Sökning: "Loss Given Default"
Visar resultat 1 - 5 av 20 uppsatser innehållade orden Loss Given Default.
1. A Dual-Lens Approach to Loss Given Default Estimation: Traditional Methods and Variable Analysis
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : This report seeks to thoroughly examine different approaches to estimating Loss Given Default through a comparison of traditional estimation methods, as well as a deeper variable analysis on micro, small, and medium-sized companies using primarily regression decision trees. The comparative study concluded that estimating loss given default depends heavily on business-specific factors and data variety. LÄS MER
2. Portfolio Risk Modelling in Venture Debt
Master-uppsats, KTH/Matematisk statistikSammanfattning : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. LÄS MER
3. A multi-gene symbolic regression approach for predicting LGD : A benchmark comparative study
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : Under the Basel accords for measuring regulatory capital requirements, the set of credit risk parameters probability of default (PD), exposure at default (EAD) and loss given default (LGD) are measured with own estimates by the internal rating based approach. The estimated parameters are also the foundation of understanding the actual risk in a banks credit portfolio. LÄS MER
4. Optimization of Collateral Allocation for Corporate Loans : A nonlinear network problem minimizing the expected loss in case of default
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : Collateral management has become an increasingly valuable aspect of credit risk. Managing collaterals and constructing accurate models for decision making can give any lender a competitive advantage and decrease overall risks. LÄS MER
5. Loss Given Default Estimation with Machine Learning Ensemble Methods
Master-uppsats, KTH/Matematisk statistikSammanfattning : This thesis evaluates the performance of three machine learning methods in prediction of the Loss Given Default (LGD). LGD can be seen as the opposite of the recovery rate, i.e. the ratio of an outstanding loan that the loan issuer would not be able to recover in case the customer would default. LÄS MER