Three distinguished plenary lectures across the BIFE 2024 program
BIFE 2024 features three plenary keynote lectures by internationally recognised scholars in computational finance, machine learning for finance, and reproducible quantitative research.
Prof. Wang will trace the methodological shift from classical econometric forecasting to machine-learning-based prediction of macro-financial indicators, drawing on two decades of contributions to multi-scale modelling, ensemble learning, and crisis early-warning systems. He will examine open challenges around data quality, regime change, and interpretability for policy use.
Biography. Prof. Wang is Academician of the Chinese Academy of Sciences and an internationally recognised authority in computational finance, decision analysis, and management science. He has authored more than 30 books and 400+ peer-reviewed papers, and serves on editorial boards of leading journals including IEEE Transactions on Computational Social Systems and European Journal of Operational Research.
Prof. Yu will present a unified perspective on hybrid intelligent systems — combining decomposition-ensemble learning, evolutionary optimisation, and deep learning — for early warning of crises in oil price, exchange rate, and credit markets. He will discuss the BIFE conference legacy, methodological innovation since 2008, and the research agenda for the coming decade.
Biography. Prof. Yu is among the most-cited researchers in computational economics with an h-index above 70. He co-founded the BIFE conference series in 2008 and has been principal investigator on more than 20 national-level research grants on financial intelligence.
Prof. Härdle will discuss the Quantlet ecosystem and the importance of open, reproducible quantitative research practices for the computational-finance community, with examples from cryptocurrency markets, volatility modelling, and non-parametric risk estimation.
Biography. Prof. Härdle is one of Europe's foremost statisticians, with seminal contributions to non-parametric regression and quantitative finance. He directs the Berlin Mathematical School's PhD programme in statistics and has authored more than 35 monographs.
A special industry panel on Thursday 14 November · 16:00 features senior researchers from leading Chinese FinTech firms:
Moderator: Dr. Ling Tang (Hangzhou Dianzi University)