Statistical Topics and Stochastic Models for Dependent Data with Applications

3A Review of the Dividend Discount Model: From Deterministic to Stochastic Models

This chapter introduces a comprehensive overview of the dividend discount models, with a focus on the modeling of the dividend growth process. The analysis starts with the basic Gordon growth model and its extensions to more advanced models based on the Markov chain, leading the reader to the latest frontiers of the stock valuation.

3.1. Introduction

This chapter presents a review of the dividend discount models starting from the basic models (Williams 1938; Gordon and Shapiro 1956) to more recent and complex models (Ghezzi and Piccardi 2003; Barbu et al. 2017; D’Amico and De Blasis 2019) with a focus on the modeling of the dividend process rather than the discounting factor, that is assumed constant in most of the models. The chapter starts with an introduction to the basic valuation model with some general aspects to consider when performing the computation. Then, section 3.3 presents the Gordon growth model (Gordon 1962) with some of its extensions (Malkiel 1963; Fuller and Hsia 1984; Molodovsky et al. 1965; Brooks and Helms 1990; Barsky and De Long 1993) and reports some empirical evidences. Extended reviews of the Gordon stock valuation model and its extensions can be found in Kamstra (2003) and Damodaran (2012). In section 3.4, the focus is directed to more recent advancements in which the dividend process is modeled as a Markov chain (Hurley and Johnson 1994; Yao 1997; Hurley and Johnson ...