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2015 | OriginalPaper | Chapter

1. 10 Computational Challenges in Finance

Authors : Sascha Desmettre, Ralf Korn

Published in: FPGA Based Accelerators for Financial Applications

Publisher: Springer International Publishing

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Abstract

With the growing use of both highly developed mathematical models and complicated derivative products at financial markets, the demand for high computational power and its efficient use via fast algorithms and sophisticated hard- and software concepts became a hot topic in mathematics and computer science. The combination of the necessity to use numerical methods such as Monte Carlo simulation, of the demand for a high accuracy of the resulting prices and risk measures, of online availability of prices, and the need for repeatedly performing those calculations for different input parameters as a kind of sensitivity analysis emphasizes this even more. In this survey, we describe the mathematical background of some of the most challenging computational tasks in financial mathematics. Among the examples are the pricing of exotic options by Monte Carlo methods, the calibration problem to obtain the input parameters for financial market models, and various risk management and measurement tasks.

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next chapter From Model to Application: Calibration to Market Data
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Metadata
Title
10 Computational Challenges in Finance
Authors
Sascha Desmettre
Ralf Korn
Copyright Year
2015
Book
FPGA Based Accelerators for Financial Applications

Print ISBN: 978-3-319-15406-0

Electronic ISBN: 978-3-319-15407-7

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-15407-7_1