In this paper we develop a deep learning method for optimal stopping problems which
directly learns the optimal stopping rule from Monte Carlo samples. As such, it is broadly …

This article presents a simple yet powerful new approach for approximating the value of
American options by simulation. The key to this approach is the use of least squares to …

This book is intended for readers who are quite familiar with probability and stochastic
processes but know little or nothing about finance. It is written in the definition/theorem/proof …

This is a thoroughly updated edition of Dynamic Asset Pricing Theory, the standard text for
doctoral students and researchers on the theory of asset pricing and portfolio selection in …

The Monte Carlo approach has proved to be a valuable and flexible computational tool in
modern finance. This paper discusses some of the recent applications of the Monte Carlo …

We introduce and analyze a simulation-based approximate dynamic programming method
for pricing complex American-style options, with a possibly high-dimensional underlying …

We develop a simulation algorithm for estimating the prices of American-style securities, ie,
securities with opportunities for early exercise. Our algorithm provides both point estimates …

This paper introduces a dual way to price American options, based on simulating the paths
of the option payoff, and of a judiciously chosen Lagrangian martingale. Taking the pathwise …

This paper presents a continuous time model of a firm that can dynamically adjust both its
capital structure and its investment choices. In the model we endogenize the investment …

We develop a new method for pricing American options. The main practical contribution of
this paper is a general algorithm for constructing upper and lower bounds on the true price …