Data Science meets Finance: Forecasting, Econometric Modelling, and Risk Management

This in-person event brought together leading academics and practitioners to discuss the latest advances in data science applications to finance, with a focus on forecasting, econometric modelling, and risk management.

The programme featured a distinguished keynote address by Professor James W. Taylor (University of Oxford), who presented on forecast combination methods for probability distributions, intervals, and risk measures. Alongside the keynote, the conference included a series of engaging research presentations by international academic experts, covering topics such as high-dimensional penalised least squares, machine-learning market-timing strategies, the effects of extreme heatwaves on stock performance, and advanced change-point detection for functional time series.

The morning sessions kicked off with research presentations from Blanka N. Horvath (University of Oxford), Ilias Chronopoulos (University of Essex), and Marcin T. Kacperczyk (Imperial College London), followed by research presentations by Shixuan Wang, Michael Clements, Emese Lazar, and Xiaochun Meng (University of Bath).