Joint Distribution of Forecasts and Outcomes: Impact of Non-Normality on the Measurement of Forecasting Skill, with Applications to Analysts’ Target Prices

Title

JOINT DISTRIBUTION OF FORECASTS AND OUTCOMES:IMPACT OF NON-NORMALITY ON THE MEASUREMENT OF FORECASTING SKILL, WITH APPLICATIONS TO ANALYSTS’ TARGET PRICES

Authors

S.A. Bond
(University of Cincinnati)
Q. Chang
(Office of the Comptroller of the Currency)
J. Knight
(University of Western Ontario)
S.E. Satchell
(Birkbeck College and University of Sydney)

Abstract

The purpose of this paper is to provide a detailed analysis of the joint distribution of forecastsand outcomes in the context of financial forecasting. We use Edgeworth expansions to model
this joint distribution. In turn this allows us to assess the impact of non-normality, either in
forecasts, or outcomes or both. This leads to multiple results; we can deduce the distribution of
the forecast error; we can analyse the properties of the hit rate (H), as a statistical concept in its
own right, and also in its relation to the information coefficient (IC); two tools that are used in
the assessment of forecasting ability by active fund managers and financial analysts. Our paper
contributes to the recent econometric literature on directional forecasting as well as the
empirical literature that examines analyst performance. We find that the close link between H
and IC under normality breaks down in the more general case. We provide further evidence on
the richness of this approach by looking at simulation and empirical evidence.

Keywords

Hit rate, Information Coefficient, Edgeworth expansions, financial forecasting, Analysts’ Target Prices

Classification-JEL

G10, G12

Pages

420-459

https://doi.org/10.47654/v22y2018i1p420-459