DIVIDENDS AND COMPOUND POISSON PROCESSES: A NEW STOCHASTIC STOCK PRICE MODEL

Battulga Gankhuu (), Jacob Kleinow (), Altangerel Lkhamsuren and Andreas Horsch ()
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Battulga Gankhuu: Department of Applied Mathematics, National University of Mongolia, Ikh Surguuliin Gudamj, Ulaanbaatar 14201, Mongolia
Jacob Kleinow: zeb Consulting, Friedrichstraße 78, D-10117 Berlin, Germany
Altangerel Lkhamsuren: Faculty of Mathematics, Computer and Natural Sciences, German-Mongolian Institute for Resources and Technology, GMIT Campus, 2nd Khoroo, Nalaikh 12790, Mongolia
Andreas Horsch: Faculty of Business Administration, Technische Universität Bergakademie Freiberg, Schlossplatz 1, D-09599 Freiberg, Germany

International Journal of Theoretical and Applied Finance (IJTAF), 2022, vol. 25, issue 03, 1-36

Abstract: This study introduces a stochastic multi-period dividend discount model (DDM) that includes (i) a compound nonhomogenous Poisson process for dividend growth and (ii) the probability of firm default. We obtain maximum likelihood (ML) estimators and confidence interval formulas of our model parameters. We apply the model to a set of firms from the S&P 500 index using historical dividend and price data over a 42-year period. Interestingly, stock price estimations calculated with the model are close to the observable prices. Overall, we prove that the model can be a useful tool for stock pricing.

Keywords: Stochastic dividend discount model; compound nonhomogeneous poisson process; random time of firm default; ML estimators (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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DOI: 10.1142/S0219024922500145

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