VTS YP Webinar: Deep Dynamic Hedging with Autonomous Economic Agents

The #IEEE Vehicular Technology Society (#VTS) serves its young professionals with events and initiatives to encourage networking, volunteerism, and career development. #5G
The Young Professionals (YP) Webinar Series is tailored for young professionals, where IEEE VTS will invite experienced professionals from academia and industry so they can share their knowledge and experiences on cutting edge technological development.
Abstract:
In the evolving landscape of data trading, the need for advanced methods to handle dynamic and diverse datasets has become increasingly crucial. This presentation introduces a novel framework for optimizing portfolio allocations in data trading markets using Autonomous Economic Agents (AEAs). Leveraging federated learning (FL), AEAs collaboratively train models while maintaining data privacy and ownership. Our approach addresses the challenges of dynamic revenue returns by integrating Histogram of Oriented Gradients (HoG) with Discrete Wavelet Transformation (DWT), enhancing the representation of non-stationary revenue patterns. Additionally, we propose a frequency-domain transformation method to efficiently manage model parameter drifts, reducing communication overhead and improving training efficiency. This presentation outlines the proposed data trading market, the innovative techniques for handling dynamic data, and the benefits of our approach in terms of privacy, data quality, and scalability.
Presented by Lei Zhao
Bio:
Lei Zhao received the B.S. and M.A.Sc. degrees in computer science and technology from Xidian University, Xi'an, China, in 2015 and 2018, respectively, and earned his Ph.D. in Electrical and Computer Engineering from the University of Victoria in 2023. He is currently a Post-Doctoral Fellow and Sessional Lecturer in the E&CE Department at the University of Victoria. His research focuses on federated learning and optimization with applications in finance.