Pricing American-style securities using simulation

TL;DR: In this article, a simple yet powerful new approach for approximating the value of American options by simulation is presented, based on the use of least squares to estimate the conditional expected payoff to the optionholder from continuation.

TL;DR: In this article, the authors discuss some of the recent applications of the Monte Carlo method to security pricing problems, with emphasis on improvements in efficiency, and describe the use of deterministic low-discrepancy sequences, also known as quasi-Monte Carlo methods, for the valuation of complex derivative securities.

TL;DR: A simulation-based approximate dynamic programming method for pricing complex American-style options, with a possibly high-dimensional underlying state space, and a related method which uses a single (parameterized) value function, which is a function of the time-state pair.

TL;DR: Stochastic differential equations are derived for term structures of forward libor and swap rates, and shown to have a unique positive solution when the percentage volatility function is bounded, implying existence of an arbitrage-free model with such volatility specification.

TL;DR: The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.

TL;DR: In this paper, a simple discrete-time model for valuing options is presented, which is based on the Black-Scholes model, which has previously been derived only by much more difficult methods.

TL;DR: In this paper, the authors examined the structure of option valuation problems and developed a new technique for their solution and introduced several jump and diffusion processes which have not been used in previous models.