Credit-Risk Modelling: Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python - Hardcover

Bolder, David Jamieson

 
9783319946870: Credit-Risk Modelling: Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python
Hardcover
ISBN 10: 3319946870 ISBN 13: 9783319946870
Verlag: Springer, 2018

Inhaltsangabe

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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

David Jamieson Bolder is currently head of the World Bank Group’s (WBG) model-risk function. Prior to this appointment, he provided analytic support to the Bank for International Settlements’ (BIS) treasury and asset-management functions and worked in quantitative roles at the Bank of Canada, the World Bank Treasury, and the European Bank for Reconstruction and Development. He has authored numerous papers, articles, and chapters in books on financial modelling, stochastic simulation, and optimization. He has also published a comprehensive book on fixed-income portfolio analytics. His career has focused on the application of mathematical techniques towards informing decision-making in the areas of sovereign-debt, pension-fund, portfolio-risk, and foreign-reserve management.



Von der hinteren Coverseite

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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
2018
Sprache
Englisch
ISBN 10 
3319946870
ISBN 13 
9783319946870
Einband
Gebundene Ausgabe
Auflage
1
Anzahl der Seiten
719
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland

Weitere beliebte Ausgaben desselben Titels

9783030069001: Credit-Risk Modelling: Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python

Vorgestellte Ausgabe

ISBN 10:  3030069001 ISBN 13:  9783030069001
Verlag: Springer, 2019
Softcover