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Parameter identification for portfolio optimization with a slow stochastic factor.
- Source :
-
Journal of Inverse & Ill-Posed Problems . Dec2022, Vol. 30 Issue 6, p777-789. 13p. - Publication Year :
- 2022
-
Abstract
- In this paper, we intend to identify two significant parameters – expected return and absolute risk aversion – in the Merton portfolio optimization problem under an exponential utility function where volatility is driven by a slow mean-reverting diffusion process. First, we find the approximate solution of the fully nonlinear Hamilton–Jacobi–Bellman equation for the Merton model by the stochastic asymptotic approximation method. Second, we estimate parameters – expected return and absolute risk aversion – through the approximate solution and prove the uniqueness and stability of the parameter identification problem. Finally, we provide an illustrative example to demonstrate the capacity and efficiency of our method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09280219
- Volume :
- 30
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Journal of Inverse & Ill-Posed Problems
- Publication Type :
- Academic Journal
- Accession number :
- 160362830
- Full Text :
- https://doi.org/10.1515/jiip-2020-0156