Jorge Caiado and João Bastos to be published in the ISI-listed international finance journal, Quantitative Finance:
BASTOS, J. A. e CAIADO, J. (2012). Clustering financial time series with variance ratio statistics, Quantitative Finance, Taylor & Francis.
|Jorge Caiado (PhD) is Assistant Professor at ISEG and a researcher at the Centre for Applied Mathematics and Economics|
João Bastos (PhD) is Adjunct Assistant Professor at ISEG and a researcher at the
This study introduces a new distance measure for clustering financial time series based on variance ratio test statistics. The proposed metric attempts to assess the level of interdependence of time series from the point of view of return predictability. Simulation results show that this metric aggregates better time series according to their serial dependence structure than a metric based on the sample autocorrelations. An empirical application of this approach to international stock market returns is presented. The results suggest that this metric discriminates reasonably well stock markets according to size and level of development. Furthermore, despite the substantial evolution of individual variance ratio statistics, the clustering pattern remains fairly stable across different time periods.