All about Artificial Intelligence and Machine Learning for Banking, Finance and Trading
Arificial Intelligence and Machine Learning for Finance and Banks
Using a Vanilla LSTM for Stock Predictions Time-series is a data format that is very tough to manage. Compared to cross-sectional data, a data format to which you can directly apply machine learning algorithms without ...
Taking Advantage of Steepness to Find Trading Signals in Python. Finding signals and patterns inside a random-like market is not an easy job and as such, one has to seek out every possible way to ...
Using Basic Information to Create a Profitable Trading Strategy. Trading strategies are the essence of buying and selling in the markets. Many traders have their reasons to participate. A strategy begins with an idea which ...
In this post I show you how to predict stock prices using a forecasting LSTM model Source
On the dangers of walk-forward backtesting, how to measure them and not feel right, but to be right Source
This rare gem is a trend-following indicator that can be used either as a trading system or as a way to place your stops. We will introduce the intuition of the SuperTrend indicator, code it ...
One of the most popular packages used for interactive visualizations is Plotly. Plotly is built on top of python and enables data scientists to produce professional and great-looking plots with less-code. It became popular because ...
Insights from Chaos Theory Applied to Trading. A Study in Python. Source
I have tested in real-time the implementation coded with Python of a famous mathematical technics to predict market movement (Bollinger Band) to check the gap between theory and reality. And here is the result. Source
A case study with technical analysis, feature selection, accuracy score & bias-variance trade-off Source