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Fixed-Income Portfolio Analytics - A Practical Guide to Implementing, Monitoring and Understanding Fixed-Income Portfolios... Fixed-Income Portfolio Analytics - A Practical Guide to Implementing, Monitoring and Understanding Fixed-Income Portfolios (Hardcover, 2015 ed.)
David Jamieson Bolder
R3,429 Discovery Miles 34 290 Ships in 12 - 17 working days

The book offers a detailed, robust, and consistent framework for the joint consideration of portfolio exposure, risk, and performance across a wide range of underlying fixed-income instruments and risk factors. Through extensive use of practical examples, the author also highlights the necessary technical tools and the common pitfalls that arise when working in this area. Finally, the book discusses tools for testing the reasonableness of the key analytics to help build and maintain confidence for using these techniques in day-to-day decision making. This will be of keen interest to risk managers, analysts and asset managers responsible for fixed-income portfolios.

Modelling Economic Capital - Practical Credit-Risk Methodologies, Applications, and Implementation Details (Hardcover, 1st ed.... Modelling Economic Capital - Practical Credit-Risk Methodologies, Applications, and Implementation Details (Hardcover, 1st ed. 2022)
David Jamieson Bolder
R3,454 Discovery Miles 34 540 Ships in 12 - 17 working days

How might one determine if a financial institution is taking risk in a balanced and productive manner? A powerful tool to address this question is economic capital, which is a model-based measure of the amount of equity that an entity must hold to satisfactorily offset its risk-generating activities. This book, with a particular focus on the credit-risk dimension, pragmatically explores real-world economic-capital methodologies and applications. It begins with the thorny practical issues surrounding the construction of an (industrial-strength) credit-risk economic-capital model, defensibly determining its parameters, and ensuring its efficient implementation. It then broadens its gaze to examine various critical applications and extensions of economic capital; these include loan pricing, the computation of loan impairments, and stress testing. Along the way, typically working from first principles, various possible modelling choices and related concepts are examined. The end result is a useful reference for students and practitioners wishing to learn more about a centrally important financial-management device.

Modelling Economic Capital - Practical Credit-Risk Methodologies, Applications, and Implementation Details (1st ed. 2022):... Modelling Economic Capital - Practical Credit-Risk Methodologies, Applications, and Implementation Details (1st ed. 2022)
David Jamieson Bolder
R2,652 Discovery Miles 26 520 Ships in 10 - 15 working days

How might one determine if a financial institution is taking risk in a balanced and productive manner? A powerful tool to address this question is economic capital, which is a model-based measure of the amount of equity that an entity must hold to satisfactorily offset its risk-generating activities. This book, with a particular focus on the credit-risk dimension, pragmatically explores real-world economic-capital methodologies and applications. It begins with the thorny practical issues surrounding the construction of an (industrial-strength) credit-risk economic-capital model, defensibly determining its parameters, and ensuring its efficient implementation. It then broadens its gaze to examine various critical applications and extensions of economic capital; these include loan pricing, the computation of loan impairments, and stress testing. Along the way, typically working from first principles, various possible modelling choices and related concepts are examined. The end result is a useful reference for students and practitioners wishing to learn more about a centrally important financial-management device.

Credit-Risk Modelling - Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python... Credit-Risk Modelling - Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python (Paperback, Softcover reprint of the original 1st ed. 2018)
David Jamieson Bolder
R1,953 Discovery Miles 19 530 Ships in 10 - 15 working days

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.

Fixed-Income Portfolio Analytics - A Practical Guide to Implementing, Monitoring and Understanding Fixed-Income Portfolios... Fixed-Income Portfolio Analytics - A Practical Guide to Implementing, Monitoring and Understanding Fixed-Income Portfolios (Paperback, Softcover reprint of the original 1st ed. 2015)
David Jamieson Bolder
R1,968 Discovery Miles 19 680 Ships in 10 - 15 working days

The book offers a detailed, robust, and consistent framework for the joint consideration of portfolio exposure, risk, and performance across a wide range of underlying fixed-income instruments and risk factors. Through extensive use of practical examples, the author also highlights the necessary technical tools and the common pitfalls that arise when working in this area. Finally, the book discusses tools for testing the reasonableness of the key analytics to help build and maintain confidence for using these techniques in day-to-day decision making. This will be of keen interest to risk managers, analysts and asset managers responsible for fixed-income portfolios.

Credit-Risk Modelling - Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python... Credit-Risk Modelling - Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python (Hardcover, 1st ed. 2018)
David Jamieson Bolder
R2,348 R2,183 Discovery Miles 21 830 Save R165 (7%) Ships in 9 - 15 working days

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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