It is well known that conventional option pricing models have systematic, statistically and economically significant errors or residuals. In this work an artificial neural network (ANN), which estimates the residuals from the most accurate conventional option pricing model, so as to improve option pricing accuracy, is constrained in such a way so that pricing must be rational at the option-pricing boundaries. These constraints lead to statistically and economically significant out-performance relative to both the most accurate conventional and non-constrained ANN option pricing models. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Lajbcygier, P. (2003). Option pricing with the product constrained hybrid neural network. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2714, 615–621. https://doi.org/10.1007/3-540-44989-2_73
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