{"_buckets": {"deposit": "70af62a7-6dc8-4c00-85ce-25b4fc845e13"}, "_deposit": {"id": "42140", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "42140"}, "status": "published"}, "_oai": {"id": "oai:repository.dl.itc.u-tokyo.ac.jp:00042140"}, "item_8_biblio_info_7": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2009-10", "bibliographicIssueDateType": "Issued"}, "bibliographicVolumeNumber": "CIRJE-F-686", "bibliographic_titles": [{"bibliographic_title": "Discussion paper series. CIRJE-F"}]}]}, "item_8_description_13": {"attribute_name": "\u30d5\u30a9\u30fc\u30de\u30c3\u30c8", "attribute_value_mlt": [{"subitem_description": "application/pdf", "subitem_description_type": "Other"}]}, "item_8_description_5": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S\u0026P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in the paper.", "subitem_description_type": "Abstract"}]}, "item_8_description_6": {"attribute_name": "\u5185\u5bb9\u8a18\u8ff0", "attribute_value_mlt": [{"subitem_description": "\u672c\u6587\u30d5\u30a3\u30eb\u306f\u30ea\u30f3\u30af\u5148\u3092\u53c2\u7167\u306e\u3053\u3068", "subitem_description_type": "Other"}]}, "item_8_publisher_20": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "\u65e5\u672c\u7d4c\u6e08\u56fd\u969b\u5171\u540c\u30bb\u30f3\u30bf\u30fc"}]}, "item_8_relation_25": {"attribute_name": "\u95a2\u4fc2URI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "http://www.cirje.e.u-tokyo.ac.jp/research/dp/2009/2009cf686ab.html", "subitem_relation_type_select": "URI"}}]}, "item_8_source_id_10": {"attribute_name": "\u66f8\u8a8c\u30ec\u30b3\u30fc\u30c9ID", "attribute_value_mlt": [{"subitem_source_identifier": "AA11450569", "subitem_source_identifier_type": "NCID"}]}, "item_8_subject_15": {"attribute_name": "\u65e5\u672c\u5341\u9032\u5206\u985e\u6cd5", "attribute_value_mlt": [{"subitem_subject": "335", "subitem_subject_scheme": "NDC"}]}, "item_8_text_21": {"attribute_name": "\u51fa\u7248\u8005\u5225\u540d", "attribute_value_mlt": [{"subitem_text_value": "Center for International Research on the Japanese Economy"}]}, "item_8_text_34": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"subitem_text_value": "Discussion Paper"}]}, "item_8_text_4": {"attribute_name": "\u8457\u8005\u6240\u5c5e", "attribute_value_mlt": [{"subitem_text_value": "Econometric Institute Erasmus School of Economics Erasmus University Rotterdam"}, {"subitem_text_value": "Tinbergen Institute"}, {"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": "\u30a2\u30af\u30bb\u30b9\u6a29", "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": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "McAleer, Michael"}], "nameIdentifiers": [{"nameIdentifier": "96988", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Medeiros, Marcelo C."}], "nameIdentifiers": [{"nameIdentifier": "96989", "nameIdentifierScheme": "WEKO"}]}]}, "item_keyword": {"attribute_name": "\u30ad\u30fc\u30ef\u30fc\u30c9", "attribute_value_mlt": [{"subitem_subject": "Financial econometrics", "subitem_subject_scheme": "Other"}, {"subitem_subject": "volatility forecasting", "subitem_subject_scheme": "Other"}, {"subitem_subject": "neural networks", "subitem_subject_scheme": "Other"}, {"subitem_subject": "nonlinear models", "subitem_subject_scheme": "Other"}, {"subitem_subject": "realized volatility", "subitem_subject_scheme": "Other"}, {"subitem_subject": "bagging", "subitem_subject_scheme": "Other"}, {"subitem_subject": "JEL Classifications: C22, C53, G12, G17.", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "technical report", "resourceuri": "http://purl.org/coar/resource_type/c_18gh"}]}, "item_title": "Forecasting Realized Volatility with Linear and Nonlinear Models", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "Forecasting Realized Volatility with Linear and Nonlinear Models"}]}, "item_type_id": "8", "owner": "1", "path": ["9/7435/7436", "62/7433/7434"], "permalink_uri": "http://hdl.handle.net/2261/32446", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_value": "2013-05-31"}, "publish_date": "2013-05-31", "publish_status": "0", "recid": "42140", "relation": {}, "relation_version_is_last": true, "title": ["Forecasting Realized Volatility with Linear and Nonlinear Models"], "weko_shared_id": null}