Pathwise Identification Of The Memory Function Of Multifractional Brownian Motion With Application To Finance

77 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics (2020, methodology): “Later, alternative estimation methods appeared, such as the detrended fluctuation analysis [64], or the absolute-moment method [8, 7, 9, 28], which is related to the notion of generalized Hurst exponent (GHE) [6, 21].”
Modeling stock prices by multifractional Brownian motion: an improved estimation of the pointwise regularity (2013, methodology): “Exploiting remark 3, Bianchi (2005) proposes a class of moving-window estimators of the functional parameter Ht.”
Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates (2017, methodology): “We compute the following statistic in a window of size εN ≤ N , for any given k ∈ N [9]:”