PARAMETER ESTIMATION METHODS OF REQUIRED RATE OF RETURN ON STOCK

Battulga Gankhuu ()
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Battulga Gankhuu: Department of Applied Mathematics, National University of Mongolia, Ikh Surguuliin Gudamj, Ulaanbaatar 14201, Mongolia

International Journal of Theoretical and Applied Finance (IJTAF), 2023, vol. 26, issue 08, 1-37

Abstract: In this study, we introduce new estimation methods for the required rate of returns on equity of private and public companies using the stochastic dividend discount model (DDM). To estimate the required rate of return on equity, we use the maximum likelihood method, the Bayesian method, and the Kalman filtering. We apply the model to a set of firms from the S&P 500 index using historical dividend and price data over a 32-year period. Overall, the suggested methods can be used to estimate the required rate of returns.

Keywords: Stochastic DDM; ML estimator; Bayesian estimator; Kalman filtering; regime-switching (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijtafx:v:26:y:2023:i:08:n:s0219024924500055

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DOI: 10.1142/S0219024924500055

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