American Option Pricing with Importance Sampling and Shifted Regressions

Parallel Binomial American Option Pricing with (and without) Transaction Costs

We present a parallel algorithm that computes the ask and bid prices of an American option when proportional transaction costs apply to the trading of the underlying asset. The algorithm computes the prices on recombining binomial trees, and is designed for modern multi-core processors. Although parallel option pricing has been well studied, none of the existing approaches takes transaction cos...

Randomized stopping times and American option pricing with transaction costs

In a general discrete-time market model with proportional transaction costs, we derive new expectation representations of the range of arbitrage-free prices of an arbitrary American option. The upper bound of this range is called the upper hedging price, and is the smallest initial wealth needed to construct a self-financing portfolio whose value dominates the option payoff at all times. A surp...

A Newton Method for American Option Pricing

The variational inequality formulation provides a mechanism to determine both the option value and the early exercise curve implicitly [17]. Standard finite difference approximation typically leads to linear complementarity problems with tridiagonal coefficient matrices. The second order upwind finite difference formulation gives rise to finite dimensional linear complementarity problems with n...

Computational Finance – Pricing The American Option

Recall that the American option has strike K and maturity T and gives the holder the right to exercise at any time in [0, T ]. The American option is not straightforward to price in the Monte Carlo framework that we have discussed. The reason is that the derivative cash flow function f(S, t) is not well defined. The problem is that we cannot compute the derivative cash flow until we know how th...

Importance Resampling with MRAS algorithm for Bermudan option pricing