• Comparing the forecasting performances of linear models for electricity prices with high RES penetration 

      Gianfreda, Angelica; Ravazzolo, Francesco; Rossini, Luca (Journal article; Peer reviewed, 2020)
      We compare alternative univariate versus multivariate models and frequentist versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, both with and without renewable ...
    • Forecasting cryptocurrencies under model and parameter instability 

      Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco (Journal article; Peer reviewed, 2019)
      This paper studies the predictability of cryptocurrency time series. We compare several alternative univariate and multivariate models for point and density forecasting of four of the most capitalized series: Bitcoin, ...
    • Forecasting electricity prices with expert, linear, and nonlinear models 

      Billé, Anna Gloria; Gianfreda, Angelica; Del Grosso, Filippo; Ravazzolo, Francesco (Peer reviewed; Journal article, 2022)
      This paper compares several models for forecasting regional hourly day-ahead electricity prices, while accounting for fundamental drivers. Forecasts of demand, in-feed from renewable energy sources, fossil fuel prices, and ...
    • Nowcasting GDP with a pool of factor models and a fast estimation algorithm 

      Eraslan, Sercan; Schröder, Maximilian (Peer reviewed; Journal article, 2022)
      We propose a novel mixed-frequency dynamic factor model with time-varying parameters and stochastic volatility for macroeconomic nowcasting and develop a fast estimation algorithm. This enables us to generate forecast ...