Algorithmic trading using phase synchronization

Abstract

A novel trading algorithm which performs trading decisions by making use of phase synchronization between oscillatory components of asset pairs is proposed. This way the phase information ascertains a leading asset, which is then used to predict the lagging asset. The oscillatory components of asset pairs are identified using the Synchrosqueezed Transform (SST), which facilitates stable and online implementation. The performance of the proposed approach is compared with existing algorithms used extensively by traders, such as the moving average cross-over, and an extrapolation algorithm based upon the multichannel-least mean square (MLMS). © 2011 IEEE.