C.A. Zapart (UK)
Artificial Intelligence Applications, Genetic Algorithms,
Neural Networks, Optimization, Time Series Analysis,
The paper presents results of simulated long-short equity
pairs trading with optimised static and dynamic wavelet
correlation models. The models trade using a set of twenty
five major capitalisation stocks from the sector "Materials".
Wavelet correlation models are optimised with help of arti
ficial neural networks and genetic algorithms. Trading sim
ulations show that models are able to make consistent prof
its during rising and falling markets even when a typical
established long-short arbitrage strategy remains flat.