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タイトル: Robustness of the Separating Information Maximum Likelihood Estimation of Realized Volatility with Micro-Market Noise
著者: Kunitomo, Naoto
Sato, Seisho
著者(別言語): 国友, 直人
佐藤, 整尚
キーワード: Realized Volatility with Micro-Market Noise
High-Frequency Data
Separating Information Maximum Likelihood (SIML)
Endogenous Noise
Autocorrelated Noise
発行日: 2010年4月
出版者: 日本経済国際共同センター
抄録: For estimating the realized volatility and covariance by using high frequency data, Kunitomo and Sato (2008a,b) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable asymptotic properties; it is consistent and it has the asymptotic normality (or the stable convergence in the general case) when the sample size is large under general conditions including non-Gaussian processes and volatility models. We also show that the SIML estimator has the asymptotic robustness in the sense that it is consistent and it has the asymptotic normality when there are autocorrelations in the market noise terms and there are endogenous correlations between the signal and noise terms.
内容記述: Forthcoming in Mathematcs and Computers in Simulation (2010), North-Holland.
URI: http://hdl.handle.net/2261/35801
その他の識別子: CIRJE-F-733
出現カテゴリ:061 ディスカッションペーパー
Discussion Paper F series (in English)


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