For estimating the realized volatility and covariance by using high frequency data, we introduce the Separating Information Maximum Likelihood (SIML) method when there are possibly micro-market noises. The resulting estimator is simple and it has the representation as a specific quadratic form...

The asymmetrical movement between the downward and upward phases of the sample paths of many financial time series has been commonly noted by economists. Since this feature cannot be described by the Autoregressive Integrated Moving-average (ARIMA) model and the Autoregressive Conditional...

The asymmetrical movements between the downward and upward phases of the sample paths of time series have been sometimes observed. By generalizing the SSAR (simultaneous switching autoregressive) models, we introduce a class of nonlinear time series models having the asymmetrical sample paths in...

The simultaneous switching autoregressive (SSAR) model is a non-linear Markovian time series model, which was originally introduced by Kunitomo and Sato (1996a). This paper gives some conditions for the geometrical ergodicity of the SSAR models and discuss the estimation methods of unknown...

For estimating the integrated volatility by using high frequency data, Kunitomo and Sato (2008, 2011, 2013) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable nite sample properties and asymptotic...

For estimating the integrated volatility and covariance by using high frequency financial data, we propose the Separating Information Maximum Likelihood (SIML) method when there are possibly micro-market noises. The resulting estimator, which is represented as a specific quadratic form of...

For the estimation problem of the realized volatility and hedging coefficient by using high-frequency data with possibly micro-market noise, we use the Separating Information Maximum Likelihood (SIML) method, which was recently developed by Kunitomo and Sato [11–13]. By analyzing the...

For estimating the realized volatility and covariance by using high frequency data, we have introduced the Separating Information Maximum Likelihood (SIML) method when there are possibly micro-market noises by Kunitomo and Sato (2008a, 2008b, 2010a, 2010b). The resulting estimator is simple and...

The Japanese Government reports the annualized estimates of the growth rates of GDP and its main components once in 3 months, and then revises them once in a while. There have been some critical comments on the accuracy of those numbers mainly from economists who want to evaluate the current...

For estimating the realized volatility and covariance by using high frequency data, we have introduced the Separating Information Maximum Likelihood (SIML) method when there are possibly micro-market noises by Kunitomo and Sato (2008a, 2008b, 2010a, 2010b). The resulting estimator is simple and...