Stefan Jansen talks about Machine Learning for Algorithmic Trading

Описание: algoseek long-term data user Stefan Jansen shares his experiences on machine learning, algorithmic trading, and managing data input.

About ML4T:

Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python is the most complete and comprehensive book in the area that covers both financial and machine learning fundamentals and also replicates recent research applications published by top hedge funds like AQR or at leading Machine Learning conferences like NeurIPS.

It is not only quite long with more than 800 pages, but also includes many resources for further study. There are over 150 notebooks that illustrate machine learning techniques from data sourcing and model development to strategy backtesting and evaluation. In addition, the book lists numerous references and resources so that readers can build on this material to build their own ML for trading practice.

Finally, it covers alternative data sources beyond market and fundamental data. There are three chapters on text data that show for example how to use SEC filings to predict earnings surprises with deep learning, and the book also covers working with image data.