Mathematical Finance Deterministic and Stochastic Models

by Janssen, Jacques; Manca, Raimondo; Volpe, Ernesto

• ISBN13: 9781848210813
• ISBN10: 1848210817
• Edition: 1st
• Format: Hardcover
• Copyright: 2009-03-03
• Publisher: Wiley-ISTE

Summary

This book provides a detailed study of Financial Mathematics. In addition to the extraordinary depth the book provides, it offers a study of the axiomatic approach that is ideally suited for analyzing financial problems. This book is addressed to MBA's, Financial Engineers, Applied Mathematicians, Banks, Insurance Companies, and Students of Business School, of Economics, of Applied Mathematics, of Financial Engineering, Banks, and more.

Author Biography

Jacques Janssen is Honorary Professor at the Solvay Business School in Brussels, Belgium. He has previously taught at EURIA and been a director of Jacan Insurance and Finance Services, a consultancy and training company.

Raimondo Manca is professor of mathematical methods applied to economics, finance and actuarial science at University of Rome "La Sapienza" in Italy. He is associate editor for the journal Methodology and Computing in Applied Probability. His main research interests are multidimensional linear algebra, computational probability, application of stochastic processes to economics, finance and insurance and simulation models.

Table of Contents

Preface  xvii

Part I. Deterministic Models 1

Chapter 1. Introductory Elements to Financial Mathematics 3

Chapter 2. Theory of Financial Laws 13

Chapter 3. Uniform Regimes in Financial Practice 41

Chapter 4. Financial Operations and their Evaluation: Decisional Criteria 91

Chapter 5. Annuities-Certain and their Value at Fixed Rate 147

Chapter 6. Loan Amortization and Funding Methods 211

Chapter 7. Exchanges and Prices on the Financial Market 289

Chapter 8. Annuities, Amortizations and Funding in the Case of Term Structures 331

Chapter 9. Time and Variability Indicators, Classical Immunization 363

Part II. Stochastic Models 409

Chapter 10. Basic Probabilistic Tools for Finance 411

Chapter 11. Markov Chains 457

Chapter 12. Semi-Markov Processes  481

Chapter 13. Stochastic or Itô Calculus 517

Chapter 14. Option Theory 553

Chapter 15. Markov and Semi-Markov Option Models 607

Chapter 16. Interest Rate Stochastic Models – Application to the Bond Pricing Problem 641

Chapter 17. Portfolio Theory 687

Chapter 18. Value at Risk (VaR) Methods and Simulation 703

Chapter 19. Credit Risk or Default Risk 743

Chapter 20. Markov and Semi-Markov Reward Processes and Stochastic Annuities 791

References 831

Index 839