Hi-Di NET
Econometric Analysis of High Dimensional Network Structures in Macroeconomics and Finance
The Project
High dimensional modelling and large dataset handling have gained attention in Economics and Finance, given also the recent surge of publicly available data. One of the key challenges of high-dimensional models is the complex interactions among variables and the inferential difficulty associated with handling large datasets.
The project Hi-Di NET deals with the 3 key aspects for forecasting and structural analysis:
- network effects and interconnectedness;
- time variation in the relationships;
- large cross section of variables and high dimension databases.
It is organised in 3 WPs dealing with:
- inclusion of network into time series analysis to deal with dynamics and time dependence;
- inference on observed and latent networks and identification issues;
- use of large datasets and related computational challenges.
The aim is to develop novel multivariate econometric models and efficient methods suitable for high dimension databases and able to deal with network effects and time varying relationships.
From an applied perspective, the Hi-Di NET project will deal with the central theme of financial and macroeconomic stability, declined in 3 empirical vertical streams related to highly relevant topics: systemic risk, uncertainty impact and new fintech instruments.
Events
People
Principal Investigator
Monica Billio, Full Professor of Econometrics, Department of Economics, Ca' Foscari University of Venice
Associated Investigators
Roberto Casarin, Full Professor of Econometrics, Department of Economics, Ca' Foscari University of Venice
Giuseppe Cavaliere, Full Professor of Econometrics, Department of Economics, University of Bologna
Luca Fanelli, Full Professor of Econometrics, Department of Economics, University of Bologna
Massimo Guidolin, Full Professor of Econometrics, Department of Finance, Bocconi University
Massimiliano Giuseppe Marcellino, Full Professor of Econometrics, Department of Economics, Bocconi University
Francesco Ravazzolo, Full Professor of Econometrics, Department of Economics, University of Bozen
Researchers
Michele Costola, Research Fellow in Economic Policy, Department of Economics, Ca' Foscari University of Venice
Jan Ditzen, Research Fellow in Econometrics, Department of Economics and Management, University of Bozen
Yu Bai, Research Grant Holder, Department of Economics, Bocconi University
Graziano Moramarco, Research Grant Holder, Department of Economics, University of Bologna
Publications
- Angelini G., Cavaliere G., Fanelli L., 2022, Bootstrap inference and diagnostic in state space models: with applications to dynamic macro models, Journal of Applied Econometrics, vol. 37, pp 3-22
- Billio M., Casarin R., Kaufmann S., Iacopini M., 2022, Bayesian Dynamic Tensor Regression, Journal of Business and Economic Statistics
- Billio M., Casarin R., Iacopini M., 2022, Bayesian Markov Switching Tensor Regression for Time-varying Networks, Journal of the American Statistical Association
- Billio M., Frattarolo L., Guégan D., 2022, High Dimensional Radial Symmetry of Copula Functions: Multiplier Bootstrap vs. Randomization, Symmetry, vol. 14, 1, 97
- Billio M., Maillet B., Pelizzon L., 2022, A meta-measure of performance related to both investors and investments characteristics, Annals of Operations Research, vol. 313, 2, pp 1405-1447
- Cavaliere G., Lu Y., Rahbek A., Stærk-Østergaard J., 2022, Bootstrap inference for Hawkes and general point processes, Journal Econometrics
- Iacopini M., Ravazzolo F., Rossini L., 2022, Proper Scoring Rules for Evaluating Asymmetry in Density Forecasting, Journal of Business and Economic Statistics
- Agudze K. M., Billio M., Casarin R., Ravazzolo F., 2021, Markov Switching Panel with Endogenous Synchronization Effects, Journal of Econometrics
- Ahelegbey D.F., Billio M. , Casarin R., 2021, Modeling Turning Points in the Global Equity Market, Econometrics and Statistics
- Billio M., Frattarolo L., Guégan D., 2021, Multivariate Radial Symmetry of Copula Functions: Finite Sample Comparison in the i.i.d Case, Dependence Modeling, vol. 9, 1, pp 43-61
- Billio M., Caporin M., Frattarolo L., Pelizzon L., 2021, Networks in risk spillovers: A multivariate GARCH perspective, Econometrics and Statistics
- Billio M., Casarin R., Costola M., Iacopini M., 2021, A Matrix-Variate t Model for Networks, Frontiers in Artificial Intelligence
- Boswijk P., Cavaliere G., Georgiev I., Rahbek A., 2021, Bootstrappingnon-stationary stochastic volatility, Journal of Econometrics, vol. 224, 1, pp. 161-180
- Caporin M., Gupta R., Ravazzolo F., 2021, Contagion between Real Estate and Financial Markets: A Bayesian Quantile-on-Quantile Approach, North American Journal of Economics and Finance, vol. 55
- Gruber P., Tebaldi C., Trojani F., 2021, The price of the Smile and Variance Risk Premia, Management Science, vol. 67, 7
- Guidolin M., Pedio M., 2021, Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?, Annals of Operations Research, vol. 299, 1, pp 1317-1356
- Tebaldi C., 2021, Self-Organized Criticality in Economic Fluctuations: The Age of Maturity, Frontiers in Physics
Last update: 17/04/2024