Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/188893
23 Visitors
28 Hits
1 Downloads
- Title
- Asset allocation under regime-switching models
- Related
- International Conference on Business Intelligence and Financial Engineering (5th : 2012) (18 - 21 August 2012 : Lanzhou, China)
- Related
- Yu, Lean; Zhang, Guoxing and Wang, Shouyang. Proceedings of the 2012 Fifth International Conference on Business Intelligence and Financial Engineering : BIFE 2012 : 18-21 August 2012, Lanzhou, Gansu, China, p.144-148
- DOI
- 10.1109/BIFE.2012.38
- Publisher
- Piscataway, NJ : IEEE
- Date
- 2012
- Author/Creator
- Song, Na
- Author/Creator
- Ching, Wai-Ki
- Author/Creator
- Zhu, Dong-Mei
- Author/Creator
- Siu, Tak-Kuen
- Description
- We discuss an optimal asset allocation problem in a wide class of discrete-time regime-switching models including the hidden Markovian regime-switching (HMRS) model, the interactive hidden Markovian regime-switching (IHMRS) model and the self-exciting threshold autoregressive (SETAR) model. In the optimal asset allocation problem, the object of the investor is to select an optimal portfolio strategy so as to maximize the expected utility of wealth over a finite investment horizon. We solve the optimal portfolio problem using a dynamic programming approach in a discrete-time set up. Numerical results are provided to illustrate the practical implementation of the models and the impacts of different types of regime switching on optimal portfolio strategies.
- Description
- 5 page(s)
- Subject Keyword
- asset allocation
- Subject Keyword
- HMM
- Subject Keyword
- IHMM
- Subject Keyword
- regime-switching models
- Subject Keyword
- SETAR Model
- Subject Keyword
- stochastic dynamical system
- Resource Type
- conference paper
- Organisation
- Macquarie University. Dept. of Applied Finance and Actuarial Studies
- Identifier
- http://hdl.handle.net/1959.14/188893
- Identifier
- ISBN:9781467320924
- Identifier
- mq_res-ext-ieee20120928343-7
- Language
- eng
- Reviewed
