| Bayesian nonparametric sparse VAR models M Billio, R Casarin, L Rossini Journal of Econometrics 212 (1), 97-115, 2019 | 81 | 2019 |
| Comparing the forecasting performances of linear models for electricity prices with high RES penetration A Gianfreda, F Ravazzolo, L Rossini International Journal of Forecasting 36 (3), 974-986, 2020 | 55 | 2020 |
| Comparing the forecasting of cryptocurrencies by Bayesian time-varying volatility models R Bohte, L Rossini Journal of Risk and Financial Management 12 (3), 150, 2019 | 36 | 2019 |
| Bayesian non-parametric conditional copula estimation of twin data LD Valle, F Leisen, L Rossini Journal of the Royal Statistical Society Series C: Applied Statistics 67 (3 …, 2018 | 34 | 2018 |
| Inference in Bayesian additive vector autoregressive tree models F Huber, L Rossini The Annals of Applied Statistics 16 (1), 104-123, 2022 | 31 | 2022 |
| Hierarchical species sampling models F Bassetti, R Casarin, L Rossini Bayesian Analysis 15 (3), 809-838, 2020 | 27 | 2020 |
| Are low frequency macroeconomic variables important for high frequency electricity prices? C Foroni, F Ravazzolo, L Rossini Economic Modelling 120, 106160, 2023 | 18* | 2023 |
| A multivariate dependence analysis for electricity prices, demand and renewable energy sources F Durante, A Gianfreda, F Ravazzolo, L Rossini Information Sciences 590, 74-89, 2022 | 18 | 2022 |
| Stablecoins and cryptocurrency returns: Evidence from large bayesian vars D Bianchi, M Iacopini, L Rossini Stablecoins and Cryptocurrency Returns: Evidence From Large Bayesian VARs …, 2020 | 17* | 2020 |
| A note on the posterior inference for the Yule–Simon distribution F Leisen, L Rossini, C Villa Journal of statistical computation and simulation 87 (6), 1179-1188, 2017 | 14 | 2017 |
| Proper scoring rules for evaluating density forecasts with asymmetric loss functions M Iacopini, F Ravazzolo, L Rossini Journal of Business & Economic Statistics 41 (2), 482-496, 2023 | 10 | 2023 |
| Bayesian analysis of immigration in Europe with generalized logistic regression L Dalla Valle, F Leisen, L Rossini, W Zhu Journal of Applied Statistics 47 (3), 424-438, 2020 | 8 | 2020 |
| Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP M Iacopini, A Poon, L Rossini, D Zhu Journal of Economic Dynamics and Control 157, 104757, 2023 | 6 | 2023 |
| Objective bayesian analysis of the Yule–Simon distribution with applications F Leisen, L Rossini, C Villa Computational Statistics 33, 99-126, 2018 | 6 | 2018 |
| Tail Heterogeneity for Dynamic Covariance-Matrix-Valued Random Variables: the F-Riesz Distribution A Lucas, A Opschoor, L Rossini Tinbergen Institute Discussion Paper 2021-010/III, 2021 | 5 | 2021 |
| Loss-based approach to two-piece location-scale distributions with applications to dependent data F Leisen, L Rossini, C Villa Statistical Methods & Applications 29 (2), 309-333, 2020 | 5 | 2020 |
| On a flexible construction of a negative binomial model F Leisen, RH Mena, F Palma, L Rossini Statistics & Probability Letters 152, 1-8, 2019 | 5 | 2019 |
| Large time-varying volatility models for electricity prices A Gianfreda, F Ravazzolo, L Rossini BI Norwegian Business School, 2020 | 4 | 2020 |
| Bayesian nonparametric graphical models for time-varying parameters VAR M Iacopini, L Rossini arXiv preprint arXiv:1906.02140, 2019 | 4 | 2019 |
| Bayesian multivariate quantile regression with alternative time-varying volatility specifications M Iacopini, F Ravazzolo, L Rossini arXiv preprint arXiv:2211.16121, 2022 | 3 | 2022 |
Francesco RavazzoloBI Norwegian Business School and Free University of Bozen-Bolzano在 unibz.it 的电子邮件经过验证
