Essays about: "Probability of default. Default probability"

Showing result 16 - 20 of 74 essays containing the words Probability of default. Default probability.

  1. 16. Modelling Credit Risk: Estimation of Asset and Default Correlation for an SME Portfolio

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik; Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Yaxum Cedeno; Rebecca Jansson; [2018]
    Keywords : Basel Capital Accord; Capital Requirements; SME; Portfolio Credit Risk; Monte-Carlo Simulations; Risk Weighted Assets RWA .; BaselKapitalavtal; Kapitalkrav; SME; PortföljKreditrisk; Monte-Carlo Simuleringar; Riskvägda Tillgångar RWA .;

    Abstract : When banks lend capital to counterparties they take on a risk, known as credit risk which traditionally has been the largest risk exposure for banks. To be protected against potential default losses when lending capital, banks must hold a regulatory capital that is based on a regulatory formula for calculating risk weighted assets (RWA). READ MORE

  2. 17. Safety analysis on digital hydraulics : Redundancy study for aviation applications

    University essay from Linköpings universitet/Fluida och mekatroniska system

    Author : Robert Pettersson; [2018]
    Keywords : ;

    Abstract : Digital hydraulic actuators (DHA) are an interesting new technology that couldreplace todays system with inefficient proportional valves. By using an arrayof on/off valves the hydraulic pressures are discretised. This gives a fixed setof force outputs that can be used to control the actuator. READ MORE

  3. 18. Modelling Probability of Default in the Nordics

    University essay from Lunds universitet/Matematisk statistik

    Author : Egil Nordgren; Carl Göransson; [2018]
    Keywords : Credit risk; Probability of default; Logistic regression; Risk-drivers; Mathematics and Statistics;

    Abstract : Credit risk is one of the greatest risks facing financial institutions, and it is therefore very important that models with good predictive power are used in order to etter capture this risk. This thesis proposes logistic regression models for modelling risk-drivers of the probability of default in a financial institution active in he Nordics. READ MORE

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

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik; Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Axel Cronstedt; Rebecca Andersson; [2018]
    Keywords : 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;

    Abstract : 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. READ MORE

  5. 20. A company’s ability Not to default on a loan : Does the location have an impact?

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : ALYCIA SUNDQVIST; [2018]
    Keywords : Location; municipality; ability to pay; logistic regression; Lokalisering; kommun; betalningsf¨orm˚aga; logistisk regression;

    Abstract : This thesis aims to answer the question if the type of region or category of a municipality in which a company is located in, impacts the company’s ability not to default on a loan. Previous literature is used to find which determinants have an impact on a company’s survival from five levels: Macro, Industry, Regional, Company and Individual entrepreneur. READ MORE