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Credit-Risk Modelling

- Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python
Af: David Jamieson Bolder Engelsk Hardback

Credit-Risk Modelling

- Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python
Af: David Jamieson Bolder Engelsk Hardback
Tjek vores konkurrenters priser
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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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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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 684
ISBN-13: 9783319946870
Indbinding: Hardback
Udgave:
ISBN-10: 3319946870
Kategori: Virksomhedsøkonomi
Udg. Dato: 12 nov 2018
Længde: 42mm
Bredde: 166mm
Højde: 237mm
Forlag: Springer International Publishing AG
Oplagsdato: 12 nov 2018
Forfatter(e): David Jamieson Bolder
Forfatter(e) David Jamieson Bolder

Kategori Virksomhedsøkonomi

ISBN-13 9783319946870

Sprog Engelsk

Indbinding Hardback

Sider 684

Udgave

Længde 42mm

Bredde 166mm

Højde 237mm

Udg. Dato 12 nov 2018

Oplagsdato 12 nov 2018

Forlag Springer International Publishing AG