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Factor Modeling

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 [https://www.interactivebrokers.com/en...] for partnering with us on this webinar! To learn more about Quantopian, visit http://www.quantopian.com. Disclaimer Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.