PARAMETER ESTIMATION METHODS OF REQUIRED RATE OF RETURN ON STOCK

被引：1

作者：

Gankhuu, Battulga ^{[1
]}

机构：

[1] Natl Univ Mongolia, Dept Appl Math, Ulaanbaatar 14201, Mongolia

来源：

INTERNATIONAL JOURNAL OF THEORETICAL AND APPLIED FINANCE | 2023年 / 26卷 / 08期

关键词：

Stochastic DDM; ML estimator; Bayesian estimator; Kalman filtering; regime-switching; TIME-SERIES;

D O I：

10.1142/S0219024924500055

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

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.

引用

页数：37

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