An Improved Combining-Model of Financial Analysts’ Forecasts and CAPM-Generated Forecasts of Firm-Earnings Growth
- 1 Department of Business Administration, Istanbul Aydin University, Istanbul, Türkiye
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.
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