Machine Learning for Continuous-Time Finance
Event details
| Date | 14.02.2020 |
| Hour | 10:30 › 12:00 |
| Speaker | Victor DUARTE, Gies College of Business - UIUC |
| Location |
UNIL, Extranef, room 126
|
| Category | Conferences - Seminars |
This paper proposes an algorithm for solving a large class of nonlinear continuous-time models in finance and economics. First, I recast the problem of solving the corresponding nonlinear partial differential equations as a sequence of supervised learning problems. Second, I prove that the computational cost of evaluating the exact continuous-time Bellman residuals does not increase in the number of state variables, allowing for the solution of high-dimensional problems. To illustrate the method, I solve canonical asset pricing models featuring recursive preferences, endogenous labor supply, irreversible investment, and state spaces with up to ten dimensions.
Practical information
- Informed public
- Free