Paper on closed form integration of ANN
chaefke@ucsd.edu
chaefke at ucsd.edu
Sun Feb 27 22:20:16 EST 2000
Dear colleagues,
You can find the paper
"Closed Form Integration of Artificial Neural Networks With Some
Applications to Finance"
by Andy Gottschling, Christian Haefke and Halbert White
at my webpage:
http://weber.ucsd.edu/~chaefke/papers/Annint_chaefke.ps.gz
or
http://weber.ucsd.edu/~chaefke/papers/Annint_chaefke.pdf
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.
Keywords: Option Pricing, Neural Networks, Nonparametric Density
Estimation, Hypergeometric Functions;
The paper prints out to 35 pages,
Filesize is 150K for the gzipped version and 350K for the pdf file.
Comments are highly appreciated.
Best regards,
Christian
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* Christian Haefke INTERNET: chaefke at weber.ucsd.edu *
* University of California, San Diego *
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