From rough to multifractal volatility: The log S-fBM model-Reference-Cited by-同舟云学术

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From rough to multifractal volatility: The log S-fBM model

Published:2022-10 Issue: Volume:604 Page:127919
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Wu Peng^ORCID,Muzy Jean-François,Bacry Emmanuel

Funder

Agence Nationale de la Recherche

Publisher

Elsevier BV

Subject

Statistical and Nonlinear Physics,Statistics and Probability

Reference30 articles.

1. Volatility is rough;Gatheral;Quant. Finance,2018

2. Semiparametric estimation and inference on the fractal index of Gaussian and conditionally Gaussian time series data;Bennedsen;Econometric Rev.,2020

3. Decoupling the short- and long-term behavior of stochastic volatility;Bennedsen;J. Financ. Econom.,2021

4. Rough volatility: Evidence from option prices;Livieri;IISE Trans.,2018

5. Pricing under rough volatility;Bayer;Quant. Finance,2016

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1. Forecasting volatility with machine learning and rough volatility: example from the crypto-winter;Digital Finance;2024-03-24

2. Rough volatility via the Lamperti transform;Communications in Nonlinear Science and Numerical Simulation;2023-12

3. Minimal model of diffusion with time changing Hurst exponent;Journal of Physics A: Mathematical and Theoretical;2023-08-10

4. Multivariate quadratic Hawkes processes—part I: theoretical analysis;Quantitative Finance;2023-03-07

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