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Credit-Risk Modelling

Name: Credit-Risk Modelling
Brand: Springer Nature Switzerland AG
SKU: 9783030069001
Price: 72.29 EUR
Availability: InStock

Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python

Автор: David Jamieson Bolder

Език:

Корици: С меки корици

Издател: Springer Nature Switzerland AG

Наличност: Външен склад

Изпращаме след 5-8 дни

72.29 € 141.39 лв

The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios i...

Информация за книгата

Автор

David Jamieson Bolder

Език

Английски език

Корици

Книга - С меки корици

Издадена

2019

страници

684

EAN

9783030069001

ISBN

3030069001

Enbook ID

21348282

Издател

Springer Nature Switzerland AG

Теглоt

1086

Размери

155 x 235 x 37

Пълно описание

The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning resource and reference text for financial-risk practitioners and an excellent source for advanced undergraduate and graduate students seeking to acquire knowledge of the key elements of this discipline.

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Credit-Risk Modelling

Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python

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