v2 Version of Research Paper on Multiscale Sources of the rBergomi Model Released
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Giuseppe Brandi and Tiziana Di Matteo released v2 of their research paper on the sources of multiscaling in the rough Bergomi (rBergomi) model, proposing a two-stage statistical testing procedure that validates result robustness through permutation surrogates, combined multifractal random walks, and fractional Lévy stable motion synthetic processes. The study concludes that multiscaling in the rBergomi model primarily originates from heavy-tailed return distributions, rather than memory effects arising from the roughness of volatility paths.
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- arXiv q-finMultiscaling in the Rough Bergomi Model: A Tale of Tails
An arXiv quantitative finance paper investigates the source of multiscaling behavior in the rough Bergomi (rBergomi) model. It proposes a two-stage statistical testing procedure that uses shuffled surrogates preserving the return distribution while destroying temporal correlations, combined with synthetic processes such as multifractal random walks and fractional Lévy stable motions, to verify robustness. The study finds that multiscaling in the model mainly arises from the heavy-tailed return distribution rather than memory effects induced by the roughness of the volatility path.
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