This article introduces a new efficient simulation smoother and disturbance smoother for asymmetric stochastic volatility models where there exists a correlation between today`s return and tomorrow`s volatility. The state vector is divided into several blocks where each block consists of many...

In the time series analysis of asset prices, the stochastic volatility models have recently attracted attentions of many researchers since it clearly describes time-varying variance of asset returns. However, it is difficult to evaluate the likelihood and obtain the maximum likelihood estimators...

This article introduces a new efficient simulation smoother and disturbance smoother for asymmetric stochastic volatility models where there exists a correlation between today's return and tomorrow's volatility. The state vector is divided into several blocks where each block consists of many...

A new efficient simulation smoother and disturbance smoother are introduced for asymmetric stochastic volatility models where there exists a correlation between today's return and tomorrow's volatility. The state vector is divided into several blocks where each block consists of many state...

This article introduces a new efficient simulation smoother and disturbance smoother for general state-space models where there exists a correlation between error terms of the measurement and state equations. The state vector is divided into several blocks where each block consists of many state...

In a Bayesian analysis of a model with Student's-t disturbances developed by Geweke (J. Appl. Econom. 8 (1993) S19), and Fernández and Steel (J. Amer. Statist. Assoc. 93 (1998) 359), the degree-of-freedom of Student's-t disturbances, if unknown, must be sampled from its conditional...

Watanabe estimated the dynamic bivariate mixture models introduced by Tauchen and Pitts and modified by Andersen using a Bayesian method via Markov chain Monte Carlo techniques. Based on a maximum likelihood method via efficient importance sampling, Liesenfeld and Richard obtained estimates that...

This article examines the pattern of autocorrelation of daily stock index returns in the Tokyo Stock Exchange (TSE) by estimating the two variants of the EGARCH model by Nelson (1991). We confirm the findings by Sentana and Wadhwani (1992) and Koutmos (1997) that stock returns exhibit positive...

In a linear Gaussian state-space time series analysis, a disturbance smoother and a simula-tion smoother are widely used procedures for smoothing and sampling state or disturbance vectors given observations. Several smoothing procedures are also proposed for a non-Gaussian observation process....