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Hands-On Value-at-Risk and Expected Shortfall: A Practical Primer: Management for Professionals

Autor Martin Auer
en Limba Engleză Hardback – 12 feb 2018
This book describes a maximally simple market risk model that is still practical and main risk measures like the value-at-risk and the expected shortfall. It outlines the model's (i) underlying math, (ii) daily operation, and (iii) implementation, while stripping away statistical overhead to keep the concepts accessible. The author selects and weighs the various model features, motivating the choices under real-world constraints, and addresses the evermore important handling of regulatory requirements. The book targets not only practitioners new to the field but also experienced market risk operators by suggesting useful data analysis procedures and implementation details. It furthermore addresses market risk consumers such as managers, traders, and compliance officers by making the model behavior intuitively transparent.


A very useful guide to the theoretical and practical aspects of implementing and operating a risk-monitoring system for a mid-size financial institution. It sets a common body of knowledge to facilitate communication between risk managers, computer and investment specialists by bridging their diverse backgrounds.
Giovanni Barone-Adesi — Professor, Universitá della Svizzera italiana
 
This unassuming and insightful book starts from the basics and plainly brings the reader up to speed on both theory and implementation.
Shane Hegarty — Director Trade Floor Risk Management, Scotiabank
 
Visit the book’s website at www.value-at-risk.com.
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Specificații

ISBN-13: 9783319723198
ISBN-10: 3319723197
Pagini: 204
Ilustrații: XVIII, 169 p. 43 illus.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.44 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Management for Professionals

Locul publicării:Cham, Switzerland

Cuprins

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Part I MEASURES
3 Basic Terms and Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4 Historical Value-at-Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5 Sensitivities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
6 Stress Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
7 Analytical Value-at-Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
8 Expected Shortfall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
9 Model Choices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
10 A Monte Carlo Modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
11 Support Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Part II OPERATIONS
12 Properties of VaR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
13 Properties of ES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
14 VaR Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
15 Backtesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5
6 Contents
16 Distribution Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
17 Nine to Five . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Part III SETUP
18 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
19 Scope and Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
20 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
WRAP-UP
21 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
22 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
APPENDIX
A Statistics 101 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
B Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
C Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

Notă biografică

Martin Auer is senior consultant in the areas of quantitative finance, market and credit risk, and IT, working for the likes of Raiffeisen Bank International, Kommunalkredit, and T-Systems in Vienna, and for Bank of America in New York. He holds degrees in computer science, mathematics, and mathematics of finance from Vienna University of Technology, University of Vienna, and Columbia University. 


Textul de pe ultima copertă

This book describes a maximally simple market risk model that is still practical and main risk measures like the value-at-risk and the expected shortfall. It outlines the model's (i) underlying math, (ii) daily operation, and (iii) implementation, while stripping away statistical overhead to keep the concepts accessible. The author selects and weighs the various model features, motivating the choices under real-world constraints, and addresses the evermore important handling of regulatory requirements. The book targets not only practitioners new to the field but also experienced market risk operators by suggesting useful data analysis procedures and implementation details. It furthermore addresses market risk consumers such as managers, traders, and compliance officers by making the model behavior intuitively transparent.

Caracteristici

Avoids unnecessary formalism to allow for an intuitive understanding of the behavior of risk models and measures for an audience with varying quantitative backgrounds
Selects and weighs different models under real-world constraints to illustrate the simplest - yet still practical - model
Provides the required regulatory context to validate risk models and to ease communication between different stakeholders