A Monte Carlo simulation allows analysts and advisors to convert investment chances into choices by factoring in a range of values for various inputs.

The Monte Carlo simulation estimates the probability of different outcomes in a process that cannot easily be predicted because of the potential for random variables.

A Monte Carlo simulation helps investors by modeling potential investment outcomes using randomization and computer algorithms.

On a canonical set of stochastic simulation examples including population-based Markov chain Monte Carlo methods and Sequential Monte Carlo methods, we find speedups from 35- to 500-fold over ...