Sökning: "Credit risk modeling"

Visar resultat 1 - 5 av 23 uppsatser innehållade orden Credit risk modeling.

  1. 1. Estimation of Loss Given Default Distributions for Non-Performing Loans Using Zero-and-One Inflated Beta Regression Type Models

    Master-uppsats, KTH/Matematisk statistik; KTH/Matematisk statistik

    Författare :Carolina Ljung; Maria Svedberg; [2020]
    Nyckelord :Loss Given Default; Non-Performing Loans; Internal Ratings Based Approach; Basel Accords; Zero-and-One Inflated Beta Regression; Bayesian Inference; Förlust vid fallissemang; Icke-presterande lån; Intern riskklassificeringsmetod; Basel; Utvidgad betaregression; Bayesiansk inferens;

    Sammanfattning : This thesis investigates three different techniques for estimating loss given default of non-performing consumer loans. This is a contribution to a credit risk evaluation model compliant with the regulations stipulated by the Basel Accords, regulating the capital requirements of European financial institutions. LÄS MER

  2. 2. Efficient Monte Carlo Simulation for Counterparty Credit Risk Modeling

    Master-uppsats, KTH/Matematisk statistik

    Författare :Sam Johansson; [2019]
    Nyckelord :CCR; OTC derivatives; European option; Bermudan option; CVA; jump-diffusion model; stochastic intensity model; Monte Carlo; variance reduction; importance sampling; least squares Monte Carlo; CCR; OTC-derivat; europeisk option; Bermuda-option; CVA; jump-diffusion-modell; stokastisk intensitetsmodell; Monte Carlo; variansreduktion; importance sampling; least squares Monte Carlo;

    Sammanfattning : In this paper, Monte Carlo simulation for CCR (Counterparty Credit Risk) modeling is investigated. A jump-diffusion model, Bates' model, is used to describe the price process of an asset, and the counterparty default probability is described by a stochastic intensity model with constant intensity. LÄS MER

  3. 3. Peer-to-Peer Lending from a CDO Perspective

    Master-uppsats, Göteborgs universitet/Graduate School

    Författare :Axel Helgason; [2018-07-04]
    Nyckelord :Credit risk management; Credit risk modeling; Collateralized debt obligations CDO ; Peer-to-peer lending;

    Sammanfattning : MSc in Finance.... LÄS MER

  4. 4. Readjusting Historical Credit Ratings : using Ordered Logistic Regression and Principal ComponentAnalysis

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik; Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Axel Cronstedt; Rebecca Andersson; [2018]
    Nyckelord :Ordered Logistic Regression; Principal Component Analysis; MacroEconomic Variables; Credit Risk; Credit Ratings; Multivariate Time SeriesData; Ordinal logistisk regression; Principalkomponentanalys; Makro-ekonomiska variabler; Kreditratings; Multivariata tidsserier;

    Sammanfattning : Readjusting Historical Credit Ratings using Ordered Logistic Re-gression and Principal Component Analysis The introduction of the Basel II Accord as a regulatory document for creditrisk presented new concepts of credit risk management and credit risk mea-surements, such as enabling international banks to use internal estimates ofprobability of default (PD), exposure at default (EAD) and loss given default(LGD). These three measurements is the foundation of the regulatory capitalcalculations and are all in turn based on the bank’s internal credit ratings. LÄS MER

  5. 5. Estimation of Probability of Default in Low Default Portfolios

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Linnéa Gerhardsson; Nina Castor; [2017]
    Nyckelord :Probability of default; PD; Low default portfolio; LDP; BCR; Bayesian; Vasicek; Monte Carlo; subportfolios; grade level estimates.; Mathematics and Statistics;

    Sammanfattning : Estimation of probability of default (PD) is a fundamental part of credit risk modeling, and estimation of PD in low default portfolios is a common issue for banks and financial institutions. The Basel Committee on Banking Supervision requires banks and financial institutions to add an additional margin of conservatism to its PD estimates in the case of insufficient data, as in low default portfolios with few default observations. LÄS MER