International Journal of Forecasting 9 (1993) 34X-344

Elsevier Science Publishers B.V., Amsterdam

34.3

Reply to commentaries on “Earnings forecasting research: its implications for capital markets research”

Lawrence D. Brown

Department of Accounting and Law, SUNY at Buffalo, 372 Jacobs Management Center, Box 604000, Buffalo, NY 14260-4000, USA

I appreciate the kind words and thoughtful commentaries by Philip Brown, John O’Hanlon, Jake Thomas, and Mark Zmijewski regarding my paper. If I did not know that the commen- tators were so kind, I would conclude that they genuinely like the paper. I agree with most of what the commentators say, and will take this opportunity to respond to just one point raised by each of them.

Philip Brown raises issue with my view that some of the analyst bias may be unintentional. I believe that most of the bias of sell-side analysts is indeed intentional. After all, a brokerage house analyst’s bonus is often determined by a poll of the firm’s sales force and, when casting their votes, the salesmen consider the amount of stock commissions that the analyst’s recom- mendations have generated for them [Dorfman (1991)]. A s ro b k ers are far more likely to make buy, rather than sell or hold, recommendations, brokerage house analysts have incentives to be overly optimistic. The anecdote in O’Glove (1987, pp. 3-4), concerning the excuse of a financial writer who claimed (ex post) to have foreseen the stock market crash of 1929, yet was a bull to the very end, is instructive: “If I said sell everything and go fishing on Monday, what could I write on Tuesday?” Behavioral research suggests that some of the analyst bias is uninten- tional. A test of the ‘unintentional bias’ theory could best be conducted on buy-side analysts, as they have no obvious economic incentives to

exhibit optimistic biases.’ A study of the bias of buy-side analysts, perhaps conducted jointly by capital markets and behavioral researchers, would enable a better understanding of how much (if any) of the analyst bias is unintentional [Schipper (1991)J.

John O’Hanlon opines that: “there is a grow- ing view that earnings/stock price research has been hindered by the lack of a model of the links between earnings and stock prices”. He uses Beaver’s (1989) three-link framework, and con- cludes that the “earnings persistence” literature, by equilibrating the stream of future earnings with that of future dividends, assumes away the second link, that between future dividends and future earnings. O’Hanlon also points out that the three links have been modelled by Ohlson (1991), and that recent empirical research has been influenced by Ohlson’s model. I concur with his view, and predict that other models will evolve that will influence subsequent earnings stock/price research.

Jake Thomas maintains that: “The most inter- esting finding in earnings forecasting over the past ten years is the realization that annual earnings do not follow a random walk”. I agree that the descriptive evidence favors a first-order

’ One of the primary information sources of buy-side

analysts is sell-side analysts [SRI International (1987)].

Buy-side analysts should be aware of, and capable of

extracting, this optimistic bias.

autoregressive model, but 1 caution readers not to interpret Thomas’ remarks as necessarily suggesting that the accuracy and/or association evidence favors a first-order autoregressive model. Thomas does not actually make this suggestion. but the unwary reader may erro- neously interpret the descriptive evidence he provides in this manner. The early studies of the time-series properties of annual earnings num- bers rejected the random walk model using in- sample data [Albrecht et al. (1977), Watts and Leftwich (1977)l. H owever, these same studies failed to reject the random walk model in a holdout period. Thus, while the random walk model was inferior ex post, it was not inferior ex ante. I would like to see evidence that an AR( 1) model, with its firm-specific parameter estimated using in-sample data, makes better predictions than a random walk model in a holdout period. Even if the accuracy evidence on a holdout sample favors a first-order autoregressive model, stock prices may not fully reflect the time-series properties of this model. Bernard and Thomas (1990) show that stock prices do not fully reflect the implications of current quarterly earnings for future quarterly earnings. Similarly, stock prices may fail to fully reflect the implications of current annual earnings for future annual earn- ings. If stock prices do not fully reflect the time- series properties of an AR( 1) model, association studies may not wish to use the model to proxy for the market’s expectation.

Mark Zmijewski offers five predictions for future research. The first two are: “( 1) cross- country comparisons of the time-series proper- ties of earnings and other information variables, (2) cross-country comparisons of the relation between earnings and stock prices and the role of earnings, and other information, in capital markets”. Although Zmijewski does not men- tion this, a primary reason for the dearth of evidence in this area is that, until recently, joint earnings and stock price data were very difficult to obtain. With the advent if I/B/E/S Interna- tional data, along with various sources of inter-

national stock price data (e.g. Reuters Informa- tion Services, PACAP). this literature is likely to expand quickly (see Front and Pownall (1993) for a study using Reuters Information Services data). I look forward to reading about. and possibly contributing to, research in this area.

Several of the commentators extrapolate from two observations, and conclude that I will pro- vide another perspective on this topic 10 years hence. In 1983, Paul Griffin and I provided a perspective based on 27 references. In 1993, I provided a perspective based on 171 references. Adopting the commentators’ linear extrapolative technique suggests that a perspective based on 315 references will be provided by zero authors in the year 2003.

References

Alhrecht. W.. L. Lookahill and J.C. McKeown. 1977, “The

time series properties of annual earnings”. Journal of Accounting Research, 15, 226-244.

Beaver. W.H., 1YXY. Financiul Reporiing: At] Accounting Revolution. 2nd edition (Prentice-Hall, Englewood Cliffs).

Bernard,V. and .I. Thomas. 1900, “Evidence that stock prices

do not fully reflect the implications of current earnings for

future earnings”. Journctl of Accounting and Economics. 13. 305-340.

Dorfman. J.R.. 1991, “Analysts devote more time to selling

as firms keep scorecard on performance”, The Wail Sfreel Journal, October 2Y. Cl-2.

Frost, C.A. and G. Pownall. 19Y3, “A comparison of the

stock price response to earnings-related disclosures in the

U.S. and the U.K.“. Working paper (Washington Universi-

ty). O’Cilovc, T.L.. 1987. c)ualiry of Emzings (The Free Press,

New York).

Ohlson. J., 1991. “Earnings, hook values and dividends in

security valuation”. Working paper (Columbia University).

Schipper, K.. lYY1, “Commentary on analysts’ forecasts”,

Accounring Horizons, 5, l05- 121. SRI International. lYX7. Ittvestor Information Needs and the

Annual Reporr (Financial Executives Research Founda-

tion. Morristown). Watts. R. and R. Leftwich. lY77, “The time series of annual

accounting earnings”. Journal of Accounting Research. IS. 253s271.