Publications
Peer-reviewed journals
Costola, M., Iacopini, M. and Wichers, C. (2024), “Bayesian SAR model with stochastic volatility and multiple time-varying weights”, Journal of Financial Econometrics, (forthcoming)
Bonaccolto, G., Caporin, M. and Iacopini, M. (2024), “Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Comment”, Energy Economics, 132:107469
Iacopini, M., Poon, A., Rossini, L. and Zhu, D. (2023), “Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP”, Journal of Economic Dynamics and Control, 157:104757
Costola, M. and Iacopini (2023), “Measuring sovereign bond fragmentation in the Eurozone”, Finance Research Letters, 51:103354
Billio, M., Casarin, R. and Iacopini, M., (2024), “Bayesian Markov switching tensor regression for time-varying networks”, Journal of the American Statistical Association, 119(545), 109–121
Billio, M., Casarin, R., Iacopini, M. and Kaufmann, S. (2023), “Bayesian dynamic tensor regression”, Journal of Business and Economic Statistics, 41(2):429–439
Iacopini, M., Ravazzolo, F. and Rossini, L. (2023), “Proper scoring rules for evaluating density forecasts with asymmetric loss functions”, Journal of Business and Economic Statistics, 41(2):482–496
Billio, M., Casarin, R., Costola, M. and Iacopini, M. (2021), “COVID-19 spreading in financial networks: A semiparametric matrix regression model”, Econometrics and Statistics, 29, 113–131
Costola, M., Iacopini, M. and Santagiustina, C.R.M.A. (2021), “On the “mementum” of meme stocks”, Economics Letters, 207, 110021
Billio, M., Casarin, R., Costola, M. and Iacopini, M. (2021), “A matrix-variate t model for networks”, Frontiers in Artificial Intelligence 4, 49
Iacopini, M. and Santagiustina, C.R.M.A. (2021), “Filtering the intensity of public concern from social media count data with jumps”, Journal of the Royal Statistical Society: Series A, 184:1283–1302
Costola, M., Iacopini, M. and Santagiustina, C.R.M.A. (2020), “Google search volumes and the financial markets during the COVID-19 outbreak”, Finance Research Letters, 42:101884
Casarin, R., Iacopini, M., Molina, G., ter Horst, E., Espinasa, R., Sucre, C. and Rigobon, R. (2020), “Multilayer Network Analysis of Oil Linkages”, The Econometrics Journal, 23(2):269–29
Discussions
Iacopini, M., Ravazzolo, R. and Rossini, L. (2020) - “Discussion on: On a Class of Objective Priors from Scoring Rules”, by Fabrizio Leisen, Cristiano Villa, and Stephen G. Walker”. Bayesian Analysis, 15(4):1345–1423.
Tonellato, S. and Iacopini, M. (2018), “A discussion on: Using stacking to average Bayesian predictive distributions by Y. Yao, A. Vehtari, D. Simpson and A. Gelman”, Bayesian Analysis, 13(3): 917–1007.
Casarin, R., Iacopini, M. and Rossini, L. (2017) - “A discussion on: Sparse graphs using exchangeable random measures by F. Caron and E.B. Fox”. Journal of the Royal Statistical Society, Series B, 79(5):1295–1366.
Book Chapters
Billio, M., Casarin, R., Costola, M. and Iacopini, M. (2022), “Matrix-variate Smooth Transition Models for Temporal Networks”, in Arashi, M., Bekker, A., Che, D., and Ferreira, J., Innovations in Multivariate Statistical Modeling: Navigating Theoretical and Multidisciplinary Domains, pages 137–167, Springer Emerging Topics in Statistics and Biostatistics
Billio, M., Casarin, R. and Iacopini, M. (2018), “Bayesian tensor regression models”, In Mathematical and Statistical Methods for Actuarial Sciences and Finance. MAF 2018. Eds. Corazza, M., Durbán, M., Grané, A., Perna, C., Sibillo, M., Springer, 149–153.
Billio, M., Casarin, R. and Iacopini, M. (2018), “Bayesian tensor binary regression”, In Mathematical and Statistical Methods for Actuarial Sciences and Finance. MAF 2018. Eds. Corazza, M., Durbán, M., Grané, A., Perna, C., Sibillo, M., Springer, 143–147.
Billio, M., Casarin, R. and Iacopini, M. (2017), “Bayesian tensor regression models”, In Proceedings of the Conference of the Italian Statistical Society. Statistics and Data Science: new challenges, new generations. Eds. Alessandra Petrucci and Rosanna Verde, Firenze University Press, 179–186.
Other publications
- Iacopini, M., (2016), “Basics of optimization theory with applications in MATLAB and R”, Quaderni di didattica, Department of Economics, Ca’ Foscari University of Venice