Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

Continuous-Time Mean-Variance Portfolio Selection Problem with Ho-Lee Stochastic Interest Rates

Authors
Chuangwei Lin, Li Zeng
Corresponding Author
Chuangwei Lin
Available Online November 2017.
DOI
10.2991/amms-17.2017.5How to use a DOI?
Keywords
mean-variance portfolio selection; Ho-Lee stochastic interest rate; efficient frontier; stochastic control.
Abstract

This paper investigates a continuous-time mean-variance portfolio selection problem with Ho-Lee stochastic interest rates. Compared with the mean-variance model with deterministic interest rate, a verification theorem without the classical Lipschitz and growth conditions is required to solve our portfolio selection problem. The optimal investment strategy, the value function and the efficient frontier are derived in closed-form. Some existing results are obtained as special cases in our paper.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
Series
Advances in Intelligent Systems Research
Publication Date
November 2017
ISBN
978-94-6252-433-0
ISSN
1951-6851
DOI
10.2991/amms-17.2017.5How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Chuangwei Lin
AU  - Li Zeng
PY  - 2017/11
DA  - 2017/11
TI  - Continuous-Time Mean-Variance Portfolio Selection Problem with Ho-Lee Stochastic Interest Rates
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 20
EP  - 26
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.5
DO  - 10.2991/amms-17.2017.5
ID  - Lin2017/11
ER  -