Using Simulation Models for Financial Engineering

The massive use of systems based on artificial intelligence and machine learning has opened up new scenarios for the financial sector. These methods can increase benefits, not only, for example, by protecting user rights but also in terms of macroeconomics.

Monte Carlo methods find a natural application in finance for the numerical resolution of pricing and option coverage problems. Essentially, these methods consist of simulating a given process or phenomenon using a given mathematical law and a sufficiently large set of data, created randomly from distributions that adequately represent real variables. The idea is that, if an analytical study is not possible, or adequate experimental sampling is not possible or convenient, the numerical simulation of the phenomenon is used. In this chapter, we will look at practical cases of using simulation methods in a financial context. You will learn how to use Monte Carlo methods to predict...