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In this study, features of the financial returns of the PSI20index, related to market efficiency, are captured using wavelet-and entropy-based techniques. This characterization includes the following points. First, the detection of long memory, associated with low frequencies, and a global measure of the time series: the Hurst exponent estimated by several methods, including wavelets. Second, the degree of roughness, or regularity variation, associated with the Hölder exponent, fractaldoi:10.3390/e16052768 fatcat:zxla7le6hbbp7orjr24nrc4sne