{"id":196382,"created":"2025-01-19T01:01:04.867373+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00196382","sets":["6504:9795:9803"]},"path":["9803"],"owner":"6748","recid":"196382","title":["NT倍率取引における深層強化学習を用いた投資戦略の構築"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-02-28"},"_buckets":{"deposit":"b132fb79-4fbd-4931-9a54-eedca3180884"},"_deposit":{"id":"196382","pid":{"type":"depid","value":"196382","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"NT倍率取引における深層強化学習を用いた投資戦略の構築","author_link":["469928","469927"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"NT倍率取引における深層強化学習を用いた投資戦略の構築"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ソフトウェア科学・工学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2019-02-28","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京都市大"},{"subitem_text_value":"東京都市大"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/196382/files/IPSJ-Z81-4P-04.pdf","label":"IPSJ-Z81-4P-04.pdf"},"date":[{"dateType":"Available","dateValue":"2019-05-27"}],"format":"application/pdf","filename":"IPSJ-Z81-4P-04.pdf","filesize":[{"value":"505.8 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"6c3bca25-696b-4313-a1f0-3af5e8bb37c5","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"常井, 祥太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"穴田, 一"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，人工知能を用いた投資戦略に関する研究が行われている．しかし，株価や為替には多くの変動要因があるため，人工知能による適切な投資戦略の構築は困難である．そこで本研究では，相関性の強い2つの金融商品に対して，売りと買いの両方を同時に行う取引方法を考える．これらは概ね同じような値動きをし，価格差が拡大しても元に戻りやすい性質があり，この価格差から利益を狙うことができる．この取引では，株価で考えられるような変動要因の大部分が相殺される．このように本研究では，状況を簡略化した上で，深層強化学習によって投資戦略を獲得するモデルを構築した．そして，現実の市場における価格データを用いて有用性を確認した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"350","bibliographic_titles":[{"bibliographic_title":"第81回全国大会講演論文集"}],"bibliographicPageStart":"349","bibliographicIssueDates":{"bibliographicIssueDate":"2019-02-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2019"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"updated":"2025-01-19T22:46:17.175395+00:00","links":{}}