Abstract

http://ssrn.com/abstract=1984252
 
 

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Detecting Statistical Arbitrage Opportunities Using a Combined Neural Network - GARCH Model


Nikos S. Thomaidis


University of the Aegean - Department of Financial Engineering & Management - Decision & Management Engineering Laboratory

Nick Kondakis


NGSQ International, Ltd

January 12, 2012


Abstract:     
This paper proposes a hybrid computational intelligent system for the detection of statistical arbitrage opportunities in pairs of assets. The proposed methodology combines nonlinear neural network autoregressive models with GARCH parametrizations of volatility for describing the dynamics of the correction of relative mispricings. First results from this approach seem encouraging; further experimentation on the optimal sampling frequency, the forecasting horizon and the points of entry and exit is conducted, in order to improve the economic value when transaction costs are taken into account.

Number of Pages in PDF File: 14

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Date posted: January 15, 2012 ; Last revised: January 24, 2012

Suggested Citation

Thomaidis, Nikos S. and Kondakis, Nick, Detecting Statistical Arbitrage Opportunities Using a Combined Neural Network - GARCH Model (January 12, 2012). Available at SSRN: http://ssrn.com/abstract=1984252 or http://dx.doi.org/10.2139/ssrn.1984252

Contact Information

Nikos S. Thomaidis (Contact Author)
University of the Aegean - Department of Financial Engineering & Management - Decision & Management Engineering Laboratory ( email )
8 Michalon Str
Chios, GR 82 100
Greece
30-2271-0-35483 (Phone)
30-2271-0-35499 (Fax)
HOME PAGE: http://decision.fme.aegean.gr
Nicholas Kondakis
NGSQ International, Ltd ( email )
Hauppauge, NY
United States
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