Peter Hafez is the head of data science at RavenPack. Since joining RavenPack in 2008, he’s been a pioneer in the field of applied news analytics bringing alternative data insights to the world’s top banks and hedge funds. Peter has more than 15 years of experience in quantitative finance with companies such as Standard & Poor’s, Credit Suisse First Boston, and Saxo Bank.
He holds a Master’s degree in Quantitative Finance from Sir John Cass Business School along with an undergraduate degree in Economics from Copenhagen University. Peter is a recognized speaker at quant finance conferences on alternative data and AI, and has given lectures at some of the world’s top academic institutions including London Business School, Courant Institute of Mathematics at NYU, and Imperial College London.
Keynote: Modeling News Impact Asymmetries
RavenPack Analytics brings the latest innovations in natural language processing – providing deeper textual analysis of unstructured documents, as compared to its predecessor. Focusing on the new event relevance and novelty scores, Peter will show how to take advantage of asymmetries stemming from event group heterogeneity to achieve stronger risk-adjusted performance. Specifically, he’ll highlight various examples that showcase the significant benefits of going beyond the headline when trading European and US equities.