Python code of commonly used stochastic models for Monte-Carlo simulations

Home Range for marine animals using dynamic brownian bridge movement models

The aim of this project is to compare different pricing methods for an Asian option. Comparisons will be made in terms of MSE, CPU time and (empirical) variance of estimators.

A collection of numerical implementations for the simulation of well-known stochastic processes on MATLAB.

The LoopMaker app lets you easily create random 3D loops with the click of a button.

PATHMC: Particle-based Approach To simulate cHemical dynamics using Monte Carlo - Consideration of interactions in the chemical stage following radiolysis.

Monte Carlo estimation of durable impairment provisions using stochastic rates, Brownian bridge correction and model point aggregation.