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1815. Reinforcement Learning for Portfolio Optimization in a Regime-Switching Model
Invited abstract in session WA-63: Novel Optimization Models in Finance, stream OR in Banking, Finance and Insurance: New Tools for Risk Management.
Wednesday, 8:30-10:00Room: S14 (building: 101)
Authors (first author is the speaker)
| 1. | David Saunders
|
| Statistics and Actuarial Science, University of Waterloo |
Abstract
We study a reinforcement learning approach to portfolio selection when the underlying asset price process follows a regime-switching diffusion model. An analytical solution to the HJB equation for the exploratory mean-variance model under regime switching is derived and implementation in practice employing a deep neural network will be discussed. Empirical results investigating robustness with respect to model mis-specification will also be presented.
Keywords
- Financial Modelling
- Risk Analysis and Management
- Control Theory
Status: accepted
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