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A Multifractal Model of Asset Returns

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Cited by:

  1. Johann Lussange & Ivan Lazarevich & Sacha Bourgeois-Gironde & Stefano Palminteri & Boris Gutkin, 2021. "Modelling Stock Markets by Multi-agent Reinforcement Learning," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 113-147, January.
  2. St'ephane Goutte & Nadia Oudjane & Francesco Russo, 2013. "Variance optimal hedging for continuous time additive processes and applications," Papers 1302.1965, arXiv.org.
  3. Todd Zorick & Mark A Mandelkern, 2013. "Multifractal Detrended Fluctuation Analysis of Human EEG: Preliminary Investigation and Comparison with the Wavelet Transform Modulus Maxima Technique," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
  4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-059, New York University, Leonard N. Stern School of Business-.
  5. 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.
  6. Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2021. "High-Frequency Volatility Forecasting of US Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 62(2), pages 283-317, February.
  7. Lux, Thomas, 2022. "Inference for Nonlinear State Space Models: A Comparison of Different Methods applied to Markov-Switching Multifractal Models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 69-95.
  8. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2016. "Anomalous volatility scaling in high frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 434-445.
  9. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
  10. Lux, Thomas & Kaizoji, Taisei, 2007. "Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1808-1843, June.
  11. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
  12. Olkhov, Victor, 2018. "Expectations, Price Fluctuations and Lorenz Attractor," MPRA Paper 89105, University Library of Munich, Germany.
  13. Olkhov, Victor, 2019. "New Essentials of Economic Theory," MPRA Paper 95065, University Library of Munich, Germany.
  14. Arun Kumar & Palaniappan Vellaisamy, 2012. "Fractional Normal Inverse Gaussian Process," Methodology and Computing in Applied Probability, Springer, vol. 14(2), pages 263-283, June.
  15. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
  16. Timothy DeLise, 2021. "Neural Options Pricing," Papers 2105.13320, arXiv.org.
  17. Victor Olkhov, 2023. "Market-Based Probability of Stock Returns," Papers 2302.07935, arXiv.org, revised Feb 2024.
  18. Chuang, Wen-I & Huang, Teng-Ching & Lin, Bing-Huei, 2013. "Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 168-187.
  19. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
  20. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
  21. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
  22. Dong Liu & Mingjie Luo & Qiang Fu & Yongjia Zhang & Khan Imran & Dan Zhao & Tianxiao Li & Faiz Abrar, 2016. "Precipitation Complexity Measurement Using Multifractal Spectra Empirical Mode Decomposition Detrended Fluctuation Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 505-522, January.
  23. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
  24. Baldovin, Fulvio & Caporin, Massimiliano & Caraglio, Michele & Stella, Attilio L. & Zamparo, Marco, 2015. "Option pricing with non-Gaussian scaling and infinite-state switching volatility," Journal of Econometrics, Elsevier, vol. 187(2), pages 486-497.
  25. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
  26. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2020. "Fluctuation and volatility dynamics of stochastic interacting energy futures price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
  27. Thomas Theobald, 2015. "Agent-based risk management – a regulatory approach to financial markets," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 42(5), pages 780-820, October.
  28. Olkhov, Victor, 2022. "The Market-Based Asset Price Probability," MPRA Paper 113096, University Library of Munich, Germany.
  29. Andria, Joseph & di Tollo, Giacomo & Kalda, Jaan, 2022. "The predictive power of power-laws: An empirical time-arrow based investigation," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
  30. Patrice Abry & Yannick Malevergne & Herwig Wendt & Marc Senneret & Laurent Jaffrès & Blaise Liaustrat, 2019. "Shuffling for understanding multifractality, application to asset price time series," Post-Print hal-02361738, HAL.
  31. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Pawe{l} O'swic{e}cimka & Marek Stanuszek, 2018. "Multifractal cross-correlations between the World Oil and other Financial Markets in 2012-2017," Papers 1812.08548, arXiv.org, revised Jun 2019.
  32. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
  33. Tetsuya Takaishi, 2019. "Rough volatility of Bitcoin," Papers 1904.12346, arXiv.org.
  34. Aslam, Faheem & Aziz, Saqib & Nguyen, Duc Khuong & Mughal, Khurrum S. & Khan, Maaz, 2020. "On the efficiency of foreign exchange markets in times of the COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
  35. Lux, Thomas & Kaizoji, Taisei, 2004. "Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models," Economics Working Papers 2004-05, Christian-Albrechts-University of Kiel, Department of Economics.
  36. Zhou, Wei-Xing, 2012. "Finite-size effect and the components of multifractality in financial volatility," Chaos, Solitons & Fractals, Elsevier, vol. 45(2), pages 147-155.
  37. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
  38. Calvet, Laurent & Fisher, Adlai, 2001. "Forecasting multifractal volatility," Journal of Econometrics, Elsevier, vol. 105(1), pages 27-58, November.
  39. Rudy Morel & Gaspar Rochette & Roberto Leonarduzzi & Jean-Philippe Bouchaud & St'ephane Mallat, 2022. "Scale Dependencies and Self-Similar Models with Wavelet Scattering Spectra," Papers 2204.10177, arXiv.org, revised Jun 2023.
  40. Calvet, Laurent E. & Fisher, Adlai J., 2008. "Multifrequency jump-diffusions: An equilibrium approach," Journal of Mathematical Economics, Elsevier, vol. 44(2), pages 207-226, January.
  41. Arshad, Shaista & Rizvi, Syed Aun R. & Haroon, Omair, 2020. "Impact of Brexit vote on the London stock exchange: A sectorial analysis of its volatility and efficiency," Finance Research Letters, Elsevier, vol. 34(C).
  42. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
  43. Ruipeng Liu & Riza Demirer & Rangan Gupta & Mark Wohar, 2020. "Volatility forecasting with bivariate multifractal models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 155-167, March.
  44. Guo, Yaoqi & Shi, Fengyuan & Yu, Zhuling & Yao, Shanshan & Zhang, Hongwei, 2022. "Asymmetric multifractality in China’s energy market based on improved asymmetric multifractal cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
  45. Schadner, Wolfgang, 2022. "U.S. Politics from a multifractal perspective," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
  46. Phooi M’ng, Jacinta Chan, 2018. "Dynamically Adjustable Moving Average (AMA’) technical analysis indicator to forecast Asian Tigers’ futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 336-345.
  47. Lux, Thomas, 2008. "The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
  48. Thomas Lux, 2003. "The Multi-Fractal Model of Asset Returns:Its Estimation via GMM and Its Use for Volatility Forecasting," Computing in Economics and Finance 2003 14, Society for Computational Economics.
  49. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
  50. Jamdee, Sutthisit & Los, Cornelis A., 2007. "Long memory options: LM evidence and simulations," Research in International Business and Finance, Elsevier, vol. 21(2), pages 260-280, June.
  51. Dmitry Ostrovsky, 2007. "Constant Elasticity Of Variance In Random Time: A New Stochastic Volatility Model With Path Dependence And Leverage Effect," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(06), pages 915-937.
  52. Rypdal, Martin & Sirnes, Espen & Løvsletten, Ola & Rypdal, Kristoffer, 2013. "Assessing market uncertainty by means of a time-varying intermittency parameter for asset price fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3335-3343.
  53. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Casado Belmonte, M.P. & Trinidad Segovia, J.E., 2020. "A note on power-law cross-correlated processes," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
  54. Paul Eitelman & Justin Vitanza, 2008. "A non-random walk revisited: short- and long-term memory in asset prices," International Finance Discussion Papers 956, Board of Governors of the Federal Reserve System (U.S.).
  55. Brandi, Giuseppe & Di Matteo, T., 2022. "Multiscaling and rough volatility: An empirical investigation," International Review of Financial Analysis, Elsevier, vol. 84(C).
  56. Giuseppe Brandi & T. Di Matteo, 2020. "On the statistics of scaling exponents and the Multiscaling Value at Risk," Papers 2002.04164, arXiv.org, revised Mar 2021.
  57. Sansone, Alessandro & Garofalo, Giuseppe, 2007. "Asset price dynamics in a financial market with heterogeneous trading strategies and time delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 247-257.
  58. Caraiani, Petre & Haven, Emmanuel, 2015. "Evidence of multifractality from CEE exchange rates against Euro," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 395-407.
  59. Mulligan, Robert F., 2004. "Fractal analysis of highly volatile markets: an application to technology equities," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(1), pages 155-179, February.
  60. Wilhelm Berghorn & Sascha Otto, 2017. "Mandelbrot Market-Model and Momentum," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 8(3), pages 1-26, July.
  61. Mulligan, Robert F. & Lombardo, Gary A., 2004. "Maritime businesses: volatile stock prices and market valuation inefficiencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 321-336, May.
  62. Eric M. Aldrich & Indra Heckenbach & Gregory Laughlin, 2014. "The Random Walk of High Frequency Trading," Papers 1408.3650, arXiv.org, revised Aug 2014.
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  66. Pablo Su'arez-Garc'ia & David G'omez-Ullate, 2013. "Multifractality and long memory of a financial index," Papers 1306.0490, arXiv.org.
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  68. Onali, Enrico & Goddard, John, 2011. "Are European equity markets efficient? New evidence from fractal analysis," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 59-67, April.
  69. Olkhov, Victor, 2019. "New Essentials of Economic Theory III. Economic Applications," MPRA Paper 94053, University Library of Munich, Germany.
  70. Noemi Nava & T. Di Matteo & Tomaso Aste, 2015. "Anomalous volatility scaling in high frequency financial data," Papers 1503.08465, arXiv.org, revised Dec 2015.
  71. J. Lussange & A. Belianin & S. Bourgeois-Gironde & B. Gutkin, 2018. "A bright future for financial agent-based models," Papers 1801.08222, arXiv.org.
  72. Mensi, Walid & Hamdi, Atef & Shahzad, Syed Jawad Hussain & Shafiullah, Muhammad & Al-Yahyaee, Khamis Hamed, 2018. "Modeling cross-correlations and efficiency of Islamic and conventional banks from Saudi Arabia: Evidence from MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 576-589.
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