In this chapter, the basic concepts of the Monte Carlo method have been explored. The Monte Carlo method consists of looking for the solution of a problem, representing it as a parameter of a hypothetical population, and of estimating this parameter by examining a sample of the population obtained through sequences of random numbers. To understand the basic concepts, a numerical integration using the Monte Carlo method was performed. Then, Monte Carlo techniques for prediction and control were explored.
Subsequently, a practical case was addressed: Amazon stock price prediction using Python. To analyze the performance of Amazon stock prices, we used data relating to the stock prices in the time interval from 2000-06-05 to 2018-06-05 on NASDAQ GS stock quote. This data was downloaded from the Yahoo Finance website. Then, a model based on a BSM formula was fit. Finally,...
