Online-Ressource | |
Verfasst von: | Aichinger, Michael [VerfasserIn] |
Titel: | A workout in computational finance |
Mitwirkende: | Binder, Andreas [MitwirkendeR] |
Verf.angabe: | Michael Aichinger, Andreas Binder. |
Verlagsort: | Chicester, West Sussex, United Kingdom |
Verlag: | John Wiley & Sons |
E-Jahr: | 2013 |
Jahr: | [2013] |
Umfang: | 1 online resource (1 volume) |
Illustrationen: | illustrations |
Fussnoten: | Includes bibliographical references and index. - Description based on online resource; title from title page (Safari, viewed January 21, 2015) |
ISBN: | 978-1-119-97191-7 |
1-119-97191-8 | |
Abstract: | 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. |
URL: | Aggregator: https://learning.oreilly.com/library/view/-/9781119971917/?ar |
Datenträger: | Online-Ressource |
Sprache: | eng |
Sach-SW: | Finance ; Mathematical models |
Electronic books | |
Electronic books ; local | |
K10plus-PPN: | 1680320378 |
Lokale URL UB: | Zum Volltext |
Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg | |
Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich | |
Bibliothek/Idn: | UW / m3609273895 |
Lokale URL Inst.: | Zum Volltext |