Since the US sub loan crisis, countries have paid more attention to the prevention of credit risks. SMEs are more difficult to measure their credit risk than large enterprises due to their own limitations, and therefore the issue of their risk measurement deserves discussions. This paper analyzes the current situation of SMEs’ credit financing, properly selects the financial data of listed companies on the New OTC Market, and establishes a Logistic regression analysis model based on factor analysis of cross section data, so as to measure the credit risk level of SMEs.


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    Titel :

    Statistical Measurement of SMEs’ Credit Risk from the Perspective of Financial Crisis


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Guda, Alexander (Herausgeber:in) / Zhang, Chenyao (Autor:in) / Zhang, Jinsong (Autor:in)

    Kongress:

    International School on Neural Networks, Initiated by IIASS and EMFCSC ; 2022 ; St.Petersburg, Russia February 08, 2022 - February 10, 2022



    Erscheinungsdatum :

    16.11.2022


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch