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Callable Swaps, Snowballs, and Videogames: Wilmott Magazine Article
Claudio Albanese 735 Views

Although economically more meaningful than the alternatives, short rate models have been dismissed for financial engineering applications in favor of market models as the latter are more flexible and best suited to cluster computing implementations.

In this paper, we argue that the paradigm shift toward GPU architectures currently taking place in the high performance computing world can potentially change the situation and tilt the balance back in favor of a new generation of short rate models.


Software issues in wavelet analysis of financial data: Finance Focus lecture
Robert Tong - NAG Ltd 15240 Views

Wavelet Multiresolution Analysis (WMA) is a technique that is widely applied in many areas of data processing, including financial time series. By revealing the structure of the data at multiple scales, the results of WMA can be used to challenge or confirm underlying assumptions of market models. In many cases, the software used to compute the analysis will have been provided by a third party. The requirements this imposes on the design and implementation of such software are examined, together with possible limitations which need to be taken into account by the user. An important consideration is the desirability for consistent output to be produced by different implementations of the wavelet algorithms, to enable valid comparisons to be made. The needs of users to choose an appropriate wavelet basis and produce results relevant to their application must be translated into efficient software in terms of scalability and the pre- and post-processing of data sets. These issues are illustrated with reference to applications such as Foreign Exchange pricing.

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