{"created":"2021-03-01T07:01:58.599745+00:00","id":42129,"links":{},"metadata":{"_buckets":{"deposit":"59ada34c-ae27-452b-b051-cd8606eadb85"},"_deposit":{"id":"42129","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42129"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042129","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2009-09","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"CIRJE-F-669","bibliographic_titles":[{"bibliographic_title":"Discussion paper series. CIRJE-F"}]}]},"item_8_description_13":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Several methods have recently been proposed in the ultra high frequency financial literature to remove the effects of microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex-post daily volatility. Even bias-corrected and consistent (modified) realized volatility (RV) estimates of the integrated volatility can contain residual microstructure noise and other measurement errors. Such noise is called \"realized volatility error\". As such measurement errors ignored, we need to take account of them in estimating and forecasting IV. This paper investigates through Monte Carlo simulations the effects of RV errors on estimating and forecasting IV with RV data. It is found that: (i) neglecting RV errors can lead to serious bias in estimators due to model misspecification; (ii) the effects of RV errors on one-step ahead forecasts are minor when consistent estimators are used and when the number of intraday observations is large; and (iii) even the partially corrected R2 recently proposed in the literature should be fully corrected for evaluating forecasts. This paper proposes a full correction of R2, which can be applied to linear and nonlinear, short and long memory models. An empirical example for S&P 500 data is used to demonstrate that neglecting RV errors can lead to serious bias in estimating the model of integrated volatility, and that the new method proposed here can eliminate the effects of the RV noise. The empirical results also show that the full correction for R2 is necessary for an accurate description of goodness-of-fit.","subitem_description_type":"Abstract"}]},"item_8_description_6":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"本文フィルはリンク先を参照のこと","subitem_description_type":"Other"}]},"item_8_publisher_20":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本経済国際共同センター"}]},"item_8_relation_25":{"attribute_name":"関係URI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://www.cirje.e.u-tokyo.ac.jp/research/dp/2009/2009cf669ab.html","subitem_relation_type_select":"URI"}}]},"item_8_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11450569","subitem_source_identifier_type":"NCID"}]},"item_8_subject_15":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"335","subitem_subject_scheme":"NDC"}]},"item_8_text_21":{"attribute_name":"出版者別名","attribute_value_mlt":[{"subitem_text_value":"Center for International Research on the Japanese Economy"}]},"item_8_text_4":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Faculty of Economics Soka University, Japan"},{"subitem_text_value":"Econometric Institute Erasmus School of Economics Erasmus University Rotterdam"},{"subitem_text_value":"Tinbergen Institute The Netherlands"},{"subitem_text_value":"Center for International Research on the Japanese Economy (CIRJE) Faculty of Economics University of Tokyo"},{"subitem_text_value":"Department of Economics Pontifical Catholic University of Rio de Janeiro"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Asai, Manabu"}],"nameIdentifiers":[{"nameIdentifier":"96962","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"McAleer, Michael"}],"nameIdentifiers":[{"nameIdentifier":"96963","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Medeiros, Marcelo C."}],"nameIdentifiers":[{"nameIdentifier":"96964","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"realized volatility","subitem_subject_scheme":"Other"},{"subitem_subject":"diffusion","subitem_subject_scheme":"Other"},{"subitem_subject":"financial econometrics","subitem_subject_scheme":"Other"},{"subitem_subject":"measurement errors","subitem_subject_scheme":"Other"},{"subitem_subject":"forecasting","subitem_subject_scheme":"Other"},{"subitem_subject":"model evaluation","subitem_subject_scheme":"Other"},{"subitem_subject":"goodness-of-fit","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"technical report","resourceuri":"http://purl.org/coar/resource_type/c_18gh"}]},"item_title":"Modelling and Forecasting Noisy Realized Volatility","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Modelling and Forecasting Noisy Realized Volatility"}]},"item_type_id":"8","owner":"1","path":["7436","7434"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-05-31"},"publish_date":"2013-05-31","publish_status":"0","recid":"42129","relation_version_is_last":true,"title":["Modelling and Forecasting Noisy Realized Volatility"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:17:22.813726+00:00"}