How can systematic investors, discretionary investors, and risk managers set themselves up for success when using alternative data?

This course, from the authors of “The Book of Alternative Data”, outlines a nine-step approach to integrating alternative data into any investment process. From setting up a vision and strategy and identifying appropriate datasets, to signal extraction and deployment in production, it instructs learners in the process of making money by investing with alternative data. The course discusses how to structure teams to use alternative data, and presents several use cases for web data, satellite imagery data, consumer transaction data, and more.

Faculty Experts:

SAEED AMEN is the founder of Cuemacro and co-founder of Thalesians. Over the past fifteen years, Saeed Amen has developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura. He is also the author of Trading Thalesians: What the ancient world can teach us about trading today (Palgrave Macmillan) and is the coauthor of The Book of Alternative Data (Wiley).

ALEXANDER DENEV is a former Head of AI and the Data Science team for Financial Services - Risk Advisory. His responsibilities included development of AI products and advisory around risks and ethical implementation of AI. He also focussed on Alternative Data, AI for Data Quality and AI for Retail Banking. Previously, Alexander was a former Head of Quantitative Research & Advanced Analytics at IHS Markit.

Prior to that, Alexander has worked in Risk Dynamics (McKinsey & Company), The Royal Bank of Scotland, European Investment Bank (EIB) and European Investment Fund (EIF), National Bank of Greece and Societe Generale.

Alexander holds a degree in Mathematical Finance from University of Oxford where he has been a Visiting Lecturer on Bayesian Risk Management and Alternative Data. He wrote several papers and books on quantitative topics, ranging from stress testing and scenario analysis to asset allocation through Machine Learning techniques and alternative data.