Determining anomalous dynamic patterns in price indexes of the London Metal Exchange by data synchronization

Abstract

Data synchronization based on the Kuramoto model for collective synchronization and hypothesis testing based on the rank test combined with the random shuffling surrogate method are applied to finding major feature patterns of weekly nonferrous metal returns from the time series of daily spot and futures price indexes in the London Metal Exchange since 1989. Our results suggest the existence of day-of-the-week anomalies in the metal returns. We conjecture that such anomalies are large-scale manifestations of synchronously accumulated risk-aversive actions of individual market players. © 2012 Elsevier B.V. All rights reserved.