Deep Learning and Statistical Approaches in Financial Modeling of Foreign Assets and Liabilities of Nepal’s Banking System

Deep Learning and Statistical Approaches in Financial Modeling of Foreign Assets and Liabilities of Nepal’s Banking System | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Deep Learning and Statistical Approaches in Financial Modeling of Foreign Assets and Liabilities of Nepal’s Banking System Aayush Man Regmi, Samrajya Raj Acharya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6483251/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In an environment marked by financial volatility and rapid economic shifts, reliable forecasts are critical for informed policy-making and strategic financial planning. This study investigates the detailed mathematical exploration followed by its computational performance of time series and deep learning models namely Auto Regressive Integrated Moving Average (ARIMA), Recurrent Neural Network (RNN), and Temporal Convolutional Network (TCN) applied to foreign assets and liabilities of banking system of Nepal consisting monetary authorities and various depository corporations. Using available primary data, we analyze trends, seasonal patterns, trajectories and their descriptive statistics to capture underlying behaviors. Also, in our work, we have identified the optimal ARIMA order that most effectively captures the linear trend. Empirical study shows that the RNN is able to handle the non-linear patterns which is determined by performance metrices on the training and testing split. TCN being computationally extensive model is not able to capture robust relation of the data due to lack of long-range dependencies and large time windowed dataset for training. Based on our results, the RNN could be used as the most suitable time series forecasting model for the foreign assets and liabilities of Nepal as it enhances the accuracy, minimizes error, and improves effectiveness in contributing to decision-making in banking system. JEL Classification: C22, C45, E44, E60 Econometrics Artificial Intelligence and Machine Learning Financial Mathematics assets and liabilities deep learning models descriptive statistics performance metrices seasonal patterns Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6483251","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":445063322,"identity":"96196a4c-53be-4826-a606-2f70335b3dcd","order_by":0,"name":"Aayush Man Regmi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYLACxgY4aQNiNB4gRUsamEGsFjA4DCbxauFvP2Mm+XPHPTn5sMMNzIU7ztutbT8MtKXGJhqXFokzOWbSvGeKjQ1vJzYwzzxzO3nbmUSglmNpuQ249BwAamFsS0jcOBuohbftdrLZAaAWxobDOLXIn38DdFhbQj1Uy7lks/MP8WsxuJFjJsHblpAgLw3WcsDO7AYBWwxvPCu2Bmox3ADUcpj3THKC2Q2gLQl4/CJ3PnnjTaDD5OVnpz98zLvDzt7sfPrDBx9qbHB7n4HDAOLCA8CgAEZQIlhlAk7lIMD+AEzJg5QCtdjjVTwKRsEoGAUjEgAAwIpm3yt2/g4AAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0002-4607-4040","institution":"Vellore Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Aayush","middleName":"Man","lastName":"Regmi","suffix":""},{"id":445063352,"identity":"eaad4cc2-4555-4242-aaf6-e8e50f712095","order_by":1,"name":"Samrajya Raj Acharya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYPACNjBp8AHEZCdFi+EMEJOZFLuYecAkAVX8/Yefbq6o4Uvsn334QbHNr23yfMwMjB8+5uDWInEjzezmmWNsiTPOpRkY5/bdNmxjZmCWnLkNjzU3GMxuNrCxJTacYQBq6bnNCNTCxsyLR4v8+ePfbjb8Y0ucf4b9g7Flz217gloMDuSY3WxsY0vccIbHwJjhx+1EgloMb+SU3WzsYzPeeIanwLC34XZyGzNjM16/yJ0/vu1mw7djsvPOsG8z+PHntu389uaDHz7i8z4EHHNsAEaiAWMbiMPYQFA9ENTYAwnmBwx/iFE8CkbBKBgFIw0AAGk6VS0Oi+aEAAAAAElFTkSuQmCC","orcid":"","institution":"Kathmandu University","correspondingAuthor":true,"prefix":"","firstName":"Samrajya","middleName":"Raj","lastName":"Acharya","suffix":""}],"badges":[],"createdAt":"2025-04-19 07:45:05","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6483251/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6483251/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81077391,"identity":"aeaac0a6-0b7b-4c3c-bea7-7e258631e974","added_by":"auto","created_at":"2025-04-22 03:29:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1013632,"visible":true,"origin":"","legend":"","description":"","filename":"DeepLearningandStatisticalApproachesinFinancialModelingofForeignAssetsandLiabilitiesofNepalsBankingSystem.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6483251/v1_covered_ac85c37b-cbd2-4f0c-8152-f6d8f0c709e7.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDeep Learning and Statistical Approaches in Financial Modeling of Foreign Assets and Liabilities of Nepal’s Banking System\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"assets and liabilities, deep learning models, descriptive statistics, performance metrices, seasonal patterns","lastPublishedDoi":"10.21203/rs.3.rs-6483251/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6483251/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn an environment marked by financial volatility and rapid economic shifts, reliable forecasts are critical for informed policy-making and strategic financial planning. 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