A Workout in Computational Finance
eBook - ePub

A Workout in Computational Finance

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

A Workout in Computational Finance

About this book

A comprehensive introduction to various numerical methods used in computational finance today

Quantitative skills are a prerequisite for anyone working in finance or beginning a career in the field, as well as risk managers. A thorough grounding in numerical methods is necessary, as is the ability to assess their quality, advantages, and limitations. This book offers a thorough introduction to each method, revealing the numerical traps that practitioners frequently fall into. Each method is referenced with practical, real-world examples in the areas of valuation, risk analysis, and calibration of specific financial instruments and models. It features a strong emphasis on robust schemes for the numerical treatment of problems within computational finance. Methods covered include PDE/PIDE using finite differences or finite elements, fast and stable solvers for sparse grid systems, stabilization and regularization techniques for inverse problems resulting from the calibration of financial models to market data, Monte Carlo and Quasi Monte Carlo techniques for simulating high dimensional systems, and local and global optimization tools to solve the minimization problem.

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Yes, you can access A Workout in Computational Finance by Andreas Binder,Michael Aichinger in PDF and/or ePUB format, as well as other popular books in Business & Corporate Finance. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2013
Print ISBN
9781119971917
eBook ISBN
9781119973492
Edition
1
Topic
Business
Subtopic
Corporate Finance
Index
Business

Table of contents

  1. Cover
  2. Series Page
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Acknowledgements
  7. About the Authors
  8. Chapter 1: Introduction and Reading Guide
  9. Chapter 2: Binomial Trees
  10. Chapter 3: Finite Differences and the Black-Scholes PDE
  11. Chapter 4: Mean Reversion and Trinomial Trees
  12. Chapter 5: Upwinding Techniques for Short Rate Models
  13. Chapter 6: Boundary, Terminal and Interface Conditions and their Influence
  14. Chapter 7: Finite Element Methods
  15. Chapter 8: Solving Systems of Linear Equations
  16. Chapter 9: Monte Carlo Simulation
  17. Chapter 10: Advanced Monte Carlo Techniques
  18. Chapter 11: Valuation of Financial Instruments with Embedded American/Bermudan Options within Monte Carlo Frameworks
  19. Chapter 12: Characteristic Function Methods for Option Pricing
  20. Chapter 13: Numerical Methods for the Solution of PIDEs
  21. Chapter 14: Copulas and the Pitfalls of Correlation
  22. Chapter 15: Parameter Calibration and Inverse Problems
  23. Chapter 16: Optimization Techniques
  24. Chapter 17: Risk Management
  25. Chapter 18: Quantitative Finance on Parallel Architectures
  26. Chapter 19: Building Large Software Systems for the Financial Industry
  27. Bibliography
  28. Index