Details about Luca Rossini

Access statistics for papers by Luca Rossini.

Last updated 2025-01-07. Update your information in the RePEc Author Service.

Short-id: pro1002

Working Papers

2024

1. A Quantile Nelson-Siegel model
   Papers, arXiv.org
2. Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications
   Papers, arXiv.org View citations (2)
3. Comparing predictive ability in presence of instability over a very short time
   Papers, arXiv.org
4. Density Forecasting for Electricity Prices under Tail Heterogeneity with the t-Riesz Distribution
   Tinbergen Institute Discussion Papers, Tinbergen Institute
5. What drives the European carbon market? Macroeconomic factors and forecasts
   Working Papers, Fondazione Eni Enrico Mattei
   Also in FEEM Working Papers, Fondazione Eni Enrico Mattei (FEEM) (2024)
   Papers, arXiv.org (2024)

2023

6. Is the Price Cap for Gas Useful? Evidence from European Countries
   Working Papers, Fondazione Eni Enrico Mattei
   Also in FEEM Working Papers, Fondazione Eni Enrico Mattei (FEEM) (2023)
7. Money Growth and Inflation: A Quantile Sensitivity Approach
   Papers, arXiv.org
8. Sparse time-varying parameter VECMs with an application to modeling electricity prices
   Papers, arXiv.org
   See also Journal Article Sparse time-varying parameter VECMs with an application to modeling electricity prices, International Journal of Forecasting, Elsevier (2025) (2025)
9. Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution
   Tinbergen Institute Discussion Papers, Tinbergen Institute View citations (2)

2022

10. A Multivariate Dependence Analysis for Electricity Prices, Demand and Renewable Energy Sources
    Papers, arXiv.org View citations (7)
11. Are low frequency macroeconomic variables important for high frequency electricity prices?
    Papers, arXiv.org
    See also Journal Article Are low frequency macroeconomic variables important for high frequency electricity prices?, Economic Modelling, Elsevier (2023) View citations (7) (2023)
12. Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP
    Papers, arXiv.org View citations (3)
    See also Journal Article Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP, Journal of Economic Dynamics and Control, Elsevier (2023) View citations (3) (2023)
13. The Role of the Monthly ENSO in Forecasting the Daily Baltic Dry Index
    Working Papers, University of Pretoria, Department of Economics View citations (1)

2021

14. Inference in Bayesian Additive Vector Autoregressive Tree Models
    Papers, arXiv.org View citations (2)

2020

15. Dynamic Bayesian forecasting of English Premier League match results with the Skellam distribution
    BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen
16. Large Time-Varying Volatility Models for Electricity Prices
    Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School View citations (4)
17. Proper scoring rules for evaluating asymmetry in density forecasting
    Papers, arXiv.org
    Also in Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School (2020)

2019

18. Bayesian nonparametric graphical models for time-varying parameters VAR
    Papers, arXiv.org
19. Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration
    Papers, arXiv.org View citations (5)
    Also in Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School (2018) View citations (4)
    See also Journal Article Comparing the forecasting performances of linear models for electricity prices with high RES penetration, International Journal of Forecasting, Elsevier (2020) View citations (34) (2020)
20. Comparing the forecasting of cryptocurrencies by Bayesian time-varying volatility models
    Papers, arXiv.org View citations (12)
    See also Journal Article Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models, JRFM, MDPI (2019) View citations (11) (2019)
21. Forecasting daily electricity prices with monthly macroeconomic variables
    Working Paper Series, European Central Bank View citations (3)

2018

22. Bayesian nonparametric sparse VAR models
    Papers, arXiv.org View citations (1)
    See also Journal Article Bayesian nonparametric sparse VAR models, Journal of Econometrics, Elsevier (2019) View citations (26) (2019)

2016

23. Bayesian Nonparametric Conditional Copula Estimation of Twin Data
    Working Papers, Department of Economics, University of Venice "Ca' Foscari" View citations (1)
    See also Journal Article Bayesian non‐parametric conditional copula estimation of twin data, Journal of the Royal Statistical Society Series C, Royal Statistical Society (2018) View citations (5) (2018)
24. Bayesian nonparametric sparse seemingly unrelated regression model (SUR)
    Working Papers, Department of Economics, University of Venice "Ca' Foscari" View citations (1)

Journal Articles

2025

1. Sparse time-varying parameter VECMs with an application to modeling electricity prices
   International Journal of Forecasting, 2025, 41, (1), 361-376
   See also Working Paper Sparse time-varying parameter VECMs with an application to modeling electricity prices, Papers (2023) (2023)

2023

2. Are low frequency macroeconomic variables important for high frequency electricity prices?
   Economic Modelling, 2023, 120, (C) View citations (7)
   See also Working Paper Are low frequency macroeconomic variables important for high frequency electricity prices?, Papers (2022) (2022)
3. Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP
   Journal of Economic Dynamics and Control, 2023, 157, (C) View citations (3)
   See also Working Paper Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP, Papers (2022) View citations (3) (2022)
4. Large Time‐Varying Volatility Models for Hourly Electricity Prices
   Oxford Bulletin of Economics and Statistics, 2023, 85, (3), 545-573
5. Proper Scoring Rules for Evaluating Density Forecasts with Asymmetric Loss Functions
   Journal of Business & Economic Statistics, 2023, 41, (2), 482-496 View citations (2)

2020

6. Bayesian analysis of immigration in Europe with generalized logistic regression
   Journal of Applied Statistics, 2020, 47, (3), 424-438 View citations (1)
7. Comparing the forecasting performances of linear models for electricity prices with high RES penetration
   International Journal of Forecasting, 2020, 36, (3), 974-986 View citations (34)
   See also Working Paper Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration, Papers (2019) View citations (5) (2019)
8. Loss-based approach to two-piece location-scale distributions with applications to dependent data
   Statistical Methods & Applications, 2020, 29, (2), 309-333

2019

9. Bayesian nonparametric sparse VAR models
   Journal of Econometrics, 2019, 212, (1), 97-115 View citations (26)
   See also Working Paper Bayesian nonparametric sparse VAR models, Papers (2018) View citations (1) (2018)
10. Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models
    JRFM, 2019, 12, (3), 1-18 View citations (11)
    See also Working Paper Comparing the forecasting of cryptocurrencies by Bayesian time-varying volatility models, Papers (2019) View citations (12) (2019)
11. On a flexible construction of a negative binomial model
    Statistics & Probability Letters, 2019, 152, (C), 1-8

2018

12. Bayesian non‐parametric conditional copula estimation of twin data
    Journal of the Royal Statistical Society Series C, 2018, 67, (3), 523-548 View citations (5)
    See also Working Paper Bayesian Nonparametric Conditional Copula Estimation of Twin Data, Working Papers (2016) View citations (1) (2016)
13. Objective bayesian analysis of the Yule–Simon distribution with applications
    Computational Statistics, 2018, 33, (1), 99-126