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BIMSA Digital Economy Lab Seminar
BIMSA Digital Economy Lab Seminar
Parsimonious Generative Machine Learning for Non-Gaussian Tail Modeling
Parsimonious Generative Machine Learning for Non-Gaussian Tail Modeling
Speaker
Time
Friday, December 5, 2025 3:00 PM - 4:00 PM
Venue
A3-2-303
Online
Zoom 435 529 7909
(BIMSA)
Abstract
The presence of non-Gaussian tails is a prevalent characteristic in many financial modeling scenarios, necessitating the use of complex non-Gaussian distributions such as the generalized beta of the second kind (GB2) and the skewed generalized $t$ (SGT). The approach we propose for modeling heavy-tailed data differs significantly from traditional methods. We utilize generative machine learning, which offers an entirely different paradigm for modeling distributions. A parsimonious nonlinear transformation is applied to a simple base random variable such as Gaussian. The parameters can be estimated effectively, and the theoretical heavy-tail properties are derived. Robust performance is observed with this approach when compared to traditional distributions. More importantly, this method is broadly useful for machine learning due to its mathematical elegance and numerical convenience.
Speaker Intro
I have been an Associate Professor at BIMSA since 2025. Prior to this role, I was an Assistant Professor at the Institute of Statistics and Big Data, Renmin University of China. My research lies at the intersection of AI and finance/business, focusing on FinTech and Business Analytics through innovative machine learning and data science methodologies. My interests include tail risk management, empirical asset pricing, portfolio optimization, derivatives, consumer credit, and related areas. Recently, I have also developed an interest in out-of-distribution (OOD) generalization and uncertainty quantification in machine learning. I publish in both finance/business and machine learning academic journals and conferences.
I am seeking highly self-motivated Postdoctoral researchers or research interns to conduct high-quality research in the areas of AI, digital economy, or applied mathematics. If you are interested, please feel free to contact me.
I am seeking highly self-motivated Postdoctoral researchers or research interns to conduct high-quality research in the areas of AI, digital economy, or applied mathematics. If you are interested, please feel free to contact me.