Evaluating Cross-Sectional Forecasting Models for Implied Cost of Capital

47 Pages Posted: 8 Sep 2013 Last revised: 6 Mar 2014

See all articles by Kevin K. Li

Kevin K. Li

Santa Clara University

Partha S. Mohanram

Rotman School of Management, University of Toronto

Multiple version iconThere are 2 versions of this paper

Date Written: May 1, 2013

Abstract

The computation of implied cost of capital (ICC) is constrained by the lack of analyst forecasts for half of all firms. Hou, van Dijk, and Zhang (2012, HVZ) present a cross-sectional model to generate forecasts in order to compute ICC. However, the forecasts from the HVZ model perform worse than those from a naïve random walk model and the ICCs show anomalous correlations with risk factors. We present two parsimonious alternatives to the HVZ model: the EP model based on persistence in earnings and the RI model based on the residual income model from Feltham and Ohlson (1996). Both models outperform the HVZ model in terms of forecast bias, accuracy, earnings response coefficients, and correlations of the ICCs with future returns and risk factors. We recommend that future research use the RI model or the EP model to generate earnings forecasts.

Keywords: Earnings forecasts, Cross-sectional models, Implied cost of capital

JEL Classification: G12, G31, G32, M40, M41

Suggested Citation

Li, Kevin K. and Mohanram, Partha S., Evaluating Cross-Sectional Forecasting Models for Implied Cost of Capital (May 1, 2013). Rotman School of Management Working Paper No. 2322047, Available at SSRN: https://ssrn.com/abstract=2322047 or http://dx.doi.org/10.2139/ssrn.2322047

Kevin K. Li (Contact Author)

Santa Clara University ( email )

500 El Camino Real
Santa Clara, CA 95053
United States

Partha S. Mohanram

Rotman School of Management, University of Toronto ( email )

Canada

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