Trading predictions using AI and Python

Originally published at: Trading predictions using AI and Python | EODHD APIs Academy

I’ve tried a number of techniques for predicting stock prices including forecasting tools like Facebook Prophet, statistical approaches like the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, machine learning techniques like Polynomial Regression, and finally an AI recurrent neural network (RNN). There are a number of AI models and techniques but I’ve found an Long Short-Term Memory (LSTM) model gets the best results. An LSTM model is a type of recurrent neural network (RNN) architecture designed to effectively handle sequence prediction problems. Unlike traditional feedforward neural networks, LSTM has a memory-like architecture that allows it to maintain contextual information over long sequences, making it ideal for time-series prediction, natural language processing, and other sequence-dependent tasks. It overcomes the limitations of…