L.P. 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 RepositoryEssays on forecasting and latent values
http://repub.eur.nl/pub/79324/
Thu, 17 Dec 2015 00:00:01 GMT<div>L.P. de Bruijn</div>
Benchmarking judgmentally adjusted forecasts
http://repub.eur.nl/pub/79222/
Sun, 01 Nov 2015 00:00:01 GMT<div>Ph.H.B.F. Franses</div><div>L.P. de Bruijn</div>
Many publicly available macroeconomic forecasts are judgmentally-adjusted model-based forecasts. In practice usually only a single final forecast is available, and not the underlying econometric model, nor are the size and reason for adjustment known. Hence, the relative weights given to the model forecasts and to the judgment are usually unknown to the analyst.
This paper proposes a methodology to evaluate the quality of such final forecasts, also to allow learning from past errors. To do so, the analyst needs benchmark forecasts. We propose two such benchmarks. The first is the simple no-change forecast, which is the bottom line forecast that an expert should be able to improve. The second benchmark is an estimated model based forecast, which is found as the best forecast given the realizations and the final forecasts. We illustrate this methodology for two sets of GDP growth forecasts, one for the US and for the Netherlands. These applications tell us that adjustment appears most effective in periods of first recovery from a recession.Stochastic levels and duration dependence in US unemployment
http://repub.eur.nl/pub/78710/
Wed, 23 Sep 2015 00:00:01 GMT<div>L.P. de Bruijn</div><div>Ph.H.B.F. Franses</div>
We introduce a new time series model that can capture the properties of data as is typically exemplified by monthly US unemployment data. These data show the familiar nonlinear features, with steeper increases in unem- ployment during economic downswings than the decreases during economic prosperity. At the same time, the levels of unemployment in each of the two states do not seem fixed, nor are the transition periods abrupt. Finally, our model should generate out-of-sample forecasts that mimic the in-sample properties. We demonstrate that our new and flexible model covers all those features, and our illustration to monthly US unemployment data shows its merits, both in and out of sample.How Informative are the Unpredictable Components of Earnings Forecasts?
http://repub.eur.nl/pub/77922/
Sun, 01 Mar 2015 00:00:01 GMT<div>L.P. de Bruijn</div><div>Ph.H.B.F. Franses</div>
__Abstract__
An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the unpredictable components, which may be viewed as the personal expertise of the earnings forecasters, we see that small adjustments to the model forecasts lead to more forecast accuracy. Based on past track records, it is possible to predict the future track record of individual forecasters.A Novel Approach to Measuring Consumer Confidence
http://repub.eur.nl/pub/77640/
Sat, 01 Nov 2014 00:00:01 GMT<div>L.P. de Bruijn</div><div>R. Segers</div><div>Ph.H.B.F. Franses</div>
__Abstract__
This paper puts forward a new data collection method to measure daily consumer confidence at the individual level. The data thus obtained allow to statistically analyze the dynamic correlation of such a consumer confidence indicator and to draw inference on transition rates. The latter is not possible for currently available monthly data collected by statistical agencies on the basis of repeated cross-sections. In an application to measuring Dutch consumer confidence, we show that the incremental information content in the novel indicator helps to better forecast consumption.Forecasting Earnings Forecasts
http://repub.eur.nl/pub/41126/
Thu, 22 Aug 2013 00:00:01 GMT<div>L.P. 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>L.P. 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>L.P. 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>L.P. 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>L.P. 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>L.P. 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.