Detailed Program - Financial Econometrics 2022

Session 1: Forecasting

David Kohns: A New Bayesian MIDAS Approach for Flexible and Interpretable Nowcasting

Tony Chernis: Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis

Ignacio Crespo: Does Anything Beat a Factor Model? Comparing Predictive Accuracy in Large Panels of Macroeconomic Time Series

Keynote lecture

John Maheu: Modeling and Forecasting Bull and Bear Markets

Session 2: Portfolio Analysis

Vilhelm Niklasson: Bayesian modelling of optimal portfolio weights using different sources of information

Taras Bodnar: Dynamic shrinkage estimation of the high-dimensional minimum-variance portfolio

Alfonso Valdesogo: Hedge Fund Investment: Optimal Portfolios with Regime-Switching

Session 3: Bayesian Econometrics

Matteo Iacopini: Adaptive Subspace Shrinkage with Mixture Functional Horseshoe Priors

Ping Wu: Spike and Slab Priors on Variable Orderings in VARs

Jan Prüser: Improving inference and forecasting in VAR models using cross-sectional information

Session 4: Tail risk

Aristeidis Raftapostolos: Deep Quantile Regression

Cristina Amado: Modelling Time-Varying Volatility Interactions

Matteo Iacopini: Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP

Keynote lecture

Marta Banbura: Advances in Modeling Time-Varying Trends using Large VARs: Order-Invariant Stochastic Volatility, Hierarchical Shrinkage and Outliers

Session 5: Financial Econometrics

Veni Arekelian: And Pythia said: ”Buy not sell"; An analysis of analyst recommendations betting on sparsity

Daniele Bianchi: Taming Momentum Crashes

Daan Opschoor: A Smooth Shadow-Rate Dynamic Nelson-Siegel Model for Yields at the Zero Lower Bound