Numerical methods in finance
Author(s)
Bibliographic Information
Numerical methods in finance
(Publications of the Newton Institute)
Cambridge University Press, 2008
- : pbk
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Note
"First published 1997. This digitally printed version 2008"--T.p. verso
"Paperback re-issue"--Back cover
Includes bibliographical references
Description and Table of Contents
Description
Numerical Methods in Finance has emerged as a discipline at the intersection of probability theory, finance and numerical analysis. This book, based on lectures given at the Newton Institute as part of a broader programme, describes a wide variety of numerical methods used in financial analysis: computation of option prices, especially of American option prices, by finite difference and other methods; numerical solution of portfolio management strategies; statistical procedures; identification of models; Monte Carlo methods; and numerical implications of stochastic volatilities. Articles have been written in a pedagogic style and made reasonably self-contained, covering both mathematical matters and practical issues in numerical problems. Thus the book has something to offer economists, probabilists and applied mathematicians working in finance.
Table of Contents
- Introduction
- 1. Convergence of numerical schemes for degenerate parabolic equations arising in finance theory G. Barles
- 2. Continuous-time Monte Carlo methods and variance reduction Nigel J. Newton
- 3. Recent advances in numerical methods for pricing derivative securities M. Broad and J. Detemple
- 4. American options: a comparison of numerical methods F. AitSahlia and P. Carr
- 5. Fast, accurate and inelegant valuation of American options Adriaan Joubert and L. C. G. Rogers
- 6. Valuation of American options in a jump-diffusion model Xiao Lan Zhang
- 7. Some nonlinear methods for studying far-from-the-money contingent claims E. Fournie, J. M. Lasry and P.-L. Lions
- 8. Stochastic volatility models E. Fournie, J. M. Lasry and N. Touzi
- 9. Dynamic optimisation for a mixed portfolio with transaction costs Agnes Sulem
- 10. Imperfect markets and backward stochastic differential equations N. El Karoui and M. C. Quenez
- 11. Numerical methods for backward stochastic differential equations D. Chevance
- 12. Viscosity solutions and numerical schemes for investment/consumption models with transaction costs Agnes Tourin and Thaleia Zariphopoulou
- 13. Does volatility jump or just diffuse? A statistical approach Renzo G. Avesani and Pierre Bertrand
- 14. Martingale-based hedge error control Peter Bossaerts and Bas Werker
- 15. The use of second order stochastic dominance to bound European call prices: theory and results Claude Henin and Nathalie Pistre.
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