. The data source is CRSP.

Arpre12

12-month abnormal return before the issue of an analyst’ report. The data source is CRSP.

Repwords

The logarithm of the total number of analyst report words. The data is obtained through textual analysis of analyst reports from Investext.

Indexpert

The logarithm of the number of firms in a two-digit SIC industry covered by the analyst in year t. The data source is I/B/E/S.

Firmex

The number of years an analyst has been following a firm. The data source is I/B/E/S.

Buy

Dummy equals one if analyst issue a buy recommendation and zero otherwise. We obtain recommendation data from analyst reports from Investext.

CFA

Dummy equals one if an analyst has a CFA designation and zero otherwise. We use textual analysis of analyst reports to identify whether an analyst has a CFA designation.

EAD30

Dummy equals to one if the analyst report is issued within 30 days before and after an annual earnings announcement date and zero otherwise. We obtain annual earnings announcement dates from Compustat.

EADCAR

Market-adjusted cumulative abnormal return starting one day before to three days after a firm’s quarterly earnings announcement date. We obtain daily stock return data from CRSP and quarterly earnings announcement date from Compustat.

  1. Financial data source is Compustat unless specified otherwise. All continuous variables are winsorized at the first and 99th percentiles

Appendix 3 List of keywords for discount rate and cash flow discussions

Discount rate discussion

Cash flow discussion

and discounting

capital expenditure

Beta

capital expenditures

CAPM

cash

capital asset pricing

cash-equivalents

CFROI

cashflow

CoC

cash-flow

COE

CFFA

cost of capita

CFPS

cost of capital

DCF

cost of debt

DCFPS

cost of equity

DDM

DCF

discounted dividend

DDM

discounted dividends

debt yield

dividend discount

discount rate

dividend discounted

discounted at

dividends paid

discounted by

FCF

discounted cash

IRR

discounted dividend

liquid assets

discounting rate

NPV

discount-rate

OCF

equity cost

paid dividends

equity discount

payments for

equity premium

payments of

equityrisk premium

perpetuity growth

ERP

present value

IRR

present-value

market excess return

proceeds from

market premia

purchase of

market premium

terminal value

marketpremium

 

MRP

 

NPV

 

present value

 

rate of return

 

rate of returns

 

return on equity

 

return on investment

 

risk premium

 

riskpremium

 

RoCE

 

ROIC

 

WACC

 

we discount

 
  1. These keywords are case-insensitive after being loaded into our Java program to count word frequency. Some phrases miss a blank between the words (such as riskpremium) or miss a letter (such as cost of capita) in the original analyst reports in PDF format. We include them as keywords in the above lists. Our results remain unchanged when we exclude the keywords DCF and DDM

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Huang, S., Tan, H., Wang, X. et al. Valuation uncertainty and analysts’ use of DCF models. Rev Account Stud 28, 827–861 (2023). https://doi.org/10.1007/s11142-021-09658-w

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