Papers for intro to Statistical Arbitrage

This page summarizes the projects mentioned and recommended in the original post on /r/algotrading

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  • pyRMT

    Python library for Random Matrix Theory, cleaning schemes for correlation matrices, and portfolio optimization

  • A nice intro is given here https://www.cfm.fr/assets/ResearchPapers/2016-Cleaning-Correlation-Matrices.pdf . The implementations aren’t super complex, but this package https://github.com/GGiecold/pyRMT has a bunch in one place that you can try out, plus a couple more references. In general this is quite an important problem and useful outside of finance too so there’s a lot of stuff on Google scholar and more comes out every year. Ledoit+Wolf, Bouchaud+Potters are some of the authors to look out for.

  • machine-learning-for-trading

    Code for Machine Learning for Algorithmic Trading, 2nd edition.

  • You have to be a little careful with ML if you’re putting it to use, a couple books that give some good practices are https://ml4trading.io/ and https://www.wiley.com/en-gb/Advances+in+Financial+Machine+Learning-p-9781119482086 .

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    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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