The multi-fractal model of asset returns: Its estimation via GMM and its use for volatility forecasting

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DETECTING MULTIFRACTAL PROPERTIES IN ASSET RETURNS: THE FAILURE OF THE "SCALING ESTIMATOR" (2004, methodology): “They also square well with the finding that the scaling estimates suffer from large biases and standard errors (Lux [20]; Yamasaki [22]).”
A multifractal approach for stock market inefficiency (2008, background): “Moreover, multifractal theoretical models were introduced [17–24] that take into account important aspects of price patterns (stylized facts), that other traditional models such as fractional Brownian motion and GARCH processes cannot.”
The Joint Distribution of Stock Returns is Not Elliptical (2010, unknown): “If we now choose σ = σ0e ξ with ξ ∼ N (0, s) (as suggested by advocates of multifractal models [3,28,35]), the resulting multivariate model defines the log-normal ensemble and the log-normal copula.”
Financial power laws: Empirical evidence, models, and mechanism (2016, background): “Implying exponential rather than hyperbolic decay of the volatility autocorrelations it nevertheless falls short of providing a stochastic process in accordance with the long memory property depicted in Eq.”