Forecasting Beer Sales with ARIMA in Python

ARIMA (Auto Regressive Integrated Moving Average) is a useful statistical modelling technique for time series forecasting. Compared to machine learning, ARIMA is a classical modeling technique that is very strong especially when the time series to be analyzed follows a clear … Continued

Color-Coded Cryptocurrency Price Charts in Python

The recent rise in the price of Bitcoin and other cryptocurrencies has also led to increased interest in visualizing price trends. In particular, price charts that use color as an overlay have a particular appeal. Such colorful price charts not … Continued

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

Correlation Matrix in Python: How Correlated are COVID-19 Cases and Different Financial Assets?

Since the sudden emergence of COVID-19, financial markets have experienced turbulent times. A sharp slump in the stock markets was followed by a sharp rise from mid-2020 onwards, bringing stock indices back to record highs by the end of the … Continued

Stock Market Prediction – Building a Univariate Model using Keras Recurrent Neural Networks in Python

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 steering towards automated predictions with machine learning. A … Continued