Feature Engineering for Multivariate Time Series Prediction with Python

Multivariate time series predictions and especially stock market forecasts pose challenging machine learning problems. Unlike univariate forecasting models, multivariate models do not rely exclusively on historical time series data, but use additional functions that are often developed from the time … Continued

Building Multivariate Time Series Models for Stock Market Prediction with Python

Time series prediction has become a major domain for the application of machine learning and more specifically recurrent neural networks. Well-designed multivariate prediction models are now able to recognize patterns in large amounts of data, allowing them to make more … Continued

Stock Market Prediction – Adjusting Time Series Prediction Intervals

Time series prediction Time series prediction is a hot topic of machine learning. In a previous post on stock market forecasting, I have shown how you can build a prediction model for the S&P500 Stock Market Index. The prediction interval … Continued

Building a Simple Univariate Model for Stock Market Prediction using Keras Recurrent Neural Networks and Python

Stock market prediction: a time series forecasting problem Forecasting the price of financial assets has fascinated researchers and analysts for many decades. While traditional prediction methods of technical analysis and fundamental analysis are still widely used, interest is now increasingly … Continued