TITLE:
An Improved Combining-Model of Financial Analysts’ Forecasts and CAPM-Generated Forecasts of Firm-Earnings Growth
AUTHORS:
Salvatore Joseph Terregrossa
KEYWORDS:
CAPM, Beta, Dispersion of Financial Analysts’ Forecasts, Earnings Growth, Combination Forecasting
JOURNAL NAME:
Theoretical Economics Letters,
Vol.12 No.3,
June
16,
2022
ABSTRACT: The present analysis seeks to develop an improved
combining-model to enhance forecast-accuracy of firm-earnings growth. There are
two components of the combining-model in this study: An expected-return model
in the form of the CAPM, and a structural model underlying financial analysts’
forecasts of earnings growth. In the present study, the path to an improved
combining-model lies in constructing a more forward-looking CAPM by making an
adjustment in the measurement of firm-beta that incorporates the dispersion of financial analysts’ forecasts. Our aim is to infuse an additional layer of independent information content into
the CAPM-generated forecasts; which in turn would make them more useful for
combining with the financial analysts’ consensus forecasts of earnings growth.
The existence of independent information is ascertained by in-sample OLS regressions of realized
values against predicted values of the forecast variable by each of the
component forecast models. The estimated regression coefficients of the in-sample tests of independent information then further serve as forecast weights for out-of-sample combination forecasts. Mean absolute forecast errors are calculated for each
forecasting method, ranging from the component models to the combination models;
and comparisons are made. The OLS regression results and the forecast error
comparisons collaboratively indicate that incorporating the dispersion of analysts’ forecasts into the estimation of beta
adds an additional independent information content in the CAPM-generated forecasts of earnings growth; which
generally leads to better CAPM-generated forecasts of earnings-growth, and in
turn, improved weighted-average combinations of analysts’ consensus forecasts and
CAPM-generated forecasts; which prove superior to either component model
forecast.