Sökning: "Credit Method"

Visar resultat 6 - 10 av 486 uppsatser innehållade orden Credit Method.

  1. 6. Modelling Proxy Credit Cruves Using Recurrent Neural Networks

    Master-uppsats, KTH/Matematisk statistik

    Författare :Lucas Fageräng; Hugo Thoursie; [2023]
    Nyckelord :Deep Neural Networks; Credit Risk; Financial Modelling; LSTM; Credit Default Swaps; Credit Valuation Adjustment; Djupa Neurala Nätverk; Kreditrisk; Finansiell Modellering; LSTM; Kreditswappar; Kreditvärderingsjustering;

    Sammanfattning : Since the global financial crisis of 2008, regulatory bodies worldwide have implementedincreasingly stringent requirements for measuring and pricing default risk in financialderivatives. Counterparty Credit Risk (CCR) serves as the measure for default risk infinancial derivatives, and Credit Valuation Adjustment (CVA) is the pricing method used toincorporate this default risk into derivatives prices. LÄS MER

  3. 7. An Analysis of the Swedish Real  Estate Bond Market:  Characteristics, Opportunities, and  Risks : A combination of a qualitative and quantitative study

    Master-uppsats, KTH/Fastighetsföretagande och finansiella system

    Författare :Hanna Landstedt; Mikaela Kulti; [2023]
    Nyckelord :Real Estate Bond; Bond Issuance; Bond Maturities; Credit Risk; Investment Grade; High Yield; Corporate Bond Market; Real Estate Bond Market; Fastighetsobligation; Utställande av obligationer; Obligationslöptid; Kreditrisk; Högränteobligationer; Företagsobligationsmarknaden; Fastighetsobligationsmarknaden;

    Sammanfattning : In the aftermath of the 2008 financial crisis, the debt capital market in Sweden experienced rapid growth, resulting in a doubling of its size. In recent years, real estate companies have become increasingly dependent on financing through the capital markets. LÄS MER

  4. 8. Credit Card Approval Prediction : A comparative analysis between logistic regressionclassifier, random forest classifier, support vectorclassifier with ensemble bagging classifier.

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Dhanush Janapareddy; Narendra Chowdary Yenduri; [2023]
    Nyckelord :Machine Learning; Logistic Regression; Random Forest; Support Vector Machine; Ensemble Learning Bagging.;

    Sammanfattning : Background. Due to an increasing number of credit card defaulters, companies arenow taking greater precautions when approving credit applications. When a customermeets certain requirements, credit card firms typically use their experience todecide whether to grant them a credit card. LÄS MER

  5. 9. Methods for local energy and climate planning : A Case stuudy on the Urban Community of Dunkirk

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Sacha Thibault; [2023]
    Nyckelord :Energy transition - Climate and energy policy - Renewable energy - Decision-Support Tools - Local authorities; Energiomställning - Klimat- och energipolitik - Förnybar energi - Verktyg för beslutsstöd - Lokala myndigheter;

    Sammanfattning : Energy management concerns were raised in France after the oil crisis in the 1970s. From then, the local actors developed policies to better control the energy production and consumption on the territories. Climate considerations and the need to limit greenhouse gases (GHG) emissions were then added to these energy issues in the early 2000s. LÄS MER

  7. 10. Den regionala karaktärens påverkan på kreditgivning till företag

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för företagande, innovation och hållbarhet

    Författare :Felicia Mandorf; Juhlina Friman; [2023]
    Nyckelord :Regionala skillnader; region; kreditgivning; bank; kreditbedömning;

    Sammanfattning : Abstract Title: The impact of the regional characteristics on lending to companies. Level: Degree of Master of Science in Business and Economics  Authors: Felicia Mandorf and Juhlina Friman   Published: 2023-05-23 Supervisor: Hans Landström Background: There is extensive research regarding the lending process to companies. LÄS MER