AIR-Quant Workshop: Tony Guida on Machine Learning for Factor Investing: From Theory to Production.

This talk will be structured as a workshop listing the ML in finance implementation’s challenges and how to overcome them from a quantitative portfolio manager point of view. We will review the main concepts one has to focus on in order to frame his/her financial ML pipeline. Those key concepts are E.D.A., empirical asset prices, model/parameters selection and backtesting protocol.
Machine learning for financial markets is NOT a copy paste from computer science. Structuring and leveraging financial domain knowledge using ML require practice, humility and guidance.

Tony Guida is a Quantitative Portfolio Manager and researcher. Tony’s work is focused primarily on extracting market inefficiencies from different sources from traditional fundamentals, market signals, alternative data, and machine learning. His expertise is in mid to low frequency in equities. Tony started his career at Unigestion in 2006 where he joined the quantitative equity low volatility team to work as a research analyst. He evolved into a member of the research and investment committee for Minimum Variance Strategies, where he led the factor investing research group for institutional clients.
In 2015, he moved to Edhec Risk Scientific Beta as a Senior Consultant for Risk allocation and factor strategies before going to a major UK pension fund in 2016 to build the in-house systematic equity, co-managing 8 billion GBP as a senior quantitative portfolio manager. He joined RAM-Active Investments in January 2019.

Tony holds a Bachelor and Master degrees in Econometry and Finance from the University of Savoy France, is the editor-in-chief and founder for the Journal of Machine Learning in Finance. Tony co-wrote and edited book “Big Data and Machine Learning in Quantitative Investment” Wiley 2018, co-wrote “Machine Learning for Factor Investing” Chapman Hall/ CRC.

He is an advisory board member for the Financial Data Professional Institute, Axess ThinkTank and a Lecturer in Machine Learning for the CQF Institute.

For any further queries, please contact peter.vodicka@cass.city.ac.uk

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