The Premier Event for Quantitative Investment Thought Leaders
Dr. Daniele Bianchi
Associate Professor at the School of Economics and Finance Queen Mary, University of London
I am an Associate Professor at the School of Economics and Finance, Queen Mary University of London. He was awarded a Ph.D. by the Department of Finance at Bocconi University. I have been a visiting economist at the Research Division of the Sveriges Riksbank and a visiting scholar at the McCombs School of Business at UT Austin in Texas, as well as at the Nova School of Business and Economics in Lisbon. My research interests span empirical asset pricing, Bayesian econometrics, and machine learning. My main publications include The Review of Financial Studies, the Journal of Econometrics, the Journal of Business and Economic Statistics, and the Journal of Banking and Finance.
Day 2: 15 October
9:20 AM Machine Learning interpretability methods in Finance
Overview objectives:
- Introducing the application of ML interpretability
- Highlight frameworks that ensure transparency and regulatory alignment in ML-driven strategies
- Examine academic research on explainable AI (XAI) models tailored to financial practical use cases and real-world industry examples
- Discuss the trade-off between model complexity and interpretability in alpha generation
Check out the incredible speaker line-up to see who will be joining Daniele.
Download The Latest Agenda
