Essays about: "Default risk"
Showing result 16 - 20 of 244 essays containing the words Default risk.
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16. A multi-gene symbolic regression approach for predicting LGD : A benchmark comparative study
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : 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. READ MORE
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17. Application of the Merton Model and the Altman Z-score Model in Credit Risk Assessment - an Empirical Study on Chinese Listed Companies
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : Corporate default poses significant risks to investors and stakeholders, highlighting the importance of predicting and managing financial risk effectively. When the geographical scope is narrowed down to China, the unique characteristics of the Chinese market, such as the lack of comprehensive credit risk databases and the influence of state-owned enterprises and small-medium enterprises, present challenges in accurately assessing creditworthiness. READ MORE
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18. Artificial Neural Networks and Inductive Biases for Multi-Instance Multi-Modal Tabular Data : A Case Study for Default Probability Estimation in Small-to-Medium Enterprise Lending
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The success of artificial neural networks in homogeneous data domains such as images, textual data, and audio and other signals has had considerable impact on Machine Learning and science in general. The domain of heterogeneous tabular data, while arguably much more common, remains much less explored with regards to artificial neural networks and deep learning. READ MORE
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19. Measurement of sectoral concentration with multiple factors
University essay from Uppsala universitet/Statistiska institutionenAbstract : One of banks core businesses today is to, in various ways, lend capital to the market and in return receive interest rate. But giving out credit comes with great risk and, therefore, precautions need to be taken. It is impossible to forecast exactly which obligor (borrower) that will default on its exposure. READ MORE
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20. Deep Learning Approach for Time- to-Event Modeling of Credit Risk
University essay from KTH/Matematisk statistikAbstract : This thesis explores how survival analysis models performs for default risk prediction of small-to-medium sized enterprises (SME) and investigates when survival analysis models are preferable to use. This is examined by comparing the performance of three deep learning models in a survival analysis setting, a traditional survival analysis model Cox Proportional Hazards, and a traditional credit risk model logistic regression. READ MORE
