Arbeitspapier

Uncertainty in firm valuation and a cross-sectional misvaluation measure

In all investment decisions it is important to determine the degree of uncertainty associated with the valuation of a company. We propose an original and robust methodology to company valuation which replaces the traditional point estimate of the conventional Discounted Cash Flow (DCF) with a probability distribution of fair values. It hinges on two main ingredients: an econometric model for the company revenues and a set of firm-specific balance sheet relations that are estimated using historical data. The effectiveness and scope of our methodology are explored through a series of statistical exercises on publicly traded U.S. companies. We show that an uncertainty-adjusted indicator of mispricing, derived from the fair value distribution, is capable of predicting future abnormal returns. Then, we construct a new long-short valuation factor and we test that it is not redundant for describing average returns when used to augment traditional market factor models.

Sprache
Englisch

Erschienen in
Series: LEM Working Paper Series ; No. 2020/15

Klassifikation
Wirtschaft
Portfolio Choice; Investment Decisions
Financial Forecasting and Simulation
Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
Thema
Stochastic Discounted Cash Flow
Valuation Uncertainty
Valuation Factor
Kalman Filter

Ereignis
Geistige Schöpfung
(wer)
Bottazzi, Giulio
Cordoni, Francesco
Livieri, Giulia
Marmi, Stefano
Ereignis
Veröffentlichung
(wer)
Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)
(wo)
Pisa
(wann)
2020

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Bottazzi, Giulio
  • Cordoni, Francesco
  • Livieri, Giulia
  • Marmi, Stefano
  • Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)

Entstanden

  • 2020

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