Universität zu Köln

Theising, Etienne, Wied, Dominik and Ziggel, Daniel . Reference class selection in similarity-based forecasting of corporate sales growth. J. Forecast.. HOBOKEN: WILEY. ISSN 1099-131X

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Abstract

This paper proposes a general method to handle forecasts exposed to behavioral bias by finding appropriate outside views, in our case corporate sales forecasts of analysts. The idea is to find reference classes, that is, peer groups, for each analyzed company separately that share similarities to the firm of interest with respect to a specific predictor. The classes are regarded to be optimal if the forecasted sales distributions match the actual distributions as closely as possible. The forecast quality is measured by applying goodness-of-fit tests on the estimated probability integral transformations and by comparing the predicted quantiles. The method is out-of-sample backtested on a data set consisting of 21,808 US firms over the time period 1950-2019, which is also descriptively analyzed. It appears that, in particular, the past operating margins are good predictors for the distribution of future sales. A case study compares the outside view of our distributional forecasts with actual analysts' forecasts and emphasizes the relevance of our approach in practice.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Theising, Etienne UNSPECIFIED UNSPECIFIED UNSPECIFIED Wied, Dominik UNSPECIFIED UNSPECIFIED UNSPECIFIED Ziggel, Daniel UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-662428
DOI:	10.1002/for.2927
Journal or Publication Title:	J. Forecast.
Publisher:	WILEY
Place of Publication:	HOBOKEN
ISSN:	1099-131X
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language EARNINGS FORECASTS; OPTIMISM; ANALYSTS; JUDGMENT Multiple languages Economics; Management Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/66242