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.