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

14 Pages Posted: 15 Jan 2012 Last revised: 24 Jan 2012

See all articles by Nikolaos S. Thomaidis

Nikolaos S. Thomaidis

School of Economics, Aristotle University of Thessaloniki

Nick Kondakis

NGSQ International, Ltd

Date Written: 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.

Suggested Citation

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

Nikolaos S. Thomaidis (Contact Author)

School of Economics, Aristotle University of Thessaloniki

OPE building, University Campus
Thessaloniki, 54124
Greece

Nicholas Kondakis

NGSQ International, Ltd ( email )

Hauppauge, NY
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
835
rank
27,333
Abstract Views
2,636
PlumX Metrics