2018年11月1日
Parametric inference for nonsynchronously observed diffusion processes in the presence of market microstructure noise
Bernoulli
- 巻
- 24
- 号
- 4B
- 開始ページ
- 3318
- 終了ページ
- 3383
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.3150/17-BEJ962
- 出版者・発行元
- International Statistical Institute
We study parametric inference for diffusion processes when observations occur nonsynchronously and are contaminated by market microstructure noise. We construct a quasi-likelihood function and study asymptotic mixed normality of maximum-likelihood- and Bayes-type estimators based on it. We also prove the local asymptotic normality of the model and asymptotic efficiency of our estimator when the diffusion coefficients are deterministic and noise follows a normal distribution. We conjecture that our estimator is asymptotically efficient even when the latent process is a general diffusion process. An estimator for the quadratic covariation of the latent process is also constructed. Some numerical examples show that this estimator performs better compared to existing estimators of the quadratic covariation.
- リンク情報
- ID情報
-
- DOI : 10.3150/17-BEJ962
- ISSN : 1350-7265
- SCOPUS ID : 85046750921