The purpose of this research is to identify an artificial intelligence tool based on neural networks to predict the behavior of performance and risk of the set of financial assets based on actions that more accurately reflect the stock market movement of the Peruvian stock market. The research initially identified the most appropriate financial asset to estimate the performance and risk values of the 50% most liquid share portfolio in the Peruvian market in the 2010-2016 period. From the selected asset, the technique of artificial neural networks with a multilayer perceptron with regression configured with 3 layers (21,85,2) was used, using a logistic activation function with an LBFGS optimizer at a learning rate of 0.01 to establish the financial, operational, commercial or corporate governance patterns that can explain and / or predict the behavior of the same in the market. The resear...