[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120872-en":3,"doc-seo-120872-105":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},120872,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Between Attention and Portfolio Adjustment - Machine Learning-based Risk Preference Assessment - Insights","Financial firms recommend products with the goal of capturing customer attention and motivating portfolio change. Drawing on behavioral decision-making theory, the study explains portfolio adjustment through the risk deviation between portfolio risk and individual risk preference. It applies machine learning to estimate risk preference, then builds a dynamic adjustment model to show when attention accelerates adjustment. Field experiment results indicate that directing attention to products matching the risk deviation increases portfolio adjustment activities.","Association for Information Systems  \nAIS Electronic Library (AISeL)  \nRising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies ICIS 2023  \nData Analytics for Business and Societal Challenges  \nDec 11th, 12:00 AM  \nBetween Attention and Portfolio Adjustment: Insights from Machine Learning-based Risk Preference Assessment  \nXin Li  \nCity University of Hong Kong, [xin.li@cityu.edu.hk](xin.li@cityu.edu.hk)  \nArun Rai  \nGeorgia State University, [arunrai@gsu.edu](arunrai@gsu.edu)  \nQingping Song  \nTsinghua University, [sqp17@mails.tsinghua.edu.cn](sqp17@mails.tsinghua.edu.cn)  \nSean Xin Xu  \nTsinghua University, [xuxin@sem.tsinghua.edu.cn](xuxin@sem.tsinghua.edu.cn)  \nFollow this and additional works at: [https://aisel.aisnet.org/icis2023](https://aisel.aisnet.org/icis2023)  \nRecommended Citation  \nLi, Xin; Rai, Arun; Song, Qingping; and Xu, Sean Xin, \"Between Attention and Portfolio Adjustment: Insights from Machine Learning-based Risk Preference Assessment\" (2023) . Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies ICIS 2023. 20.  \n[https://aisel.aisnet.org/icis2023/dab_sc/dab_sc/20](https://aisel.aisnet.org/icis2023/dab_sc/dab_sc/20)  \nThis material is brought to you by the International Conference on Information Systems (ICIS) at AIS Electronic Library (AISeL) . It has been accepted for inclusion in Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies ICIS 2023 by an authorized administrator of AIS Electronic Library (AISeL) . For more information, please [contact elibrary@aisnet.org](contact elibrary@aisnet.org).  \nBetween Attention and Portfolio Adjustment  \nBetween Attention and Portfolio Adjustment: Insights from Machine Learning-based Risk  \nPreference Assessment  \nCompleted Research Paper  \nXin Li  \nDepartment of Information Systems City University of Hong Kong Hong Kong, China [Xin.Li.PhD@gmail.com](Xin.Li.PhD@gmail.com)  \nQingping Song  \nCenter for AI and Management School of Economics and Management Tsinghua University Beijing, China [sqp17@mails.tsinghua.edu.cn](sqp17@mails.tsinghua.edu.cn)  \nArun Rai  \nCenter for Digital Innovation Robinson College of Business Georgia State University  \nAtlanta, Georgia, USA [arunrai@gsu.edu](arunrai@gsu.edu)  \nSean Xin Xu  \nCenter for AI and Management School of Economics and Management Tsinghua University Beijing, China [xuxin@sem.tsinghua.edu.cn](xuxin@sem.tsinghua.edu.cn)  \nAbstract  \nFinancial firms recommend products to customers, intending to gain their attention and change their portfolios. Based on behavioral decision-making theory, we argue attention’s effect on portfolio adjustment is through the risk deviation between portfolio risk and their risk preference. Thus, to fully understand the adjustment process, it is necessary to assess customers’risk preferences. In this study, we use machine learning methods to measure customers’risk preferences. Then, we build a dynamic adjustment model and find that attention’s impact on portfolio adjustment speed is stronger when customers’ risk preference is higher than portfolio risk (which needs an upward adjustment) and when customers’ risk preference is within historical portfolio risk experience. We conducted a field experiment and found that directing customers’attention to products addressing the risk deviation would lead to more portfolio adjustment activities. Our study illustrates the role of machine learning in enhancing our understanding of financial decision-making.  \nKeywords: Risk Preference; Portfolio Adjustment; Machine Learning; Attention; FinTech  \nIntroduction  \nIt is a common practice for financial firms to approach customers and promote products, intending to gain their attention and change their portfolios. However, the current approach to recommending financial products is not always effective. Financial marketing activities need a more theoretical underst","cbCailpQTedlAL9B","https://ap.wps.com/l/cbCailpQTedlAL9B","pdf",435580,1,16,"English","en",105,"# Introduction\n## Background and motivation\n## Behavioral decision-making framework\n## Attention and search mechanisms\n## Risk preference assessment challenge\n# Research approach\n## Machine learning estimation of risk preference\n## Dynamic portfolio adjustment model\n# Empirical results\n## Field experiment on attention guidance","[{\"question\":\"How does attention affect portfolio adjustment in this study?\",\"answer\":\"Attention influences portfolio adjustment through the risk deviation between portfolio risk and customers’ risk preference, shaping whether customers resolve that deviation through search and action.\"},{\"question\":\"What method is used to assess customers’ risk preferences?\",\"answer\":\"The study uses machine learning methods to measure customers’ risk preferences rather than relying on frequent surveys or questionnaires.\"},{\"question\":\"What do the field experiment results show?\",\"answer\":\"Directing customers’ attention to products addressing the risk deviation leads to more portfolio adjustment activities.\"}]","Between Attention and Portfolio Adjustment - Machine Learning-based Risk Preference Assessment - Insights | PDF",1785732439,40,{"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},"between-attention-and-portfolio-adjustment-machine-learning-based-risk-preference-assessment-insights","",{"@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/between-attention-and-portfolio-adjustment-machine-learning-based-risk-preference-assessment-insights/120872/",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","2026-08-03",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},"How does attention affect portfolio adjustment in this study?","Question",{"text":75,"@type":76},"Attention influences portfolio adjustment through the risk deviation between portfolio risk and customers’ risk preference, shaping whether customers resolve that deviation through search and action.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What method is used to assess customers’ risk preferences?",{"text":80,"@type":76},"The study uses machine learning methods to measure customers’ risk preferences rather than relying on frequent surveys or questionnaires.",{"name":82,"@type":73,"acceptedAnswer":83},"What do the field experiment results show?",{"text":84,"@type":76},"Directing customers’ attention to products addressing the risk deviation leads to more portfolio adjustment activities.","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},[93,97,101,105,110,115,119,122,127,130,134],{"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":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":29,"slug":118},7,"Healthcare","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"]