• Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance 

      Casarin, Roberto; Grassi, Stefano; Ravazzolo, Francesco; van Dijk, Herman K. (Working Papers;12/2015, Working paper, 2015)
      A Bayesian nonparametric predictive model is introduced to construct time-varying weighted combinations of a large set of predictive densities. A clustering mechanism allocates these densities into a smaller number of ...
    • Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies 

      Basturk, Nalan; Borowska, Agnieszka; Grassi, Stefano; Hoogerheide, Lennart; van Dijk, Herman K. (Working Paper;10/2018, Working paper, 2018)
      A dynamic asset-allocation model is specified in probabilistic terms as a combination of return distributions resulting from multiple pairs of dynamic models and portfolio strategies based on momentum patterns in US industry ...
    • Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance 

      Casarin, Roberto; Grassi, Stefano; Ravazzolo, Francesco; van Dijk, Herman K. (Working Paper;7/2019, Working paper, 2019)
      A flexible forecast density combination approach is introduced that can deal with large data sets. It extends the mixture of experts approach by allowing for model set incompleteness and dynamic learning of combination ...
    • Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo MATLAB Toolbox 

      Casarin, Roberto; Grassi, Stefano; Ravazzolo, Francesco; van Dijk, Herman K. (Working Papers;11/2014, Working paper, 2014)
      This paper presents the MATLAB package DeCo (density combination) which is based on the paper by Billio, Casarin, Ravazzolo, and van Dijk (2013) where a constructive Bayesian approach is presented for combining predictive ...
    • The R Package Mitisem: Efficient and Robust Simulation Procedures for Bayesian Inference 

      Basturk, Nalan; Grassi, Stefano; Hoogerheide, Lennart; Opschoor, Anne; van Dijk, Herman K. (Working Papers;10/2017, Working paper, 2017)
      This paper presents the R package MitISEM (mixture of t by importance sampling weighted expectation maximization) which provides an automatic and flexible two-stage method to approximate a non-elliptical target density ...