[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122911-en":3,"doc-seo-122911-105":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},122911,137441390410,"Hazel","https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984",8,"Research & Report","Improving the prediction of firm performance using nonfinancial disclosures - A machine learning approach","This study tests whether firm performance prediction improves when financial predictive models incorporate nonfinancial disclosures, including narrative disclosure tone and corporate governance indicators. Three predictive models are constructed with different predictor sets, using machine learning techniques random forest and stochastic gradient boosting. Data from 1,250 annual reports of 125 nonfinancial firms in Pakistan covering 2011–2020 are analyzed. Results show both narrative disclosure tone and corporate governance indicators significantly increase prediction accuracy, supporting investor confidence and informing regulators and investors.","PR IFYS GOL BANGOR / BANGOR  \nImproving the prediction of firm performance using nonfinancial disclosures: A machine learning approach  \nSufi, Usman ; Hasan, Arshad ; Hussainey, Khaled  \nJournal of Accounting in Emerging Economies  \nDOI:  \n10.1108/JAEE-07-2023-0205  \nE-pub ahead of print: 24/06/2024  \nPeer reviewed version  \nCyswllt i'r cyhoeddiad / Link to publication  \nDyfyniad o'r fersiwn a gyhoeddwyd / Citation for published version (APA):  \nSufi, U. , Hasan, A. , & Hussainey, K. (2024) . Improving the prediction of firm performance using nonfinancial disclosures: A machine learning approach. Journal of Accounting in Emerging Economies. Advance online publication. [https://doi.org/10.1108/JAEE-07-2023-0205](https://doi.org/10.1108/JAEE-07-2023-0205)  \nHawliau Cyffredinol / General rights  \nCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  \n• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  \n• You may not further distribute the material or use it for any profit-making activity or commercial gain  \n• You may freely distribute the URL identifying the publication in the public portal ?  \nTake down policy  \nIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.  \nImproving the prediction of firm performance using nonfinancial disclosures: a machine learning approach  \nUsman Sufi  \nInnovation Technology Centre, Lahore School of Economics, Lahore, Pakistan  \n[usman.sufi@lahoreschool.edu.pk](usman.sufi@lahoreschool.edu.pk)  \nArshad Hasan*  \nFaculty of Business,  \nLahore School of Economics, Lahore, Pakistan  \n[arshad@lahoreschool.edu.pk](arshad@lahoreschool.edu.pk)  \nKhaled Hussainey  \nBangor Business School  \nBangor University, Bangor, UK  \n[k.hussainey@bangor.ac.uk](k.hussainey@bangor.ac.uk)  \n* Corresponding author  \nImproving the prediction of firm performance using nonfinancial disclosures: a machine learning approach  \nABSTRACT  \nPurpose: The purpose of this study is to test whether the prediction of firm performance can be enhanced by incorporating nonfinancial disclosures, such as narrative disclosure tone and corporate governance indicators, into financial predictive models.  \nDesign/Methodology/Approach: Three predictive models are developed, each with a different set of predictors. This study utilises two machine learning techniques, random forest and stochastic gradient boosting, for prediction via the three models. The data are collected  \nfrom a sample of 1250 annual reports of 125 nonfinancial firms in Pakistan for the period 2011- 2020.  \nFindings: Our results indicate that both narrative disclosure tone and corporate governance indicators significantly add to the accuracy of financial predictive models of firm performance. Practical implications: Our results offer implications for the restoration of investor confidence in the highly uncertain Pakistani market by establishing nonfinancial disclosures as reliable predictors of future firm performance. Accordingly, they encourage investors to pay more attention to these disclosures while making investment decisions. In addition, they urge regulators to promote and strengthen the reporting of such nonfinancial information. Originality: This study addresses the neglect of nonfinancial disclosures in the prediction of firm performance and the scarcity of corporate governance literature relevant to the use of machine learning techniques.  \nKeywords: Firm Performance, Machine Learning, Random Forest, Stochastic Gradient Boosting, Narrative Disclosure Tone, Corporate Governance.  \n1. Introduction  \nThe ability to predict a firm's performance with ever-improved ","cbCaiaMO9DvDWbVR","https://ap.wps.com/l/cbCaiaMO9DvDWbVR","pdf",1391865,1,55,"English","en",105,"# Abstract\n# Introduction\n# Methodology and Data\n# Results and Findings\n# Practical Implications","[{\"question\":\"What is the main purpose of the study?\",\"answer\":\"To test whether adding nonfinancial disclosures—such as narrative disclosure tone and corporate governance indicators—enhances predictions of firm performance within financial predictive models.\"},{\"question\":\"Which machine learning techniques are used?\",\"answer\":\"The study develops three predictive models and applies random forest and stochastic gradient boosting to generate predictions.\"},{\"question\":\"What data and time period support the analysis?\",\"answer\":\"The models are trained and evaluated using 1,250 annual reports from 125 nonfinancial firms in Pakistan for the period 2011–2020.\"}]","Improving the prediction of firm performance using nonfinancial disclosures - A machine learning approach | PDF",1785813621,139,{"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},"improving-the-prediction-of-firm-performance-using-nonfinancial-disclosures-a-machine-learning-approach","",{"@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/improving-the-prediction-of-firm-performance-using-nonfinancial-disclosures-a-machine-learning-approach/122911/",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","2026-08-04",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},"What is the main purpose of the study?","Question",{"text":75,"@type":76},"To test whether adding nonfinancial disclosures—such as narrative disclosure tone and corporate governance indicators—enhances predictions of firm performance within financial predictive models.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning techniques are used?",{"text":80,"@type":76},"The study develops three predictive models and applies random forest and stochastic gradient boosting to generate predictions.",{"name":82,"@type":73,"acceptedAnswer":83},"What data and time period support the analysis?",{"text":84,"@type":76},"The models are trained and evaluated using 1,250 annual reports from 125 nonfinancial firms in Pakistan for the period 2011–2020.","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},[93,97,101,105,110,115,120,123,128,131,135],{"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":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]