This conference invites oral presentations containing substantial theoretical and empirical advances in econometrics and statistics. All topics within the scope of Econometrics and Financial Econometrics will be considered. Topics of interest include, but are not limited to: Estimation and inference of econometric models, model selection, panel data, time series analysis, measurement error, filtering, portfolio allocation, option pricing, quantitative risk management, systemic risk and market microstructure, forecasting, volatility and risk, credit risk, pricing models, portfolio management and emerging markets, high-dimensional problems, functional data analysis, robust statistics, resampling, dependence, extreme value theory, spatial statistics, Bayesian methods, statistical learning, nonparametric statistics, multivariate data analysis, parametric & semiparametric models, numerical methods in statistics, and substantial empirical applications in these areas. Other innovative quantitative developments, such as AI and computational algorithms, are also welcome.

Guest Speakers:

Professor Lajos Horvath, Department of Mathematics, University of Utah, USA

Professor Horvath has been a fellow of the Institute of Mathematical Statistics since 1990 and has been on the ISI highly cited authors list. Research.com ranked Professor Horvath as one of the top researchers in Mathematics. In ResearchGate, his h-index is 54, and his citation number is 13,039.

Professor Horvath was born and educated in Hungary. He has published more than 380 refereed research papers in several areas, including statistics, probability, biostatistics, literature, meteorology, econometrics, and finance. Professor Horvath enjoys working with others. He has had visiting appointments at Carleton University, Ottawa, Technical University of Graz, HKUST Hong Kong, Renmin University Beijing, National University of Singapore, University of Sidney, and Université Charles de Gaulle, Lille.

Professor Horvath’s research is in mathematical statistics and stochastic processes with applications, including meteorology, biostatistics, literature, engineering, econometrics, and finance. His publications include not only theory but also applications to real-life data sets. He usually works on problems coming from real life, and the solutions require new methods. Recently, he has been working on sequential detection of changes/anomalies in large data sets, like changes in the sentiment of Twitter users.

Professor Anindya Banerjee, Department of Economics, University of Birmingham, UK, and  the Editor of Oxford Bulletin of Economics and Statistics

Professor Anindya Banerjee is the Editor of Oxford Bulletin of Economics and Statistics. He joined the University of Birmingham in January 2008 as a professor of economics. Before coming to Birmingham, he was a professor at the European University Institute in Florence and a fellow at Wadham College, Oxford. Professor Banerjee received his Ph.D. from the University of Oxford.

His interests lie in time series econometrics, including factor models and the econometrics of integrated panel data. He has recently been using his expertise in econometric modelling to examine the use of algorithmic methods in augmenting police decision-making.

Important Dates:

• Extended submission deadline: 15 May 2026

• Notification of review results: As soon as available
• Registration deadline: 31 May 2026
• Conference event: 18–20 June 2026