Monte Carlo Simulation is a sophisticated computational technique used in various fields to assess and analyze complex systems or processes. Its name comes from the Casino de Monte-Carlo in Monaco, famous for its games of chance, as the method is based on randomness and probability.

The Monte Carlo Simulator application we have created is a software that allows simulating different scenarios or future outcomes based on input data. It uses the Montecarlo method, which is a statistical technique, to generate multiple simulations and assess how the results could vary depending on randomness and uncertainty. In our case, this application is used to simulate the evolution of an original capital in a financial market, generating charts that display potential growth or decline trajectories of the capital over time.

The origin of Monte Carlo simulation dates back to the 1940s during the development of the Manhattan Project, which aimed to develop the first atomic bomb. It was in this context that scientists like Stanislaw Ulam and John von Neumann began to use probabilistic methods and computers to address complex problems in nuclear physics. The name 'Monte Carlo' was adopted in reference to the famous casino in Monaco, due to the random nature of the methods used.

Monte Carlo Simulation is a technique that involves creating mathematical models or algorithms to mimic the behavior of a system or process under various uncertain conditions.

a monitor screen showing a monitor screen with a graphing line graphing down
a monitor screen showing a monitor screen with a graphing line graphing down

Example Monte Carlo simulation chart in the Joseja 2 Mini Nasdaq system