Disclaimer: this project must not be taken as an investment tool it's for learning purposes only. and not trading advice.
This project focuses on the prediction of the closing price of stocks based on the closing prices of the past 60 trading days, in which two stocks will be the scope of this project, Apple stock, and Exxon Mobile stock; where Apple stock is volatile, and Exxon Mobile stock is relatively stable. I will be applying data preprocessing methods on the two datasets which are provided by Yahoo Finance API and then creating 4 LSTM models, 2 for each stock where one is a baseline model, and the other is the optimized model (tuned hyperparameters), and then comparing the effect of the volatility of the stock on the performance of the models and evaluating each model based on performance metrics such as adjusted coefficient of determination (adj 𝑅2), Mean Squared Error, Root Mean Squared Error, Mean Absolute percentage error, And measuring the accuracy of the predictions that fall within 5, 3, and 1.5 percent of the actual stock price.