Arificial Intelligence and Machine Learning for Finance and Banks
Whatever your product might look like, there’s usually one or more Python libraries that can do the legwork for you. So, instead of re-inventing the wheel, let’s have a look at which packages can facilitate ...
A simple yet useful method to optimize the process of choosing stocks Source
Using VADER (Valence Aware Dictionary and sEntiment Reasoner), Pushshift API, Spacy’s Named Entity Recognition, and Spearman rank-order correlation test. Source
Model the volatility of the S&P500 to classify the market into three different segments to enhance algorithmic trading strategies. Source
Swiss researchers at the Ecole Polytechnique fédérale de Lausanne (EPFL) predicted market crashes using topological data analysis (TDA). Post Doc Guillaume Tauzin with fellow researchers introduced giotto-tda, a Python library that integrates topological data analysis with ...
In this article, must know 7 Python libraries/ modules used in Finance and Financial Technology. Source
Python packages that simplify and automates trades. Some packages will be heavily focused on the US market. Source
Using the Fractal Indicator With Moving Averages to Trade the Markets. Source
It’s a platform that helps potential students with their journey of learning about quantitative finance with Python. Source
Reinforcement learning here stands out as a Holy Graal — no need to do intermediate forecasts or rule creation — you just have to define a target and the algorithm will learn the exact rules ...