Monte Carlo approximation to optimal investment
L C G Rogers, Pawel Zaczkowski
TL;DR
This paper introduces a Monte Carlo-based duality approach to approximately solve high-dimensional optimal investment problems in incomplete markets, overcoming limitations of traditional methods.
Contribution
It presents a novel methodology combining duality and Monte Carlo simulations for high-dimensional, incomplete market investment problems.
Findings
Effective handling of high-dimensional problems
Overcomes curse of dimensionality in incomplete markets
Provides a practical approximation technique
Abstract
This paper sets up a methodology for approximately solving optimal investment problems using duality methods combined with Monte Carlo simulations. In particular, we show how to tackle high dimensional problems in incomplete markets, where traditional methods fail due to the curse of dimensionality.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and financial applications · Economic theories and models · Financial Markets and Investment Strategies