Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!iuvax!rutgers!orstcs!mist!harish
From: harish@mist.CS.ORST.EDU (Harish Pillay)
Newsgroups: comp.ai.neural-nets
Subject: How to simulate Foreign Exchange Rates
Summary: backpropagation, foreign exchange rates, simulation
Message-ID: <10198@orstcs.CS.ORST.EDU>
Date: 26 Apr 89 05:32:51 GMT
Sender: usenet@orstcs.CS.ORST.EDU
Reply-To: harish@guille.ECE.ORST.EDU (Harish Pillay)
Organization: Oregon State University, E&CE, Corvallis, Oregon 97331
Lines: 25

I am taking a grad course on NN and am planning on doing a project trying to
predict foreign exchange rates specifically the following:
   US$ vs British Pound vs Japanese Yen vs Singapore $ vs German Marks

I am using NeuralWorks and am thinking of using the backprop strategy.
So far, all I've done is to gather the exchange rates reported in the
WSJ from March 17 to today.  I've normalized it to be within 0 and 1
but my problem is in trying to train the network.  Has anyone out there
done anything similar to this?  If so, what desired output values did
you use to train?  I understand that it is naive to just take the rates
themselves and try to get a pattern or correlation.  Should I be looking
at other values too?  What kind of transfer function should I use?  I think
one hidden layer may be sufficient.

I would really appreciate any suggestions, and will post something once I
get this project done.

Thanks.

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Harish Pillay                                Internet: harish@ece.orst.edu
Electrical and Computer Engineering          MaBell: 503-758-1389 (home)
Oregon State University                              503-754-2554 (office)
Corvallis, OR 97331
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