7th Vienna Workshop on High Dimensional Time Series
in Macroeconomics and Finance
IHS, Vienna | 28-29 May 2026
Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
|
Daily Overview | |
| Location: Lecture Room E02 |
| 9:00am - 10:00am |
P1: Plenary 1 - Roberto Casarin Location: Lecture Room E02 Chair: Leopold Sögner, Institute for Advanced Studies |
| 10:30am - 12:00pm |
PS-1A Location: Lecture Room E02 Learning Nonlinear Factor Models with Unknown Monotone Links from Incomplete and Noisy Data 1: Technical University of Munich, Germany; 2: Virginia Tech, United States of America Non-Gaussian Structural Dynamic Factor Models: Identification, Estimation, and Applications 1: University of Warsaw, Poland; 2: University of Notre Dame, USA; 3: Bank of England and King’s College London, UK Factor-based imputation of missing values using cross-section averages 1: Lund University, Sweden; 2: Örebro University |
| 1:30pm - 3:00pm |
PS-2A Location: Lecture Room E02 Incorporating Micro Data into Macro Models Using Pseudo VARs 1: University of Strathclyde, United Kingdom; 2: Federal Reserve Bank of Cleveland, United States of America Bayesian modelling of VAR precision matrices using stochastic block networks 1: University of Salzburg, Austria; 2: University of Strathclyde, Great Britian; 3: Bocconi University, Italy Nonlinear Autoregressive Models for Functional Time Series with Bayesian Additive Regression Trees 1: University College Dublin, Ireland; 2: University of Texas Health Science Center at Houston; 3: NEOMA Business School; 4: Erasmus University Rotterdam; 5: Michigan State University |
| 3:00pm - 3:45pm |
Poster 1 Location: Lecture Room E02 Let the Tree decide: FABART \\ A Non-Parametric Factor Model 1: Banco de España, Spain; 2: University College Dublin Inflation Forecasting with Large Language Models: A Real-Time Evaluation Against Central Bank Projections SGH Warsaw School of Economics, Poland Envelope Matrix Autoregressive Models SIUC, United States of America Density nowcasts for U.S. GDP by probabilistic neural networks Department of Artificial Intelligence and Systems Engineering, Budapest University of Technology and Economics BIS Time-series Regression Oracle 1: Bank for International Settlements, Switzerland; 2: Saarland University Gradient-Boosted Panel MIDAS Trees 1: Erasmus University Rotterdam, Netherlands, The; 2: Tinbergen Institute, Netherlands, The Central bank independence and the transmission of external shocks in small open economies Central Bank of Ireland, Ireland How to certify positivity of a given signed mixture of statistical densities. 1: University College Cork, Netherlands, The; 2: University of Trento, Italy Forecast Combination with Random Subspaces: Accuracy Gains and Interpretability Halle Institute for Economic Research (IWH), Germany Bilinear Time Variation for High Dimensional TVP-VARs 1: Örebro University School of Business; 2: Fondazione ENI Enrico Mattei Robust Tests of Forecast Accuracy for Factor-Augmented Regressions with an Application to the Novel EA-MD-QD Dataset 1: University of Bologna, Italy; 2: University of Freiburg, Germany; 3: BI Norwegian Business School, Norway |
| 3:45pm - 5:15pm |
PS-3A Location: Lecture Room E02 Implied Factors: The Linear Skeleton of Machine Learning Forecasts 1: UQAM, Canada; 2: Bank of Canada; 3: ECB Optimal Predictor Selection for Macroeconomic Time Series using Variable Importance in Random Forests ETH Zürich, Switzerland Mapping the Design Space of High-Dimensional Macroeconomic Nowcasting 1: Institute for Advanced Studies (IHS), Vienna, Austria; 2: Vienna University of Economics and Business (WU), Vienna, Austria; 3: Vienna Graduate School of Finance (VGSF), Vienna, Austria Chronos-2: From Univariate to Universal Forecasting Boston College, United States of America |
| 5:30pm - 6:30pm |
P2: Plenary 2 - Melanie Schienle Location: Lecture Room E02 |
| 9:00am - 10:00am |
P3: Plenary 3 - Serena Ng Location: Lecture Room E02 |
| 10:30am - 12:00pm |
PS-4A Location: Lecture Room E02 Chair: Leopold Sögner, Institute for Advanced Studies Nowcasting Low-Income Countries Through Global Linkages 1: Johns Hopkins University; 2: International Moentary Fund Quantifying Demand Shocks in the Green and Digital Transition 1: University of Milan Bicocca + FEEM, Italy; 2: University of Milan + FEEM, Italy Unfolding Regional Business Cycles: Factor Models for Three-Way State-Level Tensors University of Alberta, Canada |
| 1:30pm - 3:00pm |
PS-5A Location: Lecture Room E02 Common factors in large panels of equity options 1: Neoma Business School, France; 2: Erasmus University Rotterdam; 3: Luiss University; 4: IESEG School of Management The US yield curve with cointegration and a time-varying factor structure 1: Università degli Studi dell'Insubria, Italy; 2: Fondazione Eni Enrico Mattei, Italy; 3: Università Politecnica delle Marche, Italy Common Factors in Currency Characteristics University of Innsbruck, Austria |
| 3:00pm - 3:45pm |
Poster 2 Location: Lecture Room E02 The Predictive Power of Fedspeak 1: Bloomberg, United States; 2: Bloomberg, Germany Are there asymmetries in euro area monetary policy? 1: WU Vienna; 2: Oesterreichische Nationalbank, Austria Building Climate Indices of Maximal Macroeconomic Relevance via the Assemblage VAR 1: University Bocconi, Italy; 2: Université du Québec à Montréal; 3: ETH Zurich Per capita Income Convergence in Central Europe: Does the 2004 Accession to the European Union matter? University of Warsaw, Poland Forecast Combination for Tail Risk with Regulator-Aware Decision Trees 1: Erasmus University Rotterdam; 2: University of Birmingham, United Kingdom Monthly GDP estimates for the euro area and its countries 1: European Central Bank, Germany; 2: Deutsche Bundesbank; 3: University of Leicester Comparison in Dynamic Forecasting: A Bayesian LASSO State-Space and Bayesian Factor VAR Analysis University College Dublin, Ireland Exploiting common volatility dynamics in high-dimensional portfolio selection University of Regensburg, Germany Behind the Curve: How the Fed Missed Inflation Risks Using a High-Dimensional Distributional VAR (HiDVAR) 1: Institute for Monetary and Financial Stability, Germany; 2: Goethe University Frankfurt, Germany Nelson–Siegel Autoencoders for Global Yield Curve Forecasting 1: Erasmus School of Economics, Netherlands, The; 2: Neoma Business School, France Signal-Selected Sparse Equal-Weight Portfolios 1: University of Hagen, Germany,; 2: Aalborg University Business School, Denmark |
| 3:45pm - 5:45pm |
PS-6A Location: Lecture Room E02 GENERALLY SHIFTING COEFFICIENTS IN INTERACTIVE EFFECTS PANEL DATA MODELS AND THE UNIQUE COVID-19 REGIME 1: Örebro University, Sweden; 2: Lund University, Sweden Change Point and Bubble Detection in Time Series Using Mixed Integer Programming 1: HSE University, Russian Federation; 2: University of Sydney; 3: University of South Florida Determinants and forecasting of German day-ahead electricity prices and volatility University of Cagliari, Italy |
| 5:30pm - 6:30pm |
P4: Plenary 4 - Domenico Giannone Location: Lecture Room E02 |
