Robust Artificial Neural Networks for Pricing of European Options

Author： Andreou Panayiotis   Charalambous Chris   Martzoukos Spiros  

Publisher： Springer Publishing Company

ISSN： 0927-7099

Source： Computational Economics, Vol.27, Iss.2-3, 2006-05, pp. : 329-351

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Complexity of learning in artificial neural networks

By Engel A.  

Theoretical Computer Science, Vol. 265, Iss. 1, 2001-08 ,pp. : 285-306

Elsevier

Access to resources Recommend Favorite

Adaptive neural networks for robust estimation of signal parameters

By awek   Cichocki Andrzej  

COMPEL: Int J for Computation and Maths. in Electrical and Electronic Eng., Vol. 19, Iss. 3, 2000-03 ,pp. : 903-912

Emerald Group Publishing Ltd

Access to resources Recommend Favorite

Forecast Combination by Using Artificial Neural Networks

By Aladag Cagdas  

Neural Processing Letters, Vol. 32, Iss. 3, 2010-12 ,pp. : 269-276

Springer Publishing Company

Access to resources Recommend Favorite

Artificial neural networks to optimize the extrusion of an aluminium alloy

By Lucignano Carmine   Montanari Roberto   Tagliaferri Vincenzo   Ucciardello Nadia  

Journal of Intelligent Manufacturing, Vol. 21, Iss. 4, 2010-08 ,pp. : 569-574

Springer Publishing Company

Access to resources Recommend Favorite

Sigmoidal Function Classes for Feedforward Artificial Neural Networks

By Chandra Pravin  

Neural Processing Letters, Vol. 18, Iss. 3, 2003-12 ,pp. : 205-215

Springer Publishing Company

Access to resources Recommend Favorite