Brooklyn Quant Experience Lecture Series: Derek Snow

Upon the request of the speaker, no recording is available for this lecture.

The Department of Finance and Risk Engineering welcomes Derek Snow, Visiting Industry Assistant Professor in the Department of Finance and Risk Engineering at NYU Tandon, to the BQE Lecture Series.

Title

Simulacrum or Shenanigan: Deep Generative Models and Simulators for Financial Markets

Abstract

Deep generative models are synthetic data generators that use deep learning algorithms to generate data that preserves the original data’s statistical features while producing entirely new data points. Deep generative models are not dynamic or reactive, whereas other data-generating techniques like multi-agent market simulators are. This presentation will identify the differences between these methods and discuss a new third-way approach that combines deep learning and agent-based models.

Bio

Derek is an assistant professor at NYU and an associate member at Oxford University’s Man Institute of Quantitative Finance and The Alan Turing Institute, the UK’s national institute for Artificial Intelligence. He was previously a visiting Doctoral scholar at the University of Cambridge and NYU’s School of Engineering. He received his Ph.D. and Honours degree with distinction from the University of Auckland, studying topics in Machine Learning for Finance. Derek has worked with some of the world’s largest quantitative research firms, and his software receives thousands of monthly downloads.