This conference invites oral and poster presentations containing computational or financial econometric components.

The confluence of access to large granular data sources (‘Big Data’) and the rapid advance of modelling techniques like those from machine learning (ML) promises new insights into the economy and a larger information set for policymakers. The Bank of England (BoE) and the Data Analytics for...

We welcome submissions from all fields of Bayesian econometrics (macro, micro and financial), as well as papers on statistical methodology, machine learning and computing. In addition, the Economics, Finance and Business (EFaB) section of the International Society of Bayesian Analysis (ISBA)...

WEHIA 2019 represents a unique opportunity to present and discuss the latest research on various aspects of the economy as a complex system made up of heterogeneous interacting agents. Research from different domains – economics, psychology, sociology, computer sciences, engineering, physics...

This course provides a review and practical guide to a number of microeconometric models and estimators. We focus on panel and count data models and also examine a broad class of models of discrete choice behaviour. The course emphasise two estimators, the instrumental variable estimator, and...

Topics: - Volatility and forecasting I: Univariate GARCH, theory and applications - Volatility and forecasting II: Multivariate GARCH , theory and applications - Measuring contagion among stock markets. - Panel factor models in finance - The impact of macro-announcements on the term structure,...