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10 computational challenges in finance

: Desmettre, Sascha; Korn, Ralf


Schryver, Christian de:
FPGA based accelerators for financial applications
Cham: Springer International Publishing, 2015
ISBN: 978-3-319-15406-0 (Print)
ISBN: 978-3-319-15407-7 (Online)
ISBN: 3-319-15407-9
Aufsatz in Buch
Fraunhofer ITWM ()

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.