HYBRID MULTI-STEP ESTIMATION OF THE VOLATILITY FOR STOCHASTIC REGRESSION MODELS - Collections

＜journal article＞
HYBRID MULTI-STEP ESTIMATION OF THE VOLATILITY FOR STOCHASTIC REGRESSION MODELS

Creator	Author PID 00569767 Creator Name Kamatani, Kengo 鎌谷, 研吾カマタニ, ケンゴ Affiliation Affiliation Name Graduate School of Engineering Science and MMDS, Osaka University 大阪大学基礎工学研究科
	Creator Name Nogita, Akihiro 野北, 明寛ノギタ, アキヒロ Affiliation Affiliation Name MMDS, Osaka University 大阪大学数理・データ科学教育研究センター
	Author PID 70280526 Creator Name Uchida, Masayuki 内田, 雅之ウチダ, マサユキ Affiliation Affiliation Name Graduate School of Engineering Science and MMDS, Osaka University 大阪大学基礎工学研究科
Language	English
Publisher	Research Association of Statistical Sciences
Publisher	統計科学研究会
Date	2016-12
Source Title	Bulletin of informatics and cybernetics
Vol	48
First Page	19
Last Page	35
Publication Type	Version of Record
Access Rights	open access
Crossref DOI	https://doi.org/10.5109/2203025
Abstract	We deal with an estimation problem of a volatility parameter for stochastic regression models based on high frequency data. Hybrid multi-step estimators are proposed and their asymptotic properties, i...ncluding convergence of moments, are obtained.show more

File	FileType	Size	Views	Description
2-Kamatani	pdf	354 KB	347

PISSN	0286-522X
EISSN	2435-743X
NCID	AA10634475
Record ID	2203025
Subject Terms	Asymptotic mixed normality
	Bayes type estimator
	convergence of moments
	diffusion process
	discrete time observations
	maximum likelihood type estimator
Funding Information	Funder Name 日本学術振興会 Japan Society for the Promotion of Science Award Number 24740062 Award Title 隠れマルコフモデルに対する統計計算手法の漸近的解析 Asymptotic analysis of statistical computation methods for hidden Markov models
Created Date	2019.02.25
Modified Date	2023.11.14