Browsing BI Open by Author "Ravazzolo, Francesco"

Now showing items 21-25 of 25

    • Predicting the Volatility of Cryptocurrency Time–Series 

      Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco (CAMP Working Paper Series;3, Working paper, 2018-02)
      Cryptocurrencies have recently gained a lot of interest from investors, central banks and governments worldwide. The lack of any form of political regu- lation and their market far from being “efficient”, require new forms ...

    • Proper scoring rules for evaluating asymmetry in density forecasting 

      Iacopini, Matteo; Ravazzolo, Francesco; Rossini, Luca (CAMP Working Paper Series;06/2020, Working paper, 2020-09-01)
      This paper proposes a novel asymmetric continuous probabilistic score (ACPS) for evaluating and comparing density forecasts. It extends the proposed score and defines a weighted version, which emphasizes regions of interest, ...

    • The bank-sovereign nexus: Evidence from a non-bailout episode 

      Caporin, Massimiliano; Natvik, Gisle James; Ravazzolo, Francesco; Santucci de Magistris, Paolo (Journal article; Peer reviewed, 2019)
      We explore the interplay between sovereign and bank credit risk in a setting where Danish authorities first let two Danish banks default and then left the country’s largest bank, Danske Bank, to recapitalize privately. We ...

    • Time-varying combinations of predictive densities using nonlinear filtering 

      Billio, Monica; Casarin, Roberto; Ravazzolo, Francesco; Dijk, Herman K. van (Journal article; Peer reviewed, 2013)
      We propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several speci cations of multivariate time-varying ...

    • Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts 

      Krüger, Fabian; Clark, Todd E.; Ravazzolo, Francesco (CAMP Working Paper Series;8/2015, Working paper, 2015)
      This paper shows entropic tilting to be a flexible and powerful tool for combining mediumterm forecasts from BVARs with short-term forecasts from other sources (nowcasts from either surveys or other models). Tilting ...