Xva Analysis

Probabilistic, Risk Measure, and Machine Learning Issues
1. Auflage 2025
ISBN: 978-1-041-01420-1
Verlag: CRC Press

Buch, Englisch, 456 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 449 g

Reihe: Chapman and Hall/CRC Financial Mathematics Series

XVA Analysis: Probabilistic, Risk Measure, and Machine Learning Issues offers readers an up-to-date and comprehensive exploration of the X-Value Adjustment (XVA) universe and of the embedded risk measure issues inherent within it.

Zielgruppe

Postgraduate

Autoren/Hrsg.

Crépey, Stéphane

Fachgebiete

• Mathematik | Informatik Mathematik Mathematische Analysis
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

Foreword List of Figures List of Tables List of Algorithms Preface Part INTRODUCTION Chapter 0 The Sustainable Black-Scholes Equations Part PRICING Chapter I XVA Analysis From the Balance Sheet Chapter II The Cost-of-Capital XVA Approach in Continuous Time Chapter III Cash Flows Arithmetics Part NUMERICAL METHODS Chapter IV Generalities Chapter V Pathwise CVA Regressions With Oversimulated Defaults Chapter VI CVA Sensitivities, Hedging and Risk Chapter VII Regressing Pathwise FVA, Economic Capital, and KVA Part RISK Chapter VIII Derivatives’ Risks as Costs in a One-Period Setup Chapter IX Resolving a Clearing Member’s Default by Equilibrium Chapter X Quantitative Reverse Stress Testing, Bottom Up Part HVA IS WORTH A DETOUR Chapter XI Hedging Valuation Adjustment and Model Risk Bibliography Index Acknowledgments Author Bio

Über Autor(innen)

Stéphane Crépey is a professor at the mathematics department of Univ Evry, Université Paris-Saclay, in charge of the probability and finance group and of the quantitative finance master 2 program.