Introduction to Financial Derivatives with Python

Alos Elisa

ISBN 10: 1032211032 / ISBN 13: 9781032211039

Verlag: Chapman and Hall/CRC, 2022

Beschreibung

Bestandsnummer des Verkäufers 18395210023

Bibliografische Details

• Titel: Introduction to Financial Derivatives with Python
• Verlag: Chapman and Hall/CRC
• Erscheinungsjahr: 2022
• Sprache: Englisch
• ISBN-10: 1032211032
• ISBN-13: 9781032211039
• Einband: Hardcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

Introduction to Financial Derivatives with Python is an ideal textbook for an undergraduate course on derivatives, whether on a finance, economics, or financial mathematics programme. As well as covering all of the essential topics one would expect to be covered, the book also includes the basis of the numerical techniques most used in the financial industry, and their implementation in Python.

Features

• Connected to a Github repository with the codes in the book. The repository can be accessed at https://bit.ly/3bllnuf
• Suitable for undergraduate students, as well as anyone who wants a gentle introduction to the principles of quantitative finance
• No pre-requisites required for programming or advanced mathematics beyond basic calculus

Über die Autorin bzw. den Autor

Elisa Alòs holds a Ph.D. in Mathematics from the University of Barcelona. She is an Associate Professor in the Department of Economics and Business at Universitat Pompeu Fabra (UPF) and a Barcelona GSE Affiliated Professor. Her research focus has been on the applications of the Malliavin calculus and the fractional Brownian motion in mathematical finance and volatility modelling since he past fourteen years.

Raúl Merino has been working full-time in the industry as Risk Quant since 2008. He is also an Associate Professor at Pompeu Fabra University (UPF) where he teaches the course "Financial Derivatives and Risk Management". Raul holds a Ph.D. in Mathematics from the University of Barcelona. In his Ph.D. he studied the use of decomposition formulas in stochastic volatility models. His research interests are stochastic analysis and applied mathematics, with a special focus on applications to mathematical finance.