Comparison of stationary time series using distribution-free methods

In this paper we propose distribution-free procedures based on the moving blocks bootstrap for differentiating between two stationary time series that are not necessarily independent. A chi-square type statistic and a KolmogorovSmimov type statistic, each of which are based on the differences between the autocorrelations and the differences between the partial autocorrelations of the two series, are constructed. Monte Carlo studies carried out to assess the tests, show that they perform reasonably well. The tests are applied to real financial time series