AbstractIn the framework of statistical time series analysis of complex dynamics, we present a multiscale characterization of solar wind turbulence in the near-earth environment. The data analysis, based on the Markov process theory, is meant to estimate the Kramers–Moyal coefficients associated with the measured magnetic field fluctuations. In fact, when the scale-to-scale dynamics can be successfully described as a Markov process, first- and second-order Kramers–Moyal coefficients provide a complete description of the dynamics in terms of Langevin stochastic process. The analysis is carried out using high-resolution magnetic field measurements gathered by Cluster during a fast solar wind period on January 20, 2007. This analysis extends recent findings in the near-Sun environment with the aim of testing the universality of the Markovian nature of the magnetic field fluctuations in the sub-ion/kinetic domain.