9 citations · 20 across the 11 of their papers we have counts for
6 papers · 1 filter
Model selection confidence sets for time series models with applications to electricity load data
Piersilvio De Bortoli, Davide Ferrari, Francesco Ravazzolo +1
This paper studies the Model Selection Confidence Set (MSCS) methodology for univariate time series models involving autoregressive and moving average components, and applies it to…
Forecasting Oil Consumption: The Statistical Review of World Energy Meets Machine Learning
Jan Ditzen, Erkal Ersoy, Haoyang Li +1
This paper studies whether a small set of dominant countries can account for most of the dynamics of regional oil demand and improve forecasting performance. We focus on dominant d…
Modeling European Electricity Market Integration during turbulent times
Francesco Ravazzolo, Luca Rossini, Andrea Viselli
This paper introduces a novel Bayesian reverse unrestricted mixed-frequency model applied to a panel of nine European electricity markets. Our model analyzes the impact of daily fo…
Dominant Drivers of National Inflation
Jan Ditzen, Francesco Ravazzolo
For western economies a long-forgotten phenomenon is on the horizon: rising inflation rates. We propose a novel approach christened D2ML to identify drivers of national inflation.…
Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications
Matteo Iacopini, Francesco Ravazzolo, Luca Rossini
This article proposes a novel Bayesian multivariate quantile regression to forecast the tail behavior of energy commodities, where the homoskedasticity assumption is relaxed to all…
Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration
Angelica Gianfreda, Francesco Ravazzolo, Luca Rossini
This paper compares alternative univariate versus multivariate models, frequentist versus Bayesian autoregressive and vector autoregressive specifications, for hourly day-ahead ele…