We calculate the Hurst exponent H (t) of several time series by dynamical implementation of
a recently proposed scaling technique: the detrending moving average (DMA). In order to
assess the accuracy of the technique, we calculate the exponent H (t) for artificial series,
simulating monofractal Brownian paths, with assigned Hurst exponents H. We next calculate
the exponent H (t) for the return of high-frequency (tick-by-tick sampled every minute) series
of the German market. We find a much more pronounced time-variability in the local scaling …

We calculate the Hurst exponent H (t) of several time series by dynamical implementation of
a scaling technique: the detrending moving average (DMA). In order to assess the accuracy
of the technique, we calculate the exponent H (t) for artificial series, simulating monofractal
Brownian paths, with assigned Hurst exponents H. We next calculate the exponent H (t) for
the return of high-frequency (tick-by-tick sampled every minute) series of the Shanghai stock
market. We find a much more pronounced time-variability in the local scaling exponent of …