A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand
© 2019, The Author(s). A compound Ornstein–Uhlenbeck process is applied to create a model that can calculate the dividend yield represented in a sample case of Stock Exchange of Thailand index in which earning yield is randomly determined. Parameter estimations are made through the use of least-squa...
Saved in:
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Article |
Published: |
2020
|
Subjects: | |
Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/51186 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Mahidol University |
id |
th-mahidol.51186 |
---|---|
record_format |
dspace |
spelling |
th-mahidol.511862020-01-27T16:12:04Z A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand P. Vatiwutipong N. Phewchean South Carolina Commission on Higher Education Mahidol University Mathematics © 2019, The Author(s). A compound Ornstein–Uhlenbeck process is applied to create a model that can calculate the dividend yield represented in a sample case of Stock Exchange of Thailand index in which earning yield is randomly determined. Parameter estimations are made through the use of least-square technique, while the outcomes are deduced from the Euler–Maruyama method. We use numerical simulation to determine the effectiveness of the models, comparing our newly proposed model with the previous models. The actual dividend yield data is applied for comparison. The results show that our model performs best among the three models being compared. 2020-01-27T09:12:04Z 2020-01-27T09:12:04Z 2019-12-01 Article Advances in Difference Equations. Vol.2019, No.1 (2019) 10.1186/s13662-019-2231-0 16871847 16871839 2-s2.0-85069195666 https://repository.li.mahidol.ac.th/handle/123456789/51186 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85069195666&origin=inward |
institution |
Mahidol University |
building |
Mahidol University Library |
continent |
Asia |
country |
Thailand Thailand |
content_provider |
Mahidol University Library |
collection |
Mahidol University Institutional Repository |
topic |
Mathematics |
spellingShingle |
Mathematics P. Vatiwutipong N. Phewchean A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand |
description |
© 2019, The Author(s). A compound Ornstein–Uhlenbeck process is applied to create a model that can calculate the dividend yield represented in a sample case of Stock Exchange of Thailand index in which earning yield is randomly determined. Parameter estimations are made through the use of least-square technique, while the outcomes are deduced from the Euler–Maruyama method. We use numerical simulation to determine the effectiveness of the models, comparing our newly proposed model with the previous models. The actual dividend yield data is applied for comparison. The results show that our model performs best among the three models being compared. |
author2 |
South Carolina Commission on Higher Education |
author_facet |
South Carolina Commission on Higher Education P. Vatiwutipong N. Phewchean |
format |
Article |
author |
P. Vatiwutipong N. Phewchean |
author_sort |
P. Vatiwutipong |
title |
A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand |
title_short |
A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand |
title_full |
A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand |
title_fullStr |
A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand |
title_full_unstemmed |
A study of dividend yield model under stochastic earning yield environment in stock exchange of Thailand |
title_sort |
study of dividend yield model under stochastic earning yield environment in stock exchange of thailand |
publishDate |
2020 |
url |
https://repository.li.mahidol.ac.th/handle/123456789/51186 |
_version_ |
1763495646584635392 |