LAUSR

Abstract In this paper we implemented the detrended multiple cross-correlation coefficient with sliding windows approach in order to measure multiple cross-correlation between time series as a function of time scale n , and a sliding time τ . Faced with several non-stationary time series, a fixed size window will be defined by w , and the coefficients D M C x 2 are calculated for different time scales ( 4 ≤ n ≤ w 4 ) and time τ . Following this methodology, it was possible to set up a D M C x 2 cross-correlation color map for a simulated (random) and an empirical case. This new color map with sliding windows shows the time scale and the current day for a cross-correlation analysis. In this way, it is possible to analyze the multiple cross-correlation between three or more variables in different areas of knowledge, such as economics and finance.