We consider the recently introduced Transformation-based Markov Chain Monte Carlo (TMCMC) (Stat. Methodol. 16 (2014) 100–116), a methodology that is designed to update all the parameters ...

We propose a new, flexible framework using Monte Carlo methods to price Parisian options not only with constant boundaries but also with general curved boundaries. The proposed approach also enables a ...

In this paper, we develop a Monte Carlo method that enables us to price instruments with discontinuous payoffs and nonsmooth trigger functions; this allows a stable computation of Greeks via finite ...

The application of Bayesian methods to large-scale phylogenetics problems is increasingly limited by computational issues, motivating the development of methods that can complement existing Markov ...

Pete Rathburn is a copy editor and fact-checker with expertise in economics and personal finance and over twenty years of experience in the classroom. Getty Images / Monty Rakusen Analysts can assess ...

Uncertainty and risk are issues that virtually every business analyst must deal with, sooner or later. The consequences of not properly estimating and dealing with risk can be devastating. There’s a ...

Monte Carlo methods have become indispensable in simulating light transport due to their flexibility in handling complex phenomena such as scattering, absorption, and emission in heterogeneous media.

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and ...