Text Books
If you’re looking to learn more about using MlFinLab, we highly recommend checking out the following two textbooks:
Advances in Financial Machine Learning by Marcos Lopez de Prado is considered by many to be the gold standard and go to text in the field. MlFinLab started by implementing all the techniques in this book and thus it is an excellent resource for those interested in using machine learning techniques to analyze and make predictions about financial data. The book covers a wide range of topics, including how to implement machine learning algorithms in Python, and is filled with practical examples and case studies.
Machine Learning for Asset Managers by Marcos Lopez de Prado is the follow up text with newer techniques and further elaborations on concepts such as Meta-Labeling.
Overall, these two textbooks are a great starting point for anyone looking to get started with financial machine learning.
For those looking to stay up to date with the latest advancements in the field, we recommend the Journal of Financial Data Science (JFDS), which is a peer-reviewed academic journal that publishes research on the use of data science techniques in finance.
The journal covers a wide range of topics, including machine learning, natural language processing, and high-dimensional data analysis, and is aimed at researchers and practitioners working in the field of of trading and investment management. The JFDS is published by PMResearch, an organization dedicated to advancing the field of financial data science through research, education, and outreach. Overall, the JFDS is a valuable resource for anyone interested in staying up-to-date with the latest research and developments in the field of financial data science.