Extension of the lognormal multifractal limit theorem

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Let MM be the lognormal multifractal random measure with parameter γ2\gamma^2, and let the extended singular integral be defined, for x∈[0,1]x\in[0,1] and continuous ff, by

∫01(τ∣t−x∣)+γ2f(t)M(dt)=lim⁡η→0∫t∈[0,1]; ∣t−x∣>η(τ∣t−x∣)+γ2f(t)M(dt).\int_0^1 \left(\frac{\tau}{|t-x|}\right)_+^{\gamma^2}f(t)M(dt)=\lim_{\eta\to0}\int_{t\in[0,1];\,|t-x|>\eta}\left(\frac{\tau}{|t-x|}\right)_+^{\gamma^2}f(t)M(dt).

Let μz2\mu_z^2 and KzK_z denote the unique constant and bounded function characterized by the limiting equations of Theorem 3, and let υ\upsilon be the probability measure whose Stieltjes transform is μz2\mu_z^2. Extension conjecture. Theorem 3 should hold in the lognormal multifractal case for all γ2∈[0,2[\gamma^2\in[0,2[, and the limiting equations should be obtained from those of the regularized theorem with 2W=ωϵ2W=\omega_\epsilon as ϵ→0\epsilon\to0.

This would extend the main limiting characterization beyond the small-intermittency range required by the paper's proofs, using the extended definition of the singular integral.

References

Primary source

Romain Allez, Rémi Rhodes and Vincent Vargas, “Marchenko Pastur type theorem for independent MRW processes: convergence of the empirical spectral measure”, arXiv:1106.5891 (2012).

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