May 18, 2017 - May 19, 2017
8:00 AM - 2:40 PM
Organized by Francis X. Diebold, Eric Ghysels, Per A. Mykland, and Lan Zhang.
Administrative assistant: Violette Swinton
Sponsored by:
Warren Center for Network and Data Sciences, University of Pennsylvania
Stevanovich Center for Financial Mathematics, University of Chicago
Penn Institute for Economic Research (PIER), University of Pennsylvania
Themes of interest are centered around scalable methods for high-dimensional dynamic econometrics; that is, high-dimensional aspects of selection, shrinkage (toward sparsity, toward reduced rank, etc.), identification schemes for variance decompositions and impulse responses, summarization and visualization, optimal filtering, time-varying parameters, mixed-frequency and missing data, real-time vintage data, etc.
Thursday, May 18th:
SESSION I: Shrinkage, Selection, Combination and Sparsity, I
Chair: Andrea Carriero (Queen Mary, University of London)
Oliver Linton (Cambridge), Jia Chen, Degui Li, and Zudi Lu, “Semiparametric Ultra‐High Dimensional Model Averaging of Nonlinear Dynamic Time Series”
Todd Clark (FRB Cleveland), Andrea Carriero, and Massimiliano Marcellino, “Large Vector Autoregressions with Stochastic Volatility and Flexible Priors”
Davide Pettenuzzo (Brandeis) and Dimitris Korobilis, “Adaptive Minnesota Prior for High‐Dimensional Vector Autoregressions”
SESSION II: High‐Dimensional Covariance Matrices
Chair: Tim Bollerslev (Duke)
Robert Engle (NYU), Olivier Ledoit, and Michael Wolf, “Large Dynamic Covariance Matrices”
Serge Nyawa (Toulouse School of Economics), Tim Bollerslev, and Nour Meddahi, “High‐Dimensional Multivariate Realized Volatility Estimation”
Nikolaus Hautsch (University of Vienna) and Stefan Voigt, “Large‐Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High‐ and Low‐Frequency Information”
Rogier Quaedvlieg (Erasmus), Tim Bollerslev, and Andrew Patton, “Realized Semi‐Covariances: Looking for Signs of Direction inside Realized Covariances”
SESSION III: Shrinkage, Selection, Combination and Sparsity, II
Chair: Nour Meddahi (Toulouse)
Domenico Giannone (FRB New York), Michele Lenza, and Giorgio Primiceri, “Macroeconomic Prediction with Big Data: the Illusion of Sparsity”
Dalibor Stevanovic (Université du Québec à Montréal), Rachidi Kotchoni, and Maxime Leroux, “Macroeconomic Forecast Accuracy in a Data‐Rich Environment”
Monica Billio (Università Ca’ Foscari di Venezia), Roberto Casarin, and Luca Rossini, “Bayesian Nonparametric Sparse Seemingly Unrelated Regression Model (SUR)”
SESSION IV: Network Econometrics
Chair: George Tauchen, Duke
Kamil Yilmaz (Koc) and Dimitris Korobilis, “Measuring Dynamic Connectedness with Large Bayesian VAR Models”
Daniela Scidá (FRB Richmond), “Structural VAR and Financial Networks: A Minimum Distance Approach to Spatial Modeling”
Weining Wang (Humboldt), Wolfgang Härdle, Hangsheng Wang, and Xuening Zhu, “Network Quantile Autoregression”
Xiu Xu (Humboldt), Cathy Yi‐Hsuan Chen, and Wolfgang Härdle, “Dynamic Credit Default Swaps Curve in a Network Topology”
Friday, May 19th
SESSION V: High‐Dimensional Dynamic Factor Modeling, I
Chair: Andrew Patton (Duke)
Serena Ng (Columbia) and Jushan Bai, “Estimation of Common Factors by Regularized Principal Components”
Viktor Todorov (Northwestern), Torben Andersen, Nicola Fusari, and Rasmus Varneskov, “Unified Inference for Nonlinear Factor Models from Panels with Fixed and Large Time Span”
Christian Brownlees (Pompeu Fabra) and Geert Mesters, “Detecting Granular Time Series in Large Panels”
SESSION VI: High‐Dimensional Dynamic Factor Modeling, II
Chair: Giorgio Primiceri (Northwestern)
Glenn Rudebusch (FRB San Francisco), Jens Christensen, and Martin Andreasen, “Term Structure Modeling with Big Data”
Matteo Barigozzi (London School of Economics) and Matteo Luciani, “Common Factors, Trends, and Cycles in Large Datasets”
Eric Ghysels (UNC) and Xi Chen, “Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty”
SESSION VII: Time‐Varying Parameters and Mixed‐Frequency Data in High‐Dimensional Filtering
Chair: Silvia Goncalves (Western Ontario)
Allan Timmermann (UCSD) and Simon C. Smith, ““Forecasting Panel Data in the Presence of Breaks”
Katerina Petrova (St. Andrews), “A Quasi‐Bayesian Local Likelihood Approach to Time Varying Parameter VAR Models”
Galina Hale (FRB San Francisco), Jose Lopez, and Glenn Rudebusch, “Monitoring Banking System Fragility with Big Data”
Manfred Deistler (Technical University of Vienna), B.D.O. Anderson, A. Braumann, E. Felsenstein, B. Funovits, L. Koebl, and M. Zamani, “High‐Frequency Linear Time Series Models and Mixed Frequency Data”, “The Structure of Multivariate AR and ARMA Systems: Regular and Singular Systems; the Single and the Mixed Frequency Case” and “Multivariate AR Systems and Mixed Frequency Data: G-Identifiability and Estimation”