[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125359-en":3,"doc-seo-125359-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125359,962075114101,"Seraphina","https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165",8,"Research & Report","Hedge Fund Performance - Classification with Machine Learning - and Managerial Implications","Hedge funds attract sustained interest from academic and industry audiences, yet hedge fund databases rely on declared strategies without a universal classification scheme. This inconsistency can create biased and inaccurate strategy labels, distorting investors’ expectations and expected risk-return profiles. Using machine learning, the study tests whether reported fund strategies align with realized performance and evaluates how classification shapes managerial decision-making. Results indicate limited alignment for most strategies and show that classification influences abnormal returns and risk exposures.","British Journal of Management, Vol. 36, 1835–1858 (2025) DOI: 10.1111/1467-8551.70011  \nHedge Fund Performance, Classification with Machine Learning, and Managerial Implications  \nEmmanouil Platanakis, 1 Dimitrios Stafylas,2 Charles Sutcliffe 3  \nand Wenke Zhang4  \n1 School of Management, University of Bath, Bath, BA2 7AY, UK, 2 School for Business and Society, University of York, York, YO10 5GD, UK, 3The ICMA Centre, Henley Business School, University of Reading, Reading, RG6 6DL, UK, and  \n4 College of Business, Arts and Social Sciences, Brunel University of London, Middlesex, Uxbridge, UB8 3PH, UK  \nCorresponding author: email: [c.m.s.sutcliffe@gmail.com](c.m.s.sutcliffe@gmail.com)  \nPrior academic research on hedge funds focuses predominantly on fund strategies in relation to market timing, stock picking and performance persistence, among others. However, the hedge fund industry lacks a universal classification scheme for strategies, leading to potentially biased fund classificationsand inaccurate expectations of hedge fund performance. This paper uses machine learning techniques to address this issue. First, it examines whether the reported fund strategies are consistent with their performance. Second, it examines the potential impact of hedge fund classification on managerial decision-making. Our results suggest that for most reported strategies there is no alignment with fund performance. Classification matters in terms of abnormal returns and risk exposures, although the market factor remains consistently the most important exposure for most clusters and strategies. An important policy implication of our study is that the classification of hedge funds affects asset and portfolio allocation decisions, and the construction of the benchmarks against which performance is  \njudged.  \nIntroduction  \nDuring the last decade, hedge funds (HFs) have received significant attention from both academic researchers and practitioners. As of the second quarter of 2024, the total assets under management for the HF industry were almost USD$5 . 1 trillion (BarclayHedge, 2024) . Each HF declares its investment strategy, which is both advertised to potential investors and used by databases when reporting HF performance.1 Investors seek to achieve a diversified portfolio when making asset allocation deci-  \nWe are grateful to the editor, an associate editor and three anonymous reviewers of this journal, as well as conference participants atthe 2023 Annual Meeting of the European Financial Management Association (EFMA) 2023 and the BAFA Annual Conference 2023 for their useful comments and suggestions that helped us improve the paper significantly.  \n1 Due to the private partnership nature of HFs, information disclosure is not regulated by the Securities and Exchange Commission, and the inclusion of a HF in a database is a voluntary decision taken by its managers. This can lead to history bias, as only the more successful HF managers are motivated to report their performance. Even if a fund manager decides to report their performance, this could be limited to only one database.  \nsions, which rely on the expected risk and return of possible investments and their correlations with each other. The formation of these expectations for HFs is heavily influenced by the reported past performance of the different HF strategies supplied by the available databases (e.g. Agarwal, Arisoy and Naik, 2017; Karehnke and Roon, 2022) . Therefore, the classification of HFs into particular strategies by databases has an important influence on investment decisions.  \nWhile databases generally classify HFs according to the strategy declared by the HF itself, HFs sometimes diverge from, adjust or cease to follow their declared strategy. In consequence, such HFs are classified by the databases as an inappropriate strategy. Since performance differs as between strategies, this leads to investors forming inaccurate expectations when evaluating HFs, and this prevents th","cbCaisRSRyEcJzdD","https://ap.wps.com/l/cbCaisRSRyEcJzdD","pdf",379427,1,24,"English","en",105,"# Introduction\n## Hedge fund strategy classification and data biases\n## Machine learning approach and study questions\n## Policy and managerial implications","[{\"question\":\"Why does hedge fund strategy classification matter for investors?\",\"answer\":\"Because different databases use different classification schemes, investors may form inaccurate expectations about performance and risk-return tradeoffs when evaluating hedge funds.\"},{\"question\":\"How does the study assess whether reported strategies match performance?\",\"answer\":\"It uses machine learning techniques to examine consistency between reported fund strategies and realized performance outcomes.\"},{\"question\":\"What managerial implications does the paper highlight?\",\"answer\":\"Hedge fund classification affects asset and portfolio allocation decisions and the construction of benchmarks used to judge performance.\"}]","Hedge Fund Performance - Classification with Machine Learning - and Managerial Implications | PDF",1785898410,60,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"hedge-fund-performance-classification-with-machine-learning-and-managerial-implications-125359","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/hedge-fund-performance-classification-with-machine-learning-and-managerial-implications-125359/125359/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why does hedge fund strategy classification matter for investors?","Question",{"text":75,"@type":76},"Because different databases use different classification schemes, investors may form inaccurate expectations about performance and risk-return tradeoffs when evaluating hedge funds.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the study assess whether reported strategies match performance?",{"text":80,"@type":76},"It uses machine learning techniques to examine consistency between reported fund strategies and realized performance outcomes.",{"name":82,"@type":73,"acceptedAnswer":83},"What managerial implications does the paper highlight?",{"text":84,"@type":76},"Hedge fund classification affects asset and portfolio allocation decisions and the construction of benchmarks used to judge performance.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,109,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":29,"slug":108},5,"Comic","comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]