The algorithm's name refers to the grand casino in the Principality of Monaco at Monte Carlo For example, in the stock market, Montecarlo-based risk assessment models are normally used to determine 'signals' (trends) that indicate a stock investor when or when not to invest on certain portfolios.

This feature allows you to build risk models based on such events and provide a visual way to interpret/quantify that risk and act accordingly. The purpose of running such algorithm is to simulate what would statistically happen on valid random events for any scenario we want to analyze (gambling in this tutorial). In a very simplistic synopsis, Montecarlo is an algorithm that allow you to randomly sample a probability distribution. If you were to invest/bet/etc on a high volatility environment (e.g casino), would you like to know what are the chances you win? Or better yet worded, what are the chances you may be at risk and lose your money? The most important question remains, how do you simulate all likely scenarios? Is that even possible? Well, in this tutorial we analyze one of the simplest solutions, Monte Carlo simulations. This tutorial assumes you have NodeJS and react tooling installed.

The technologies we will discuss in this tutorial are: Typescript and React. We will create a very basic risk assessment model for a casino Roulette game. In this tutorial we will discuss what MonteCarlo simulations are and how they are useful in several areas (gambling, finance, health, etc).

Simple roulette game using 2 classes