🎙️ Who is Peter Cotton?
Peter Cotton is a highly accomplished and experienced Quant who currently leads data science for Intech Investments, where he works on the theory and practice of portfolio construction. He has invented Schur Portfolio allocation, which unifies machine learning HRP and more traditional MPT approaches. With his expertise in the field, he has also created and maintained various microprediction projects, including packages, books, and live probability exchange. Peter has previously founded Benchmark Solutions, an enterprise data company that was later acquired by Bloomberg, and worked at J.P. Morgan, where he pioneered control theory application to OTC trading and privacy-preserving Machine Learning. At Morgan Stanley, he also invented closed-form CDO pricing, marking the start of his career. During the pandemic, Peter has been coping with zwift, bullet chess, and amateur epidemiology.

💡 In this episode...
In this episode we received Peter Cotton, a highly accomplished and experienced Quant who currently leads data science for Intech Investments. He discusses his work on the theory and practice of portfolio construction and his invention of Schur Portfolio allocation. Peter has also created and maintained various microprediction projects, founded Benchmark Solutions, and worked at J.P. Morgan, where he pioneered control theory application to OTC trading and privacy-preserving Machine Learning. He shares his insights on the adoption and implementation of data science technology in finance and his entrepreneurial journey and experience in the hedge fund industry. Peter also talks about the importance of markets in prediction and reflects on AI regulation, capabilities, and future implications. 

Peter Cotton: https://www.linkedin.com/in/petercotton/
Thomas Bustos: https://www.linkedin.com/in/thomasbustos/

Artistic Direction & Video: Maxence Kerhoas

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