This paper explores continuous-time and state-space optimal stopping problems from a
reinforcement learning perspective. We begin by formulating the stopping problem using …

In this paper, we present an iteration algorithm for the pricing of American options based on
reinforcement learning. At each iteration, the method approximates the expected discounted …

This article studies deep neural network expression rates for optimal stopping problems of
discrete-time Markov processes on high-dimensional state spaces. A general framework is …

Abstract The generalized Brans–Dicke theory (GBD), as one of the modified gravitational
theories, was proposed previously and some interesting properties were found in this theory …

We consider the supervised learning problem of learning the price of an option or the
implied volatility given appropriate input data (model parameters) and corresponding output …

We review the modelling and pricing of American options both in classical mathematical
finance and in reinforcement learning (RL). Some of the main difficulties when pricing an …

In general, there is little difference in relative value between American and European option
prices. In addition, American options are very sensitive to corporate events such as earnings …

American options have long received considerable attention in the literature, with numerous
publications dedicated to their pricing. Bermudan and randomized Bermudan options are …

A Bibliography of Publications in SIAM Journal on Financial Mathematics Page 1 A
Bibliography of Publications in SIAM Journal on Financial Mathematics Nelson HF Beebe …