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https://github.com/hudson-and-thames/mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
https://github.com/hudson-and-thames/mlfinlab

algorithmic-trading finance financial-machine-learning investing machine-learning portfolio-management portfolio-optimization python quantitative-finance research trading

Last synced: 24 days ago
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MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

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README 

        


   

   

   

   

  




# Welcome to Machine Learning Financial Laboratory! 





    





>This repo is public facing and exists for the sole purpose of providing users with an easy way to raise bugs, feature requests, and other issues.





    





## What is MlFinLab?

MlFinlab python library is a perfect toolbox that every financial machine learning researcher needs. 



It covers every step of the ML strategy creation, starting from data structures generation and finishing with backtest statistics.

We pride ourselves in the robustness of our codebase - every line of code existing in the modules is extensively tested and 

documented.



## Documentation, Example Notebooks and Lecture Videos

For every technique present in the library we not only provide extensive documentation, with both theoretical explanations

and detailed descriptions of available functions, but also supplement the modules with ever-growing array of lecture videos and slides 

on the implemented methods.

 

We want you to be able to use the tools right away. To achieve that, every module comes with a number of example notebooks 

which include detailed examples of the usage of the algorithms. Our goal is to show you the whole pipeline, starting from 

importing the libraries and ending with strategy performance metrics so you can get the added value from the get-go.





   

   

   

   

   

   

   

   

   




### Included modules:



- Backtest Overfitting Tools

- Data Structures

- Labeling

- Sampling

- Feature Engineering

- Models

- Clustering

- Cross-Validation

- Hyper-Parameter Tuning

- Feature Importance

- Bet Sizing

- Synthetic Data Generation

- Networks

- Measures of Codependence

- Useful Financial Features



## Licensing options

This project is licensed under an all rights reserved [licence](https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt).



* Business

* Enterprise



## Community

With the purchase of the library, our clients get access to the Hudson & Thames Slack community, where our engineers and other quants 

are always ready to answer your questions.



Alternatively, you can email us at: [email protected].





   

   

   




## Who is Hudson & Thames?

Hudson and Thames Quantitative Research is a company with the goal of bridging the gap between the advanced research developed in 

quantitative finance and its practical application. We have created three premium python libraries so you can effortlessly access the

latest techniques and focus on what matters most: **creating your own winning strategy**.



### What was only possible with the help of huge R&D teams is now at your disposal, anywhere, anytime.