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TITLE Pricing options with exponential Levy neural network
KIAS AUTHORS Huh, Jeonggyu
JOURNAL EXPERT SYSTEMS WITH APPLICATIONS, 2019
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ABSTRACT In this paper, we propose the exponential Levy neural network (ELNN) for option pricing, which is a new non-parametric exponential Levy model using artificial neural networks (ANN). The ELNN fully integrates the ANNs with the exponential Levy model, a conventional pricing model. So, the ELNN can improve ANN-based models to avoid several essential issues such as unacceptable outcomes and inconsistent pricing of over-the-counter products. Moreover, the ELNN is the first applicable non-parametric exponential Levy model by virtue of outstanding researches on optimization in the field of ANN. The existing non-parametric models are rather not robust for application in practice. The empirical tests with S&P 500 option prices show that the ELNN fits the data better than two parametric exp-Levy models and its estimates are less overfit than another network-based model. (C) 2019 Elsevier Ltd. All rights reserved.
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