{"created":"2023-07-27T07:50:59.713288+00:00","id":26244,"links":{},"metadata":{"_buckets":{"deposit":"7e147ffa-d567-462a-a166-4dc1acc14762"},"_deposit":{"created_by":20,"id":"26244","owners":[20],"pid":{"revision_id":0,"type":"depid","value":"26244"},"status":"published"},"_oai":{"id":"oai:doshisha.repo.nii.ac.jp:00026244","sets":["4251:8138:8139:8140:8148","8:3372:3847:3855"]},"author_link":["24270","16397"],"item_1693811493084":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_1694490770713":{"attribute_name":"権利者情報","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"DA18202107","nameIdentifierScheme":"AID"}],"rightHolderNames":[{"rightHolderLanguage":"ja","rightHolderName":"同志社大学ハリス理化学研究所"},{"rightHolderLanguage":"en","rightHolderName":"Harris Science Research Institute of Doshisha University"}]}]},"item_1_biblio_info_14":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-07-31","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"106","bibliographicPageStart":"99","bibliographicVolumeNumber":"59","bibliographic_titles":[{"bibliographic_title":"同志社大学ハリス理化学研究報告","bibliographic_titleLang":"ja"},{"bibliographic_title":"The Harris science review of Doshisha University","bibliographic_titleLang":"en"}]}]},"item_1_description_12":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"近年，情報技術の発展に伴い，深層学習の活用が注目されている．最近では，画像やテキストなど様々なデータに対して深層学習を用いることの有効性が示されている．そのため，金融市場の分析や予測において，深層学習を応用する動きが活発になっている．また，近年，インターネットの普及により株式取引の手数料の低コスト化が実現されるとともに，個人投資家の数が激増している．ところで，株式予測には大きく分けてファンダメンタル分析とテクニカル分析の2つが存在する．テクニカル分析では，株価チャートのパターンから売買タイミングを判断する．そして，テクニカル分析により収益を得ている個人投資家は少なくない．しかし，テクニカル分析は個人の能力に依存し，主観的である．そこで，本研究では畳み込みニューラルネットワーク(CNN)により株価変動の予測を試みた．そして，本研究の目的はCNNにより株価変動を予測する手法の開発とする．","subitem_description_language":"ja","subitem_description_type":"Abstract"},{"subitem_description":"Today，the use of the deep learning is being focused with the development of the information technology．Recently it is shown that using deep learning for several data is effective，especially pictures or text. Therefore，many researchers have been using deep learning to analyze or predict the financial market．In addition，the spread of Internet enable people to get stocks in lower brokerage．Then the number of the private investors is increasing nowadays．By the way，there are two ways to analyze stock price． They are the fundamental analysis and the technical analysis．The technical analysts use the patterns of stock price change to know whether they invest or not．And not a few people make profits by technical analysis．But this method depends on personal skills so that it is subjective．Thus，we tried to predict the fluctuation of stock price by Convolutional Neural Network (CNN)．Then the goal of our research is to develop the method of the prediction about the fluctuation of stock price by CNN.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_1_description_25":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_1_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.14988/pa.2018.0000000163","subitem_identifier_reg_type":"JaLC"}]},"item_1_publisher_15":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"同志社大学ハリス理化学研究所","subitem_publisher_language":"ja"}]},"item_1_publisher_16":{"attribute_name":"出版者（英）","attribute_value_mlt":[{"subitem_publisher":"Harris Science Research Institute of Doshisha University","subitem_publisher_language":"en"}]},"item_1_relation_24":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_language":"ja","subitem_relation_name_text":"掲載刊行物所蔵情報へのリンク ／ Link to Contents"}],"subitem_relation_type":"isFormatOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doors.doshisha.ac.jp/opac/opac_link/bibid/SB12902196/?lang=0","subitem_relation_type_select":"URI"}}]},"item_1_select_10":{"attribute_name":"所属機関識別子種別","attribute_value_mlt":[{"subitem_select_item":"kakenhi"}]},"item_1_select_11":{"attribute_name":"所属機関識別子","attribute_value_mlt":[{"subitem_select_item":"34310"}]},"item_1_source_id_17":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"21895937","subitem_source_identifier_type":"PISSN"}]},"item_1_source_id_19":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12716107","subitem_source_identifier_type":"NCID"}]},"item_1_subject_27":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"338.155","subitem_subject_scheme":"NDC"}]},"item_1_text_8":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"白方, 健司 / Department of Mathematical Sciences, Doshisha University"},{"subitem_text_language":"ja","subitem_text_value":"津田, 博史 / 同志社大学理工学部数理システム学科教授"}]},"item_1_text_9":{"attribute_name":"著者所属（英）","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Doshisha University"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"白方, 健司","creatorNameLang":"ja"},{"creatorName":"シラカタ, ケンジ","creatorNameLang":"ja-Kana"},{"creatorName":"Shirakata, Kenji","creatorNameLang":"en"}],"nameIdentifiers":[{},{}]},{"creatorNames":[{"creatorName":"津田, 博史","creatorNameLang":"ja"},{"creatorName":"ツダ, ヒロシ","creatorNameLang":"ja-Kana"},{"creatorName":"Tsuda, Hiroshi","creatorNameLang":"en"}],"nameIdentifiers":[{},{},{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-08-21"}],"displaytype":"detail","filename":"023059020007.pdf","filesize":[{"value":"572.2 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"023059020007.pdf","url":"https://doshisha.repo.nii.ac.jp/record/26244/files/023059020007.pdf"},"version_id":"4ede3bc1-5775-4c35-ae02-072c32aaeebe"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"深層学習","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"畳み込みニューラルネットワーク(CNN)","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"株価予測","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"テクニカル分析","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"deep learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Convolutional Neural Network(CNN)","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"stock price prediction","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"technical analysis","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"畳み込みニューラルネットワークによる株価インデックス騰落予測","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"畳み込みニューラルネットワークによる株価インデックス騰落予測","subitem_title_language":"ja"},{"subitem_title":"タタミコミ ニューラル ネットワーク ニヨル カブカ インデックス トウラク ヨソク","subitem_title_language":"ja-Kana"},{"subitem_title":"The prediction of the fluctuation of stock index by using convolutional neural network","subitem_title_language":"en"}]},"item_type_id":"1","owner":"20","path":["3855","8148"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2018-08-22"},"publish_date":"2018-08-22","publish_status":"0","recid":"26244","relation_version_is_last":true,"title":["畳み込みニューラルネットワークによる株価インデックス騰落予測"],"weko_creator_id":"20","weko_shared_id":-1},"updated":"2023-11-30T01:30:40.148967+00:00"}