Improving Monte Carlo efficiency with a simple trick

An implementation in Python,

Monte Carlo simulations encompass a broad range of algorithms that make use of statistical sampling to obtain useful information about something which is random in nature. A perfect example of this is the simulation of stock prices using stochastic models, which often require the numerical solution of a stochastic (or “noisy”) differential equation. Because differential equations represent processes which evolve in time, each solution of the equation will require N recursive steps in time (where N is something…