B. de Bruijn (Bert)
http://repub.eur.nl/ppl/36855/
List of Publicationsenhttp://repub.eur.nl/eur_signature.png
http://repub.eur.nl/
RePub, Erasmus University RepositoryForecasting Earnings Forecasts
http://repub.eur.nl/pub/41126/
Thu, 22 Aug 2013 00:00:01 GMT<div>B. de Bruijn</div><div>Ph.H.B.F. Franses</div>
We analyze earnings forecasts retrieved from the I/B/E/S database concerning 596 firms for the sample 1995 to 2011, with a specific focus on whether these earnings forecasts can be predicted from available data. Our main result is that earnings forecasts can be predicted quite accurately using publicly available information. Second, we show that earnings forecasts that are less predictable are also less accurate. We also show that earnings forecasters who quote forecasts that are too extreme need to correct these as the earnings announcement approaches. Finally, we show that the unpredictable component of earnings forecasts can contain information which we can use to improve the forecasts.
Analyzing fixed-event forecast revisions
http://repub.eur.nl/pub/41580/
Thu, 08 Aug 2013 00:00:01 GMT<div>C-L. Chang</div><div>B. de Bruijn</div><div>Ph.H.B.F. Franses</div><div>M.J. McAleer</div>
It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current forecast revisions on one-period lagged forecast revisions. Under weak-form (forecast) efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that this null hypothesis of zero correlation is rejected frequently, and the correlation can be either positive (which is widely interpreted in the literature as "smoothing") or negative (which is widely interpreted as "over-reacting"). We propose a methodology for interpreting such non-zero correlations in a straightforward and clear manner. Our approach is based on the assumption that numerical forecasts can be decomposed into both an econometric model and random expert intuition. We show that the interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the current and lagged correlations between intuition and news (or shocks to the numerical forecasts). It follows that the estimated non-zero correlation cannot be given a direct interpretation in terms of either smoothing or over-reaction. Analyzing Fixed-Event Forecast
Revisions
http://repub.eur.nl/pub/39841/
Thu, 11 Apr 2013 00:00:01 GMT<div>C-L. Chang</div><div>B. de Bruijn</div><div>Ph.H.B.F. Franses</div><div>M.J. McAleer</div>
It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current forecast revisions on one-period lagged forecast revisions. Under weak-form (forecast) efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that this null hypothesis of zero correlation is rejected frequently, where the correlation can be either positive (which is widely interpreted in the literature as “smoothing”) or negative (which is widely interpreted as “over-reacting”). We propose a methodology to interpret such non-zero correlations in a straightforward and clear manner. Our approach is based on the assumption that numerical forecasts can be decomposed into both an econometric model and random expert intuition. We show that the interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the current and lagged correlations between intuition and news (or shocks to the numerical forecasts). It follows that the estimated non-zero correlation cannot be given a direct interpretation in terms of smoothing or over-reaction.
Managing Sales Forecasters
http://repub.eur.nl/pub/38213/
Fri, 30 Nov 2012 00:00:01 GMT<div>B. de Bruijn</div><div>Ph.H.B.F. Franses</div>
A Forecast Support System (FSS), which generates sales forecasts, is a sophisticated business analytical tool that can help to improve targeted business decisions. Many companies use such a tool, although at the same time they may allow managers to quote their own forecasts. These sales forecasters (managers) can take the FSS output as their input, but they can also fully ignore the FSS out- comes. We propose a methodology that allows to evaluate the forecast accuracy of these managers, relative to the FSS, while taking aboard latent variation across managers' behavior. We show that the results, here for a large Germany-based pharmaceutical company, can in fact be used to manage the sales forecasters by giving clear-cut recommendations for improvement.What drives the Quotes of Earnings Forecasters?
http://repub.eur.nl/pub/34710/
Wed, 11 Jul 2012 00:00:01 GMT<div>B. de Bruijn</div><div>Ph.H.B.F. Franses</div>
Earnings forecasts can be useful for investment decisions. Research on earnings forecasts has focused on forecast performance in relation to firm characteristics, on categorizing the analysts into groups with similar behaviour and on the effect of an earnings announcement by thefirm on future earnings forecasts. In this paper we investigate the factors that determine the value of the forecast and also investigate to what extent the timing of the forecast can be modeled. We propose a novel methodology that allows for such an investigation. As an illustration we analyze within-year earnings forecasts for AMD in the period 1997 to 2011, where the data are obtained from the I/B/E/S database. Our empirical findings suggest clear drivers of the value and the timing of the earnings forecast. We thus show that not only the forecasts themselves are predictable, but that also the timing of the quotes is predictable to some extent.
Evaluating the Rationality of Managers' Sales Forecasts
http://repub.eur.nl/pub/26867/
Mon, 14 Nov 2011 00:00:01 GMT<div>B. de Bruijn</div><div>Ph.H.B.F. Franses</div>
This paper deals with the analysis and evaluation of sales forecasts of managers, given that it is unknown how they constructed their forecasts. Our goal is to find out whether these forecasts are rational. To examine deviations from rationality, we argue that one has to approximate how the managers could have generated the forecasts. We describe several ways to construct these approximate expressions. The analysis of a large set of a single manager's forecasts for sales of pharmaceutical products illustrates the practical usefulness of our methodology.