Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model
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DOI: 10.1016/j.chaos.2023.113550
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- Mikkel Bennedsen & Asger Lunde & Mikko S Pakkanen, 2022. "Decoupling the Short- and Long-Term Behavior of Stochastic Volatility [Multifactor Approximation of Rough Volatility Models]," Journal of Financial Econometrics, Oxford University Press, vol. 20(5), pages 961-1006.
- S. Bianchi & A. Pantanella & A. Pianese, 2013. "Modeling stock prices by multifractional Brownian motion: an improved estimation of the pointwise regularity," Quantitative Finance, Taylor & Francis Journals, vol. 13(8), pages 1317-1330, July.
- Ayache, Antoine & Bouly, Florent, 2022. "Moving average Multifractional Processes with Random Exponent: Lower bounds for local oscillations," Stochastic Processes and their Applications, Elsevier, vol. 146(C), pages 143-163.
- Bolko, Anine E. & Christensen, Kim & Pakkanen, Mikko S. & Veliyev, Bezirgen, 2023.
"A GMM approach to estimate the roughness of stochastic volatility,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 745-778.
- Anine E. Bolko & Kim Christensen & Mikko S. Pakkanen & Bezirgen Veliyev, 2020. "A GMM approach to estimate the roughness of stochastic volatility," Papers 2010.04610, arXiv.org, revised Apr 2022.
- Qidi Peng & Ran Zhao, 2017. "A General Class of Multifractional Processes and Stock Price Informativeness," Papers 1708.04217, arXiv.org, revised Aug 2018.
- Sergio Bianchi, 2005. "Pathwise Identification Of The Memory Function Of Multifractional Brownian Motion With Application To Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 255-281.
- R'emy Chicheportiche & Jean-Philippe Bouchaud, 2012. "Weighted Kolmogorov-Smirnov test: Accounting for the tails," Papers 1207.7308, arXiv.org, revised Oct 2012.
- Giuseppe Brandi & T. Di Matteo, 2022. "Multiscaling and rough volatility: an empirical investigation," Papers 2201.10466, arXiv.org.
- Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
- Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
- Antoine Ayache & Jacques Vehel, 2000. "The Generalized Multifractional Brownian Motion," Statistical Inference for Stochastic Processes, Springer, vol. 3(1), pages 7-18, January.
- Cajueiro, Daniel O & Tabak, Benjamin M, 2004. "The Hurst exponent over time: testing the assertion that emerging markets are becoming more efficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 521-537.
- Albert Benassi & Pierre Bertrand & Serge Cohen & Jacques Istas, 2000. "Identification of the Hurst Index of a Step Fractional Brownian Motion," Statistical Inference for Stochastic Processes, Springer, vol. 3(1), pages 101-111, January.
- Raffaele Mattera & Fabrizio Di Sciorio & Juan E. Trinidad-Segovia & Sameh S. Askar, 2022. "A Composite Index for Measuring Stock Market Inefficiency," Complexity, Hindawi, vol. 2022, pages 1-13, January.
- Peng Yue & Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei-Xing Zhou, 2017. "Linear and nonlinear correlations in order aggressiveness of Chinese stocks," Papers 1707.05604, arXiv.org.
- Giulia Livieri & Saad Mouti & Andrea Pallavicini & Mathieu Rosenbaum, 2018.
"Rough volatility: Evidence from option prices,"
IISE Transactions, Taylor & Francis Journals, vol. 50(9), pages 767-776, September.
- Giulia Livieri & Saad Mouti & Andrea Pallavicini & Mathieu Rosenbaum, 2017. "Rough volatility: evidence from option prices," Papers 1702.02777, arXiv.org.
- T. Di Matteo, 2007. "Multi-scaling in finance," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 21-36.
- L. C. G. Rogers, 1997. "Arbitrage with Fractional Brownian Motion," Mathematical Finance, Wiley Blackwell, vol. 7(1), pages 95-105, January.
- Fabienne Comte & Eric Renault, 1998.
"Long memory in continuous‐time stochastic volatility models,"
Mathematical Finance, Wiley Blackwell, vol. 8(4), pages 291-323, October.
- Comte, F. & Renault, E., 1996. "Long Memory in Continuous Time Stochastic Volatility Models," Papers 96.406, Toulouse - GREMAQ.
- Li, Ming, 2020. "Multi-fractional generalized Cauchy process and its application to teletraffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
- Sergio Bianchi & Alexandre Pantanella & Augusto Pianese, 2015. "Efficient Markets And Behavioral Finance: A Comprehensive Multifractional Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 18(01n02), pages 1-29.
- Jim Gatheral & Thibault Jaisson & Mathieu Rosenbaum, 2018. "Volatility is rough," Quantitative Finance, Taylor & Francis Journals, vol. 18(6), pages 933-949, June.
- Loboda, Dennis & Mies, Fabian & Steland, Ansgar, 2021. "Regularity of multifractional moving average processes with random Hurst exponent," Stochastic Processes and their Applications, Elsevier, vol. 140(C), pages 21-48.
- S. Bianchi & A. Pianese, 2008. "Multifractional Properties Of Stock Indices Decomposed By Filtering Their Pointwise Hölder Regularity," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 567-595.
- Antoine Ayache, 2013. "Continuous Gaussian Multifractional Processes with Random Pointwise Hölder Regularity," Journal of Theoretical Probability, Springer, vol. 26(1), pages 72-93, March.
- Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
- Hu, Yaozhong & Nualart, David, 2010. "Parameter estimation for fractional Ornstein-Uhlenbeck processes," Statistics & Probability Letters, Elsevier, vol. 80(11-12), pages 1030-1038, June.
- Bianchi, Sergio, 2004. "A new distribution-based test of self-similarity," MPRA Paper 16640, University Library of Munich, Germany.
- Giuseppe Brandi & T. Di Matteo, 2022. "On the statistics of scaling exponents and the multiscaling value at risk," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1361-1382, October.
- Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
- Jean-François Coeurjolly, 2001. "Estimating the Parameters of a Fractional Brownian Motion by Discrete Variations of its Sample Paths," Statistical Inference for Stochastic Processes, Springer, vol. 4(2), pages 199-227, May.
- Masaaki Fukasawa & Tetsuya Takabatake & Rebecca Westphal, 2019. "Is Volatility Rough ?," Papers 1905.04852, arXiv.org, revised May 2019.
- Matthieu Garcin, 2019. "Fractal analysis of the multifractality of foreign exchange rates [Analyse fractale de la multifractalité des taux de change]," Working Papers hal-02283915, HAL.
- Masaaki Fukasawa, 2021. "Volatility has to be rough," Quantitative Finance, Taylor & Francis Journals, vol. 21(1), pages 1-8, January.
- Ayache, Antoine & Lévy Véhel, Jacques, 2004. "On the identification of the pointwise Hölder exponent of the generalized multifractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 111(1), pages 119-156, May.
- Peng, Qidi & Zhao, Ran, 2018. "A general class of multifractional processes and stock price informativeness," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 248-267.
- Matthieu Garcin, 2022. "Forecasting with fractional Brownian motion: a financial perspective," Quantitative Finance, Taylor & Francis Journals, vol. 22(8), pages 1495-1512, August.
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- Li, Yicun & Teng, Yuanyang, 2023. "Statistical inference in discretely observed fractional Ornstein–Uhlenbeck processes," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
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Keywords
Rough volatility; Fractional Ornstein–Uhlenbeck process; Multifractional process with random exponent; Hurst-Hölder exponent;All these keywords.
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