On the identification of the pointwise Hölder exponent of the generalized multifractional Brownian motion

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Wavelet construction of Generalized Multifractional processes. (2007, background): “However, in many situations, such a modelling is not realistic because, the pointwise Hölder exponent of a fractal signal evolves in time, while that of FBM remains constant (see for instance [5, 9, 10, 20, 26, 30, 34, 35]).”
Estimators of Fractal Dimension: Assessing the Roughness of Time Series and Spatial Data (2011, methodology): “In this setting, the estimators considered in our paper can be used as building blocks for the more complex estimators needed to handle these nonstationary processes, as studied by Benassi, Cohen and Istas (1998), Ayache and Lévy Véhel (2004) and Coeurjolly (2005), among others.”
Modeling stock prices by multifractional Brownian motion: an improved estimation of the pointwise regularity (2013, unknown): “To identify the functional parameter of an even more general mBm (the generalized mBm), Ayache and Levy Vehel ( 2004 ) and Ayache et al.”