{"created":"2025-01-19T01:29:23.283465+00:00","updated":"2025-01-19T11:21:26.867280+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229931","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229931","title":["機械学習を用いた為替取引における適した時間粒度の分析"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"adb78df4-eefe-4052-a32e-32d784f2a3ee"},"_deposit":{"id":"229931","pid":{"type":"depid","value":"229931","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習を用いた為替取引における適した時間粒度の分析","author_link":["618555","618557","618556"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いた為替取引における適した時間粒度の分析"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","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":"神奈川大"},{"subitem_text_value":"神奈川大"},{"subitem_text_value":"神奈川大"}]},"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/229931/files/IPSJ-Z85-7Q-01.pdf","label":"IPSJ-Z85-7Q-01.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-7Q-01.pdf","filesize":[{"value":"219.9 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"343c694e-003d-47df-9e58-4f0d408ee0c8","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"加藤, 大樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"李, 嘉誠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"能登, 正人"}],"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":"株や為替といった市場価格予測に関する技術は日々進歩しており，機械学習を用いた研究も盛んに行われている．学習に使用するための様々な指標は，投資家が利用するテクニカル指標やニュース記事などを用いたものまで多数存在する．多くの研究では1日毎のデータを使用しているが，適した時間粒度(どれほどの期間の値動きをまとめるか)を利用することで，より大きい利益を得られる可能性がある．しかしながら，データの粒度と予測結果との関係性に着目した研究は非常に少ない．本研究では，機械学習ベースのモデルを用いることにより価格を予測し，為替取引シミュレーション実験を行った．実験の結果，利益を得やすい粒度が確認できた．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"268","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"267","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229931,"links":{}}