{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1390870529360843392.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.11517/jsaisigtwo.2026.fin-036_76"}}],"dc:title":[{"@language":"ja","@value":"部分空間正則化付き主成分分析を用いた日米業種リードラグ投資戦略"},{"@language":"en","@value":"Lead-lag strategies for Japanese and U.S. sectors using subspace regularization PCA"}],"dc:language":"ja","description":[{"type":"abstract","notation":[{"@language":"ja","@value":"<p>本研究は、取引時間帯の非同期性により先に閉まる市場で確定した情報が後に開く市場の寄付きから日中にかけて反映するというリード・ラグ仮説を、日米の業種別ETFデータを用いて検証する。具体的には、米国の業種ETFで観測される当日のClose-to-Closeリターンを情報集合とし、日本の業種ETFの翌営業日Open-to-Closeリターンを予測対象として、日米の結合相関行列に対する部分空間正則化付きPCAに基づく予測シグナルを構成する。当該シグナルは米国のリターンに対する日本のリターンのランク線形予測器として表現でき、共通ファクターが米国で顕在化し翌日に日本へ波及する理想化モデルの下で、最良線形予測であることが示される。実証分析では、提案法に基づくロング・ショート戦略が、モメンタム、正則化なしPCA、モメンタムとのダブルソート等のベースラインと比較して、リスク調整後のパフォーマンスおよび最大ドローダウンの観点で優位である。</p>"}],"abstractLicenseFlag":"allow"}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1410870529360843393","@type":"Researcher","foaf:name":[{"@language":"ja","@value":"中川 慧"},{"@language":"en","@value":"NAKAGAWA Kei"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Osaka Metropolitan University"},{"@language":"ja","@value":"大阪公立大学"},{"@language":"en","@value":"MATSUO Institute, Inc"},{"@language":"ja","@value":"株式会社松尾研究所"}]},{"@id":"https://cir.nii.ac.jp/crid/1410870529360843394","@type":"Researcher","foaf:name":[{"@language":"ja","@value":"竹本 悠城"},{"@language":"en","@value":"TAKEMOTO Yuki"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Independent Researcher"},{"@language":"ja","@value":"独立研究者"}]},{"@id":"https://cir.nii.ac.jp/crid/1410870529360843395","@type":"Researcher","foaf:name":[{"@language":"ja","@value":"久保 健治"},{"@language":"en","@value":"KUBO Kenji"}],"jpcoar:affiliationName":[{"@language":"en","@value":"MATSUO Institute, Inc"},{"@language":"ja","@value":"株式会社松尾研究所"},{"@language":"en","@value":"The University of Tokyo"},{"@language":"ja","@value":"東京大学"}]},{"@id":"https://cir.nii.ac.jp/crid/1410870529360843392","@type":"Researcher","foaf:name":[{"@language":"ja","@value":"加藤 真大"},{"@language":"en","@value":"KATO Masahiro"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Osaka Metropolitan University"},{"@language":"ja","@value":"大阪公立大学"},{"@language":"en","@value":"Mizuho-DL Financial Technology Co., Ltd."},{"@language":"ja","@value":"みずほ第一フィナンシャルテクノロジー株式会社"}]}],"publication":{"publicationIdentifier":[{"@type":"EISSN","@value":"24365556"}],"prism:publicationName":[{"@language":"ja","@value":"人工知能学会第二種研究会資料"},{"@language":"en","@value":"JSAI Technical Report, Type 2 SIG"},{"@language":"ja","@value":"人工知能学会第二種研究会"}],"dc:publisher":[{"@language":"en","@value":"The Japanese Society for Artificial Intelligence"},{"@language":"ja","@value":"一般社団法人 人工知能学会"}],"prism:publicationDate":"2026-03-18","prism:volume":"2026","prism:number":"FIN-036","prism:startingPage":"76","prism:endingPage":"83"},"jpcoar:conferenceName":"金融情報学研究会","jpcoar:conferencePlace":"成蹊大学 6号館401教室およびオンライン（Zoom使用）のハイブリッド開催","availableAt":"2026-03-18","foaf:topic":[{"@id":"https://cir.nii.ac.jp/all?q=%E9%83%A8%E5%88%86%E7%A9%BA%E9%96%93%E6%AD%A3%E5%89%87%E5%8C%96%E4%BB%98%E3%81%8D%E4%B8%BB%E6%88%90%E5%88%86%E5%88%86%E6%9E%90","dc:title":"部分空間正則化付き主成分分析"},{"@id":"https://cir.nii.ac.jp/all?q=%E3%83%AA%E3%83%BC%E3%83%89%E3%83%A9%E3%82%B0","dc:title":"リードラグ"},{"@id":"https://cir.nii.ac.jp/all?q=%E3%82%BB%E3%82%AF%E3%82%BF%E3%83%BC%E3%83%AD%E3%83%BC%E3%83%86%E3%83%BC%E3%82%B7%E3%83%A7%E3%83%B3","dc:title":"セクターローテーション"}],"dataSourceIdentifier":[{"@type":"JALC","@value":"oai:japanlinkcenter.org:2015068438"}]}