Digital contracts-driven method for pricing complex derivatives

Digital contracts-driven method for pricing complex derivatives

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Article ID: iaor20041635
Country: United Kingdom
Volume: 54
Issue: 9
Start Page Number: 1002
End Page Number: 1010
Publication Date: Sep 2003
Journal: Journal of the Operational Research Society
Authors: ,
Keywords: derivatives
Abstract:

In this paper, we propose a hybrid method of nonparametric and parametric methods, that is a digital contracts-driven (DCD) method, for pricing various complex options. Differing from general nonparametric data-driven methods, in which usually the observed data are used as training data directly, in the DCD method the European-style digital contracts of the underlying assets are used as basic inputs for a learning network. The digital contracts calculated from the observed data based upon the parametric method are used as hints in the learning process, and then enable the DCD method to have superior pricing accuracy to the common data-driven method in practical applications. Some Monte Carlo simulation experiments are performed and the results demonstrate that the proposed hybrid method not only has the advantages of generality and superior accuracy as the nonparametric method, but also the robust property to financial data with noise as the parametric method.

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