Buch, Englisch, Format (B × H): 155 mm x 235 mm
Reihe: Springer Series in Operations Research and Financial Engineering
Buch, Englisch, Format (B × H): 155 mm x 235 mm
Reihe: Springer Series in Operations Research and Financial Engineering
ISBN: 978-0-387-98954-9
Verlag: Springer-Verlag New York
This book will provide senior undergraduate and graduate students in the science and engineering disciplines with an understanding of the quantitative finance and investment management (FIM) business and illustrate how they can apply their quantitative skills in this area. The author having worked as a mathematical professor, systems engineer and an investment manager identifies interesting and important problems of FIM and brings to bear appropriate methods from the technical disciplines. One of the fundamental issues in the interplay between the theory and practice of FIM is a combination of model sensitivity with the lack of sufficient relevant data to accurately construct models. The markets are not stationery systems with some underlying natural law, so that model parameters are evolving and poorly estimated by historically remote data. Hence this book tries to outline the controversies of current models and offer alternate approaches where available.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
Weitere Infos & Material
Introduction * 2 Theory of Uncertainty 3 * Classical Portfolio Selection * 4 Advanced Portfolio Selection * 5 Primary Security Price Models in Discrete Time * 6 Primary Security Price Models in Continuous Time * 7 Parameter Estimation * 8 Preferences and Utilities * 9 Simulation in FIM * 10 Options for Financial Engineers * 11 Options for Managers and Traders * 12 Risk Assessment * 13 Capital Growth Models * 14 Linear Risk Factor Models * 15 Performance Evaluation * 16 Avant-Garde Topics
