A Workout in Computational Finance, with Website (The Wiley Finance Series) - Tapa dura

Acerca del autor

MICHAEL AICHINGER obtained his Ph.D. in Theoretical Physics from the Johannes Kepler University Linz with a thesis on numerical methods in density functional theory and their application to 2D finite electron systems. A mobility grant led him to the Texas A&M University (2003) and to the Helsinki University of Technology (2004). In 2007 Michael Aichinger joined the Industrial Mathematics Competence Center where he has been working as a senior researcher and consultant in the field of quantitative finance for the last five years. He also works for the Austrian Academy of Sciences at the Radon Institute for Computational and Applied Mathematics where he is involved in several industrial mathematics and computational physics projects. Michael has (co-) authored around 20 journal articles in the fields of computational physics and quantitative finance.

ANDREAS BINDER obtained his Ph.D. in Industrial Mathematics from the Johannes Kepler University Linz with a thesis on continuous casting of steel. A research grant led him to the Oxford Center for Industrial and Applied Mathematics, UK, in 1991, where he got in touch with mathematical finance for the first time. After some years being an assistant professor at the Industrial Mathematics Institute, in 1996, he left university and became managing director of MathConsult GmbH, where he heads also the Computational Finance Group. Andreas has authored two introductory books on mathematical finance and 25 journal articles in the fields of industrial mathematics and of mathematical finance.

De la contraportada

Quantitative skills are a prerequisite for anyone looking to work in the finance industry today. Within the industry, any risk professional who wants to collaborate with, or work in most front office departments needs a thorough grounding in numerical methods, and the ability to assess their quality, their advantages and their limitations.

A Workout in Computational Finance delivers a profound and hands-on account of numerical methods used in modern quantitative finance, covering valuation and risk analysis of financial instruments from vanilla bonds to complex structures. The presented algorithms include, amongst others, tree methods, finite differences and finite elements, efficient Monte Carlo methods and Fourier techniques. Local and global optimisation techniques as well as stabilising regularisation methods for model calibration are thoroughly analysed.

The authors originate from the fields of theoretical physics and industrial mathematics, respectively, and have spent their professional careers creating efficient software solutions for producing industries and for financial industries. This book develops algorithms from the ground up, thus giving the reader a sound overview of their relative strengths and weaknesses. It is aimed at practitioners in the financial industry, for whom this is key knowledge in order to achieve optimal results with available data. It also enables junior quants with an IT background to implement numerical algorithms that work right away.

A Workout in Computational Finance is accompanied by a range of worked-out examples available from www.unrisk.com/Workout.