Monte Carlo methods via a dual approach for some discrete time stochastic control problems

TL;DR

This paper introduces a dual approach using Monte Carlo methods for discrete-time stochastic control problems, improving valuation estimates in financial applications like gas storage.

Contribution

It develops a novel dual formulation and numerical technique that outperforms traditional regression-based methods for stochastic control valuation.

Findings

Enhanced accuracy in value function estimation

Effective application to gas storage valuation

Outperforms existing regression-based methods

Abstract

We consider a class of discrete time stochastic control problems motivated by some financial applications. We use a pathwise stochastic control approach to provide a dual formulation of the problem. This enables us to develop a numerical technique for obtaining an estimate of the value function which improves on purely regression based methods. We demonstrate the competitiveness of the method on the example of a gas storage valuation problem.