統計学輪講（第24回）

    統計学輪講（第24回）
    日時      2017年12月05日(火)    14時55分～15時45分
    場所      経済学部新棟３階第３教室
    講演者   粟屋　直 (経済D1)
    演題      Particle rolling MCMC with forward and backward block sampling 
    with application to stochastic volatility models

    概要   
    The objective is to provide a new simulation-based methodology for 
    rolling estimation in state space model from Bayesian approach.
    This type of estimation requires sampling by simulation-based method 
    from a lot of posteriors if the model does not have so simple form.
    Repetition of sampling from each posterior by Markov Chain Monte Carlo 
    is not realistic from a viewpoint of computational time,
    so in order to address this problem a new sampling algorithm based on 
    sequential Monte Carlo is presented.
    This method is applied to SP 500 data with the realized stochastic 
    volatility with leverage model and how the economic structure which 
    generates the financial data is changed is shown.