Introduction to Monte Carlo Model

This Blog entry is from the Monte Carlo Model section in Learn Palisade.

Monte Carlo Simulation is a technique to create many random simulations based upon a random case (i.e. a transaction).   The random value can be forced to obey certain statistical assumptions, which in this example will be a triangular distribution.  Monte Carlo simulation is an enormous topic in its own right yet these procedures are intended to give just a basic overview of the tool and allow for the simulation of models created in these procedures.

Simulation for Communication refers to being able to run models based on explainable statically assumptions so to facilitate expectation setting for the models impact.  Furthermore, that millions of random simulations will be exposed to the model, where records of both the randomly generated record and the output are retained, Monte Carlo simulation can help identify scenarios where there is potential for optimisation or risk mitigation.