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An Intelligent Statistical Arbitrage Trading System

  • Nikos S. Thomaidis
  • Nick Kondakis
  • George D. Dounias
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3955)

Abstract

This paper proposes an intelligent combination of neural network theory and financial statistical models for the detection of arbitrage opportunities in a group of stocks. The proposed intelligent methodology is based on a class of neural network-GARCH autoregressive models for the effective handling of the dynamics related to the statistical mispricing between relative stock prices. The performance of the proposed intelligent trading system is properly measured with the aid of profit & loss diagrams.

Keywords

Trading System Statistical Arbitrage Arbitrage Opportunity Equity Index Index Future 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nikos S. Thomaidis
    • 1
  • Nick Kondakis
    • 1
    • 2
  • George D. Dounias
    • 1
  1. 1.Decision and Management Engineering Laboratory, Dept. of Financial Engineering & ManagementUniversity of the AegeanChiosGreece
  2. 2.Kepler Asset ManagementNew YorkUSA

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