A common technique in quantitative finance is that of ranking stocks by using a combination of fundamental factors and price-based signals. The resulting factors can be used for many purposes, from cross-sectional equity models to performance attribution. In this webinar, Max Margenot, Academia & Data Science Lead at Quantopian, discusses factor models and how they fit into a common quantitative workflow.
About the Speaker: Max Margenot
Max Margenot is Quantopian’s Academia and Data Science Lead. His background is in applied mathematics, statistics, and quantitative finance. He runs the online lecture series at Quantopian and is responsible for workshop curriculums and educational content. In addition to having experimented with algorithmic trading of cryptocurrencies and Bayesian estimation of covariance matrices, Max has published work in theoretical mathematics. He works with top universities including Columbia, U Chicago, and Cornell and holds a MS in Mathematical Finance from Boston University.
Thank you to Interactive Brokers [www.interactivebrokers.com/en...] for partnering with us on this webinar!
To learn more about Quantopian, visit www.quantopian.com.
Disclaimer
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
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