統計学輪講（第17回）

    統計学輪講（第17回）
    日時      2017年10月10日(火)    14時55分～16時35分
    場所      経済学部新棟３階第３教室
    講演者    大森 裕浩 (経済)
    演題      Realized Stochastic Volatility Models with Skewed t Distribution

    概要
    The predictive performance of the realized stochastic volatility model
    which incorporates the asymmetric stochastic volatility model with the 
    realized volatility, is investigated.
    Considering well known characteristics of financial returns, heavy tail 
    and negative skewness,
    the model is extended by employing wider class distributions
    including the generalized hyperbolic skew Student's t-distribution, for 
    financial returns.
    With the Bayesian estimation scheme via Markov chain Monte Carlo method,
    the model enables us to estimate the parameters in the return 
    distribution and in the model jointly.
    It also makes it possible to forecast volatility and return quantiles by 
    sampling from their posterior distributions jointly.
    The model is applied to quantile forecasts of financial returns such as 
    value-at-risk and expected shortfall
    as well as volatility forecasts and those forecasts are evaluated by 
    various tests and performance measures.
    Empirical results with the US and Japanese stock indices, Dow Jones 
    Industrial Average and Nikkei 225,
    show that the extended model improves the volatility and quantile 
    forecasts especially in some volatile periods.
    This is a joint work with Makoto Takahashi and Toshiaki Watanabe.