Logo DOAB
  • Connection pour éditeurs
    • Support
    • Language 
      • English
      • français
    • Deposit
            Voir le document 
            •   Accueil de DSpace
            • Voir le document
            •   Accueil de DSpace
            • Voir le document
            JavaScript is disabled for your browser. Some features of this site may not work without it.

            Proceedings of the Second International Forum on Financial Mathematics and Financial Technology

            Thumbnail
            Contributor(s)
            Zheng, Zhiyong (editor)
            Language
            English
            Afficher la notice complète
            Résumé
            This open access book is the documentary of the Second International Forum on Financial Mathematics and Financial Technology, with focus on selected aspects of the current and upcoming trends in FinTech. In detail, the included scientific papers cover financial mathematics and FinTech, presenting the innovative mathematical models and state-of-the-art technologies such as deep learning, with the aim to improve the financial analysis and decision-making and enhance the quality of financial services and risk control. The variety of the papers delivers added value for both scholars and practitioners where they will find perfect integration of elegant mathematical models and up-to-date data mining technologies in financial market analysis. Due to COVID-19, the conference was held virtually on August 13–15, 2021, jointly held by the School of Mathematics of Renmin University of China, the Engineering Research Center of Financial Computing and Digital Engineering of Ministry of Education, the Statistics and Big Data Research Institute of Renmin University of China, the Blockchain Research Institute of Renmin University of China, the Zhongguancun Internet Finance Research Institute, and the Renmin University Press.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/175569
            Keywords
            Financial Mathematics; Financial Technology; Machine Learning; Deep Learning; Intelligent Algorithms; Financial Mathematical Models; Data Minning
            DOI
            10.1007/978-981-99-2366-3
            ISBN
            9789819923663, 9789819923656
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Singapore, 2023
            Grantor
            • Renmin University of China
            Imprint
            Springer Nature Singapore
            Series
            Financial Mathematics and Fintech,
            Pages
            237
            • OAPEN harvesting collection

            Parcourir

            Tout DSpaceSubjectsPublishersLanguagesCollections

            Mon compte

            Ouvrir une sessionS'inscrire

            Export

            Repository metadata
            Doabooks

            • For Researchers
            • For Librarians
            • For Publishers
            • Our Supporters
            • Resources
            • DOAB

            Newsletter


            • subscribe to our newsletter
            • view our news archive

            Follow us on

            • Twitter

            License

            • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

            donate


            • Donate
              Support DOAB and the OAPEN Library

            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

            Directory of Open Access Books is a joint service of OAPEN, OpenEdition, CNRS and Aix-Marseille Université, provided by DOAB Foundation.

            Websites:

            DOAB
            www.doabooks.org

            OAPEN Home
            www.oapen.org

            OAPEN OA Books Toolkit
            www.oabooks-toolkit.org

            Export search results

            The export option will allow you to export the current search results of the entered query to a file. Differen formats are available for download. To export the items, click on the button corresponding with the preferred download format.

            A logged-in user can export up to 15000 items. If you're not logged in, you can export no more than 500 items.

            To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

            After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.