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Title:Closed form integration of artificial neural networks with some applications PDF Logo
Authors:Gottschling, Andreas
Haefke, Christian
White, Halbert
Issue Date:1999
Series/Report no.:Research notes in economics & statistics 99-9
Abstract:Many economic and econometric applications require the integration of functions lacking a closed form antiderivative, which is therefore a task that can only be solved by numerical methods. We propose a new family of probability densities that can be used as substitutes and have the property of closed form integrability. This is especially advantageous in cases where either the complexity of a problem makes numerical function evaluations very costly, or fast information extraction is required for time-varying environments. Our approach allows generally for nonparametric maximum likelihood density estimation and may thus find a variety of applications, two of which are illustrated briefly: Estimation of Value at Risk based on approximations to the density of stock returns; Recovering risk neutral densities for the valuation of options from the option price - strike price relation.
Subjects:Option Pricing
Neural Networks
Nonparametric Density Estimation
JEL:C45
G13
C63
Document Type:Working Paper
Appears in Collections:Research Notes, Deutsche Bank Research

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