Blar i Scientific articles på forfatter "Casarin, Roberto"

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    • A flexible predictive density combination for large financial data sets in regular and crisis periods 

      Casarin, Roberto; Grassi, Stefano; Ravazzolo, Francesco; van Dijk, Herman K. (Peer reviewed; Journal article, 2023)
      A flexible predictive density combination is introduced for large financial data sets which allows for model set incompleteness. Dimension reduction procedures that include learning allocate the large sets of predictive ...

    • Markov switching panel with endogenous synchronization effects 

      Agudze, Komla M.; Billio, Monica; Casarin, Roberto; Ravazzolo, Francesco (Journal article; Peer reviewed, 2021)
      This paper introduces a new dynamic panel model with multi-layer network effects. Series-specific latent Markov chain processes drive the dynamics of the observable processes, and several types of interaction effects among ...

    • Nowcasting industrial production using linear and non-linear models of electricity demand 

      Galdi, Giulio; Casarin, Roberto; Ferrari, Davide; Fezzi, Carlo; Ravazzolo, Francesco (Peer reviewed; Journal article, 2023)
      This article proposes different modelling approaches which exploit electricity market data to nowcast industrial production. Our models include linear, mixed-data sampling (MIDAS), Markov-Switching (MS) and MS-MIDAS ...

    • A scoring rule for factor and autoregressive models under misspecification 

      Ravazzolo, Francesco; Casarin, Roberto; Corradin, Fausto; Sartore, Domenico (Journal article; Peer reviewed, 2020)
      Factor models (FM) are now widely used for forecasting with large set of time series. Another class of models, which can be easily estimated and used in a large dimensional setting, is multivariate autoregressive models ...

    • 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 ...