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Evaluating cross-sectional forecasting models for implied cost of capital

Author

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  • Kevin K. Li

    (University of Toronto)

  • Partha Mohanram

    (University of Toronto)

Abstract

The computation of implied cost of capital (ICC) is constrained by the lack of analyst forecasts for half of all firms. Hou et al. (J Account Econ 53:504–526, 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 (Contemp Account Res 11:689–732, 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.

Suggested Citation

  • Kevin K. Li & Partha Mohanram, 2014. "Evaluating cross-sectional forecasting models for implied cost of capital," Review of Accounting Studies, Springer, vol. 19(3), pages 1152-1185, September.
    • Handle: RePEc:spr:reaccs:v:19:y:2014:i:3:d:10.1007_s11142-014-9282-y
    DOI: 10.1007/s11142-014-9282-y
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    References listed on IDEAS

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    1. Fama, Eugene F & French, Kenneth R, 2000. "Forecasting Profitability and Earnings," The Journal of Business, University of Chicago Press, vol. 73(2), pages 161-175, April.
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    Cited by:

    1. Mei Feng, 2014. "Discussion of “Evaluating cross-sectional forecasting models for implied cost of capital”," Review of Accounting Studies, Springer, vol. 19(3), pages 1186-1190, September.
    2. Hess, Dieter & Simon, Frederik & Weibels, Sebastian, 2025. "Interpretable machine learning for earnings forecasts: Leveraging high-dimensional financial statement data," CFR Working Papers 25-06, University of Cologne, Centre for Financial Research (CFR).

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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