kalman filter for arbitrage id...

kalman filter for arbitrage identification in high frequency dataA ROBUST NON-LINEAR MULTIVARIATE KALMAN FILTER FOR ARBITRAGE IDENTIFICATION IN HIGH FREQUENCY DATA
P. J. BOLLAND AND J. T. CONNOR London Business School Department of Decision Science Sussex Place, Regents Park London NW1 4SA Phone -(+44) 71-262-5050 FAX - (+44) 71-724-7875 E-Mail - pbolland@lbs.lon.ac.uk E-Mail - jconnor@lbs.lon.ac.uk ABSTRACT We present a methodology for modelling real world high frequency financial data. The methodology copes with the erratic arrival of data and is robust to additive outliers in the data set. Arbitrage pricing relationships are formulated into a linear state space representation. Arbitrage opportunities violate these pricing relationships and are analogous to multivariate additive outliers. Robust identification/filtering of arbitrage opportunities in t