The Department of Finance and Risk Engineering welcomes Sandrine Ungari, Head of Cross-Asset Quantitative Research Team at Société Générale, to the BQE Lecture Series.
A Brief History of Quant Investing – from Traditional Equity Factors to Machine Learning
Over the past few decades, systematic quantitative investing has gathered interest from a wide range of investors ranging from hedge funds to asset owners. In this presentation, we review a few of the most emblematic systematic strategies, and discuss their more recent implementations making use of modern statistical learning. Differences in performance across factors and cycles highlight the importance of having a portfolio framework. We show how diversification can be a factor of performance in that field too.
Sandrine Ungari is currently Head of Cross-Asset Quantitative Research team at Société Générale. The Quantitative Research team has been recognised as a market leader in quantitative research and is recipient of the 2020 Risk Award for Research House of the Year. Sandrine's research topics cover systematic strategies across asset classes, interest rate modeling, machine learning, statistical analysis and portfolio construction. She joined Société Générale in 2006. Prior to that, she worked as a quantitative analyst at HBOS Treasury and at Reech Sungard in London. She is a graduate of ENSTA (Paris) and holds a Master's in Quantitative Finance from Paris VI University.