文档介绍：An Intelligent Statistical Arbitrage Trading
System
Nikos S. Thomaidis1,, Nick Kondakis1,2, and e D. Dounias1
1 Decision and Management Engineering Laboratory,
Dept. of Financial Engineering & Management,
University of the Aegean, 31 Fostini Str., GR-821 00, Chios, Greece
Tel.: +30-2271-0-35454 (35483); Fax: +30-2271-0-35499
{nthomaid, kondakis, }***@
2 Kepler Asset Management, 100 Wall Street, New York, NY 10005
nick@
Abstract. This paper proposes an bination of -
work theory and financial statistical models for the detection of arbitrage
opportunities in a group of stocks. The proposed intelligent methodol-
ogy is based on a class of work-GARCH autoregressive models
for the effective handling of the dynamics related to the statistical mis-
pricing between relative stock prices. The performance of the proposed
intelligent trading system is properly measured with the aid of profit &
loss diagrams.
1 Introduction
Statistical arbitrage is an attempt to profit from price discrepancies that appear
in a group of assets. The detection of mispricings is based upon finding a linear
combination of assets, or else a “synthetic” asset, whose time series is mean-
reverting with finite variance. Given a set of assets X1,...,Xn,asyntheticisa
bination ω=(w1,w2, ..., wn) such that
··· ∼ 2 2 ∞
w1X1 + w2X2