Advanced-Deep-Trading
Experimental implementations of financial machine learning techniques from 'Advances in Financial Machine Learning' for stochastic time series data.
What is Advanced-Deep-Trading?
Advanced-Deep-Trading is a collection of experimental implementations based on the book 'Advances in Financial Machine Learning' by Marcos Lopez de Prado. It explores how to adapt machine learning techniques from domains like computer vision and natural language processing to work effectively with financial time series data, which has unique stochastic properties that challenge traditional ML approaches.
Quantitative researchers, algorithmic traders, and data scientists working in finance who need to implement advanced machine learning techniques for financial time series analysis and trading strategy development.
Provides practical, experimental implementations of cutting-edge financial machine learning concepts from an authoritative source, helping practitioners bridge the gap between theoretical financial ML research and real-world application.
Overview
Mostly experiments based on "Advances in financial machine learning" book
Use Cases
Best For
- Implementing financial machine learning techniques from academic literature
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