After the COVID-19 pandemic and the travel restrictions that followed, we are slowly getting back on track. Between April and December 2024, we had visitors from 9 countries around the world 🌍, who engaged in long – sometimes late into the evening 😏 – discussions with us and gave stimulating talks at the S3 Seminar:
- Hans Auer (Energy Economics Group, TU Wien, AUT 🇦🇹) on Peer-to-peer trading implementation case studies in electricity markets considering uncertainty
- Jozef Barunik (Institute of Economic Studies, Charles University, Prague, CZE 🇨🇿) on Predicting the volatility of major energy commodity prices: the dynamic persistence model
- Guglielmo Maria Caporale (College of Business, Arts and Social Sciences, Brunel University London, GBR 🇬🇧) on Global food prices and inflation
- Jieyu Chen (Institute of Statistics, KIT, Karlsruhe, GER 🇩🇪) on Trading on short-term path forecasts of intraday electricity prices – generative machine learning methods
- Frederic Dias (School of Mathematics and Statistics, University College Dublin, IRL 🇮🇪) on Ocean waves: the perfect example of a complex system
- Yan Gao (Department of Systems Science, Business School, University of Shanghai for Science and Technology, Shanghai, CHN 🇨🇳) on Real-time pricing based on demand side management for smart grid
- Luboš Hanus (Institute of Economic Studies, Charles University, Prague, CZE 🇨🇿) on Learning probability distributions of day-ahead electricity prices
- Rainer Hegselmann (MODUS, University of Bayreuth and Frankfurt School of Finance & Management, GER 🇩🇪) on Computational social epistemology: A case study on two-armed bandits versus inductive truth seekers and epistemic free riders with bounded confidence
- David Obst (Department of Statistics & Mathematical Optimization, EDF R&D, Palaiseau, FRA 🇫🇷) on Expert aggregation and metrics for short-term electricity price forecasting
- Antony Ware (Department of Mathematics and Statistics, University of Calgary, CAN 🇨🇦) on Reliability-constrained hydropower valuation
- Sjur Westgaard (IØT, NTNU, Trondheim, NOR 🇳🇴) on Forecasting expected shortfall for energy commodities using quantile regression
Curious to see what 2025 will bring …
