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Benoît B. Mandelbrot
(Benoit B. Mandelbrot)

(deceased)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Benoit B. Mandelbrot, 2000. "Cartoons of the Variation of Financial Prices and of Brownian Motions in Multifractal Time," Cowles Foundation Discussion Papers 1256, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Djahoué Mangblé Gérald, 2018. "Estimating and Forecasting West Africa Stock Market Volatility Using Asymmetric GARCH Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(6), pages 1-4.

  2. Benoit Mandelbrot, 1999. "Survey of Multifractality in Finance," Cowles Foundation Discussion Papers 1238, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. 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.
    2. Li, Jiang-Cheng & Tang, Nian-Sheng & Mei, Dong-Cheng & Li, Yun-Xian & Zhang, Wan, 2016. "The trading time risks of stock investment in stock price drop," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 778-787.
    3. Alexandros Leontitsis & Constantinos E. Vorlow, 2005. "Accounting for outliers and calendar effects in surrogate simulations of stock return sequences," Papers physics/0504187, arXiv.org.
    4. Federico Maglione, 2015. "Multifractality in Finance: A deep understanding and review of Mandelbrot's MMAR," Working Papers 2015:05, Department of Economics, University of Venice "Ca' Foscari".
    5. Dong Liu & Mingjie Luo & Qiang Fu & Yongjia Zhang & Khan M. Imran & Dan Zhao & Tianxiao Li & Faiz M. 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.
    6. Traversaro, Francisco & Redelico, Francisco O., 2018. "Characterization of autoregressive processes using entropic quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 13-23.

  3. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.

    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. Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
    3. St'ephane Goutte & Nadia Oudjane & Francesco Russo, 2013. "Variance optimal hedging for continuous time additive processes and applications," Papers 1302.1965, arXiv.org.
    4. Corsi, Fulvio & Kretschmer, Uta & Mittnik, Stefan & Pigorsch, Christian, 2005. "The volatility of realized volatility," CFS Working Paper Series 2005/33, Center for Financial Studies (CFS).
    5. 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.
    6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    7. Giuseppe Brandi & T. Di Matteo, 2022. "Multiscaling and rough volatility: an empirical investigation," Papers 2201.10466, arXiv.org.
    8. 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.
    9. Rosser, J. Jr. & Ahmed, Ehsan & Hartmann, Georg C., 2003. "Volatility via social flaring," Journal of Economic Behavior & Organization, Elsevier, vol. 50(1), pages 77-87, January.
    10. Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019. "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers 201977, University of Pretoria, Department of Economics.
    11. Samet Günay, 2016. "Performance of the Multifractal Model of Asset Returns (MMAR): Evidence from Emerging Stock Markets," IJFS, MDPI, vol. 4(2), pages 1-17, May.
    12. 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.
    13. Laurent-Emmanuel Calvet & Adlai J. Fisher, 2008. "Multifrequency jump-diffusions: An equilibrium approach," Post-Print hal-00459681, HAL.
    14. 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.
    15. 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.
    16. Yufang Liu & Weiguo Zhang & Junhui Fu & Xiang Wu, 2020. "Multifractal Analysis of Realized Volatilities in Chinese Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 319-336, August.
    17. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
    18. M. Rypdal & O. L{o}vsletten, 2011. "Multifractal modeling of short-term interest rates," Papers 1111.5265, arXiv.org.
    19. Jiang, Jiaqi & Gu, Rongbao, 2016. "Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 254-264.
    20. Mandelbrot, Benoit B., 1999. "Renormalization and fixed points in finance, since 1962," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 263(1), pages 477-487.
    21. Grahovac, Danijel, 2020. "Multifractal processes: Definition, properties and new examples," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    22. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    23. Faheem Aslam & Wahbeeah Mohti & Paulo Ferreira, 2020. "Evidence of Intraday Multifractality in European Stock Markets during the Recent Coronavirus (COVID-19) Outbreak," IJFS, MDPI, vol. 8(2), pages 1-13, May.
    24. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.
    25. Pier Paolo Peirano & Damien Challet, 2012. "Baldovin-Stella stochastic volatility process and Wiener process mixtures," Post-Print hal-00734355, HAL.
    26. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    27. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.
    28. 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.
    29. Olkhov, Victor, 2018. "Expectations, Price Fluctuations and Lorenz Attractor," MPRA Paper 89105, University Library of Munich, Germany.
    30. Olkhov, Victor, 2019. "New Essentials of Economic Theory," MPRA Paper 95065, University Library of Munich, Germany.
    31. Arun Kumar & Palaniappan Vellaisamy, 2012. "Fractional Normal Inverse Gaussian Process," Methodology and Computing in Applied Probability, Springer, vol. 14(2), pages 263-283, June.
    32. Halbleib, Roxana & Dimitriadis, Timo, 2019. "How informative is high-frequency data for tail risk estimation and forecasting? An intrinsic time perspectice," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203669, Verein für Socialpolitik / German Economic Association.
    33. 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).
    34. Dmitry Ostrovsky, 2007. "Black–Scholes–Merton In Random Time: A New Stochastic Volatility Model With Path Dependence," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(05), pages 847-872.
    35. Timothy DeLise, 2021. "Neural Options Pricing," Papers 2105.13320, arXiv.org.
    36. Olkhov, Victor, 2023. "The Market-Based Probability of Stock Returns," MPRA Paper 116234, University Library of Munich, Germany.
    37. Benoit B. Mandelbrot, 2005. "Parallel cartoons of fractal models of finance," Annals of Finance, Springer, vol. 1(2), pages 179-192, October.
    38. Plamen Ch Ivanov & Ainslie Yuen & Pandelis Perakakis, 2014. "Impact of Stock Market Structure on Intertrade Time and Price Dynamics," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    39. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    40. 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.
    41. Emrah BALKAN & Umut UYAR, 2022. "The Fractal Structure of CDS Spreads: Evidence from the OECD Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 106-121, April.
    42. Bertrand B. Maillet & Thierry L. Michel, 2005. "The Impact of the 9/11 Events on the American and French Stock Markets," Review of International Economics, Wiley Blackwell, vol. 13(3), pages 597-611, August.
    43. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
    44. Laurent Calvet, 2000. "Forecasting Multifractal Volatility," Harvard Institute of Economic Research Working Papers 1902, Harvard - Institute of Economic Research.
    45. 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.
    46. Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," CQE Working Papers 6117, Center for Quantitative Economics (CQE), University of Muenster.
    47. 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.
    48. Paul Hager & Eyal Neuman, 2020. "The Multiplicative Chaos of $H=0$ Fractional Brownian Fields," Papers 2008.01385, arXiv.org.
    49. Mansfield, Peter, 1999. "GARCH in question ... and as a benchmark," International Review of Financial Analysis, Elsevier, vol. 8(1), pages 1-20.
    50. Krenar Avdulaj & Ladislav Kristoufek, 2020. "On Tail Dependence and Multifractality," Mathematics, MDPI, vol. 8(10), pages 1-13, October.
    51. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    52. E. Bacry & A. Kozhemyak & J. F. Muzy, 2011. "Log-normal continuous cascade model of asset returns: aggregation properties and estimation," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 795-818, October.
    53. 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).
    54. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    55. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW Kiel).
    56. 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.
    57. 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.
    58. 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.
    59. Patrice Abry & Yannick Malevergne & Herwig Wendt & Stéphane Jaffard & Marc Senneret & Laurent Jaffrès, 2022. "Foreign Exchange Multivariate Multifractal Analysis," Post-Print hal-03735497, HAL.
    60. Giuseppe Garofalo & Alessandro Sansone, 2006. "Asset Price Dynamics in a Financial Market with Heterogeneous Trading Strategies and Time Delays," Papers physics/0607276, arXiv.org.
    61. 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.
    62. Martin Rypdal & Espen Sirnes & Ola L{o}vsletten & Kristoffer Rypdal, 2012. "Assessing market uncertainty by means of a time-varying intermittency parameter for asset price fluctuations," Papers 1202.4877, arXiv.org.
    63. 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.
    64. Gao, Jiti, 2002. "Modeling long-range dependent Gaussian processes with application in continuous-time financial models," MPRA Paper 11973, University Library of Munich, Germany, revised 18 Sep 2003.
    65. Sutthisit Jamdee & Cornelis A. Los, 2005. "Multifractal Modeling of the US Treasury Term Structure and Fed Funds Rate," Finance 0502021, University Library of Munich, Germany.
    66. John Goddard & Enrico Onali, 2014. "Self-affinity in financial asset returns," Papers 1401.7170, arXiv.org.
    67. Cornelis A. Los & Rossitsa M. Yalamova, 2004. "Multi-Fractal Spectral Analysis of the 1987 Stock Market Crash," Finance 0409050, University Library of Munich, Germany.
    68. 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).
    69. Thomas Theobald, 2012. "Agent-based risk management - A regulatory approach to financial markets," IMK Working Paper 95-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    70. Decrouez, Geoffrey & Hambly, Ben & Jones, Owen Dafydd, 2015. "The Hausdorff spectrum of a class of multifractal processes," Stochastic Processes and their Applications, Elsevier, vol. 125(4), pages 1541-1568.
    71. Olkhov, Victor, 2022. "The Market-Based Asset Price Probability," MPRA Paper 115382, University Library of Munich, Germany, revised 16 Nov 2022.
    72. Scarlat, E.I. & Stan, Cristina & Cristescu, C.P., 2007. "Self-similar characteristics of the currency exchange rate in an economy in transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 188-198.
    73. 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).
    74. Wu, Peng & Muzy, Jean-François & Bacry, Emmanuel, 2022. "From rough to multifractal volatility: The log S-fBM model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    75. Li, Jiang-Cheng & Tang, Nian-Sheng & Mei, Dong-Cheng & Li, Yun-Xian & Zhang, Wan, 2016. "The trading time risks of stock investment in stock price drop," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 778-787.
    76. 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.
    77. Peter Hall & Wolfgang Härdle & Torsten Kleinow & Peter Schmidt, 2000. "Semiparametric Bootstrap Approach to Hypothesis Tests and Confidence Intervals for the Hurst Coefficient," Statistical Inference for Stochastic Processes, Springer, vol. 3(3), pages 263-276, October.
    78. 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.
    79. Petre Caraiani, 2012. "Evidence of Multifractality from Emerging European Stock Markets," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    80. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    81. Faheem Aslam & Saqib Aziz & Duc Khuong Nguyen & Khurrum Mughal & Maaz Khan, 2020. "On the efficiency of foreign exchange markets in times of the COVID-19 pandemic," Post-Print hal-02966920, HAL.
    82. Tetsuya Takaishi, 2019. "Rough volatility of Bitcoin," Papers 1904.12346, arXiv.org.
    83. Dr. Brian J. Jacobsen, 2005. "The Use of Downside Risk Measures in Portfolio Construction and Evaluation," Computing in Economics and Finance 2005 5, Society for Computational Economics.
    84. 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.
    85. Sijing Zong & Cornelis A. Los & Nyonyo Kyaw, 2004. "Persistence Characteristics of Latin American Financial Markets," Finance 0411013, University Library of Munich, Germany.
    86. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    87. Marañon, Matias & Kumral, Mustafa, 2018. "Exploring the Elliott Wave Principle to interpret metal commodity price cycles," Resources Policy, Elsevier, vol. 59(C), pages 125-138.
    88. Wei-Xing Zhou, 2009. "Finite-size effect and the components of multifractality in financial volatility," Papers 0912.4782, arXiv.org.
    89. Bhardwaj, Shivam & Chandrasekhar, E. & Seemala, Gopi K. & Gadre, Vikram M., 2020. "Characterization of ionospheric total electron content data using wavelet-based multifractal formalism," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    90. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    91. Chuxuan Jiang & Priya Dev & Ross A. Maller, 2020. "A Hypothesis Test Method for Detecting Multifractal Scaling, Applied to Bitcoin Prices," JRFM, MDPI, vol. 13(5), pages 1-21, May.
    92. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    93. Leopoldo S'anchez-Cant'u & Carlos Arturo Soto-Campos & Andriy Kryvko, 2016. "Evidence of Self-Organization in Time Series of Capital Markets," Papers 1604.03996, arXiv.org, revised Mar 2017.
    94. Zunino, Luciano & Figliola, Alejandra & Tabak, Benjamin M. & Pérez, Darío G. & Garavaglia, Mario & Rosso, Osvaldo A., 2009. "Multifractal structure in Latin-American market indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2331-2340.
    95. 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.
    96. Ali, Naseem & Cal, Raúl Bayoán, 2019. "Scale evolution, intermittency and fluctuation relations in the near-wake of a wind turbine array," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 215-229.
    97. Thomas Lux, 2004. "Detecting Multifractal Properties In Asset Returns: The Failure Of The "Scaling Estimator"," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 481-491.
    98. 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).
    99. M. A. H. Dempster, 2011. "Benoit B. Mandelbrot (1924-2010): a father of Quantitative Finance," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 155-156.
    100. 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).
    101. Wei, Yu & Huang, Dengshi, 2005. "Multifractal analysis of SSEC in Chinese stock market: A different empirical result from Heng Seng index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(2), pages 497-508.
    102. 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.
    103. Robert Mulligan, 2000. "A fractal analysis of foreign exchange markets," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 6(1), pages 33-49, February.
    104. L. A. Gil-Alana, 2005. "Measuring The Memory Parameter On Several Transformations Of Asset Returns," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(06), pages 675-691.
    105. Eisler, Z. & Kertész, J., 2004. "Multifractal model of asset returns with leverage effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 603-622.
    106. Bikramaditya Ghosh & Spyros Papathanasiou & Dimitrios Kenourgios, 2022. "Cross-Country Linkages and Asymmetries of Sovereign Risk Pluralistic Investigation of CDS Spreads," Sustainability, MDPI, vol. 14(21), pages 1-10, October.
    107. 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).
    108. Schadner, Wolfgang, 2022. "U.S. Politics from a multifractal perspective," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    109. Selçuk, Faruk, 2004. "Financial earthquakes, aftershocks and scaling in emerging stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 306-316.
    110. Lux, Thomas, 2013. "Exact solutions for the transient densities of continuous-time Markov switching models: With an application to the poisson multifractal model," Kiel Working Papers 1871, Kiel Institute for the World Economy (IfW Kiel).
    111. 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.
    112. Lux, Thomas, 2003. "The multi-fractal model of asset returns: Its estimation via GMM and its use for volatility forecasting," Economics Working Papers 2003-13, Christian-Albrechts-University of Kiel, Department of Economics.
    113. Enrico Onali & John Goddard, 2014. "Are European equity markets efficient? New evidence from fractal analysis," Papers 1402.1440, arXiv.org.
    114. Thomas Lux & Leonardo Morales-Arias, 2013. "Relative forecasting performance of volatility models: Monte Carlo evidence," Quantitative Finance, Taylor & Francis Journals, vol. 13(9), pages 1375-1394, September.
    115. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
    116. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
    117. Sutthisit Jamdee & Cornelis A. Los, 2005. "Long Memory Options: LM Evidence and Simulations," Finance 0505003, University Library of Munich, Germany.
    118. 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.
    119. 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).
    120. Olkhov, Victor, 2019. "Econophysics of Asset Price, Return and Multiple Expectations," MPRA Paper 91587, University Library of Munich, Germany.
    121. 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.).
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    Cited by:

    1. Giuseppe Brandi & T. Di Matteo, 2022. "Multiscaling and rough volatility: an empirical investigation," Papers 2201.10466, arXiv.org.
    2. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
    3. Mandelbrot, Benoit B., 1999. "Renormalization and fixed points in finance, since 1962," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 263(1), pages 477-487.
    4. Oświe¸cimka, P. & Kwapień, J. & Drożdż, S., 2005. "Multifractality in the stock market: price increments versus waiting times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 347(C), pages 626-638.
    5. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.
    6. Halbleib, Roxana & Dimitriadis, Timo, 2019. "How informative is high-frequency data for tail risk estimation and forecasting? An intrinsic time perspectice," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203669, Verein für Socialpolitik / German Economic Association.
    7. Benoit B. Mandelbrot, 2005. "Parallel cartoons of fractal models of finance," Annals of Finance, Springer, vol. 1(2), pages 179-192, October.
    8. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    9. Laurent Calvet, 2000. "Forecasting Multifractal Volatility," Harvard Institute of Economic Research Working Papers 1902, Harvard - Institute of Economic Research.
    10. Suárez-García, Pablo & Gómez-Ullate, David, 2014. "Multifractality and long memory of a financial index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 226-234.
    11. 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).
    12. Skjeltorp, Johannes A, 2000. "Scaling in the Norwegian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 486-528.
    13. 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.
    14. Laurent Calvet & Adlai Fisher & Benoit Mandelbrot, 1999. "A Multifractal Model of Assets Returns," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-072, New York University, Leonard N. Stern School of Business-.
    15. Sutthisit Jamdee & Cornelis A. Los, 2005. "Multifractal Modeling of the US Treasury Term Structure and Fed Funds Rate," Finance 0502021, University Library of Munich, Germany.
    16. Kwapień, J. & Drożdż, S. & Oświe¸cimka, P., 2006. "The bulk of the stock market correlation matrix is not pure noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 359(C), pages 589-606.
    17. Pawe{l} O'swik{e}cimka & Stanis{l}aw Dro.zd.z & Mattia Frasca & Robert Gk{e}barowski & Natsue Yoshimura & Luciano Zunino & Ludovico Minati, 2020. "Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses," Papers 2004.03319, arXiv.org.
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    29. Eric M. Aldrich & Indra Heckenbach & Gregory Laughlin, 2014. "A Compound Multifractal Model for High-Frequency Asset Returns," BYU Macroeconomics and Computational Laboratory Working Paper Series 2014-05, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    30. Céline Azizieh & Wolfgang Breymann, 2005. "Estimation of the Stylized Facts of a Stochastic Cascade Model," Working Papers CEB 05-009.RS, ULB -- Universite Libre de Bruxelles.
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    35. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    36. Grahovac, Danijel & Leonenko, Nikolai N., 2014. "Detecting multifractal stochastic processes under heavy-tailed effects," Chaos, Solitons & Fractals, Elsevier, vol. 65(C), pages 78-89.

  5. Adlai Fisher & Laurent Calvet & Benoit Mandelbrot, 1997. "Multifractality of Deutschemark/US Dollar Exchange Rates," Cowles Foundation Discussion Papers 1166, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. 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.
    2. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
    4. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    5. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.
    6. Assaf, A., 2006. "Dependence and mean reversion in stock prices: The case of the MENA region," Research in International Business and Finance, Elsevier, vol. 20(3), pages 286-304, September.
    7. Laurent Calvet, 2000. "Forecasting Multifractal Volatility," Harvard Institute of Economic Research Working Papers 1902, Harvard - Institute of Economic Research.
    8. Suárez-García, Pablo & Gómez-Ullate, David, 2014. "Multifractality and long memory of a financial index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 226-234.
    9. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    10. Skjeltorp, Johannes A, 2000. "Scaling in the Norwegian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 486-528.
    11. 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.
    12. Laurent Calvet & Adlai Fisher & Benoit Mandelbrot, 1999. "A Multifractal Model of Assets Returns," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-072, New York University, Leonard N. Stern School of Business-.
    13. Scarlat, E.I. & Stan, Cristina & Cristescu, C.P., 2007. "Self-similar characteristics of the currency exchange rate in an economy in transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 188-198.
    14. 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.
    15. Stošić, Darko & Stošić, Dusan & Stošić, Tatijana & Stanley, H. Eugene, 2015. "Multifractal analysis of managed and independent float exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 13-18.
    16. Zunino, Luciano & Figliola, Alejandra & Tabak, Benjamin M. & Pérez, Darío G. & Garavaglia, Mario & Rosso, Osvaldo A., 2009. "Multifractal structure in Latin-American market indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2331-2340.
    17. Stanislaw Drozdz & Jaroslaw Kwapien & Pawel Oswiecimka & Rafal Rak, 2010. "The foreign exchange market: return distributions, multifractality, anomalous multifractality and Epps effect," Papers 1011.2385, arXiv.org.
    18. Selçuk, Faruk, 2004. "Financial earthquakes, aftershocks and scaling in emerging stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 306-316.
    19. Marc-Etienne BRACHET & Erik TAFLIN & Jean Marcel TCHEOU, 1999. "Scaling transformation and probability distributions for financial time series," GE, Growth, Math methods 9901003, University Library of Munich, Germany.
    20. Lux, Thomas, 2003. "The multi-fractal model of asset returns: Its estimation via GMM and its use for volatility forecasting," Economics Working Papers 2003-13, Christian-Albrechts-University of Kiel, Department of Economics.
    21. Enrico Onali & John Goddard, 2014. "Are European equity markets efficient? New evidence from fractal analysis," Papers 1402.1440, arXiv.org.
    22. Akash P. POOJARI & Siva Kiran GUPTHA & G Raghavender RAJU, 2022. "Multifractal analysis of equities. Evidence from the emerging and frontier banking sectors," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(632), A), pages 61-80, Autumn.
    23. Sornette, Didier & Zhou, Wei-Xing, 2006. "Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 704-726.
    24. Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Naveed & Al-Yahyaee, Khamis Hamed, 2018. "Stock market efficiency: A comparative analysis of Islamic and conventional stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 139-153.
    25. 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.
    26. 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.
    27. Céline Azizieh & Wolfgang Breymann, 2005. "Estimation of the Stylized Facts of a Stochastic Cascade Model," Working Papers CEB 05-009.RS, ULB -- Universite Libre de Bruxelles.
    28. Per Frederiksen & Frank S. Nielsen, 2008. "Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood," CREATES Research Papers 2008-59, Department of Economics and Business Economics, Aarhus University.
    29. Hallam, Mark & Olmo, Jose, 2014. "Forecasting daily return densities from intraday data: A multifractal approach," International Journal of Forecasting, Elsevier, vol. 30(4), pages 863-881.
    30. Aloui, Chaker & Shahzad, Syed Jawad Hussain & Jammazi, Rania, 2018. "Dynamic efficiency of European credit sectors: A rolling-window multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 337-349.
    31. Rossitsa Yalamova, 2012. "Fractal Measures in Market Microstructure Research," Multinational Finance Journal, Multinational Finance Journal, vol. 16(1-2), pages 137-154, March - J.
    32. Baviera, Roberto & Vergni, Davide & Vulpiani, Angelo, 2000. "Markovian approximation in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 280(3), pages 566-581.
    33. Laurent Calvet & Adlai Fisher & Benoit Mandelbrot, 1997. "Large Deviations and the Distribution of Price Changes," Cowles Foundation Discussion Papers 1165, Cowles Foundation for Research in Economics, Yale University.
    34. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Differentiating intraday seasonalities through wavelet multi-scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 543-556.
    35. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    36. Assaf, Ata, 2015. "Long memory and level shifts in REITs returns and volatility," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 172-182.

Articles

  1. Benoit B. Mandelbrot, 2005. "Parallel cartoons of fractal models of finance," Annals of Finance, Springer, vol. 1(2), pages 179-192, October.

    Cited by:

    1. Estrada, Fernando, 2010. "Benoit Mandelbrot 1924 -2010: A Greek among Romans," MPRA Paper 25946, University Library of Munich, Germany.
    2. Estrada, Fernando, 2011. "Benoit Mandelbrot (1924 - 2011 ) : A Greek among Romans," MPRA Paper 30563, University Library of Munich, Germany.
    3. Yuli Radev, 2015. "New dynamic disequilibrium," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 65-90.
    4. Ronny Mazzocchi, 2013. "Scope and Flaws of the New Neoclassical Synthesis," DEM Discussion Papers 2013/13, Department of Economics and Management.

  2. Benoit B. Mandelbrot, 2005. "The inescapable need for fractal tools in finance," Annals of Finance, Springer, vol. 1(2), pages 193-195, October.

    Cited by:

    1. A. K. M. Azhar & Vincent B. Y. Gan & W. A. T. Wan Abdullah & H. Zainuddin, 2015. "On the Fractal Geometry of the Balance Sheet and the Fractal Index of Insolvency Risk," Papers 1512.09280, arXiv.org.

  3. J. Asikainen & A. Aharony & B. Mandelbrot & E. Rausch & J.-P. Hovi, 2003. "Fractal geometry of critical Potts clusters," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 34(4), pages 479-487, August.

    Cited by:

    1. Ilnytskyi, Jaroslav & Pikuta, Piotr & Ilnytskyi, Hryhoriy, 2018. "Stationary states and spatial patterning in the cellular automaton SEIS epidemiology model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 241-255.

  4. B. B. Mandelbrot, 2001. "Scaling in financial prices: II. Multifractals and the star equation," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 124-130.

    Cited by:

    1. Benoit B. Mandelbrot, 2005. "Parallel cartoons of fractal models of finance," Annals of Finance, Springer, vol. 1(2), pages 179-192, October.
    2. 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).
    3. Sutthisit Jamdee & Cornelis A. Los, 2005. "Multifractal Modeling of the US Treasury Term Structure and Fed Funds Rate," Finance 0502021, University Library of Munich, Germany.
    4. M. A. H. Dempster, 2011. "Benoit B. Mandelbrot (1924-2010): a father of Quantitative Finance," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 155-156.
    5. Wilhelm Berghorn & Martin T. Schulz & Markus Vogl & Sascha Otto, 2021. "Trend Momentum II: Driving Forces of Low Volatility and Momentum," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 300-319, May.
    6. 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.
    7. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    8. Gao-Feng Gu & Wei-Xing Zhou, 2006. "Statistical properties of daily ensemble variables in the Chinese stock markets," Papers physics/0603147, arXiv.org.
    9. Jean de Carufel & Martin Brooks & Michael Stieber & Paul Britton, 2017. "A Topological Approach to Scaling in Financial Data," Papers 1710.08860, arXiv.org.
    10. Chris Heyde, 2009. "Scaling issues for risky asset modelling," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 593-603, July.

  5. B. B. Mandelbrot, 2001. "Stochastic volatility, power laws and long memory," Quantitative Finance, Taylor & Francis Journals, vol. 1(6), pages 558-559.

    Cited by:

    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
    2. T. Di Matteo & T. Aste & Michel M. Dacorogna, 2004. "Using the Scaling Analysis to Characterize Financial Markets," Finance 0402014, University Library of Munich, Germany.
    3. Jean-Philippe Bouchaud & Julien Kockelkoren & Marc Potters, 2006. "Random walks, liquidity molasses and critical response in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 6(2), pages 115-123.
    4. Steven N. Durlauf, 2005. "Complexity and Empirical Economics," Economic Journal, Royal Economic Society, vol. 115(504), pages 225-243, June.
    5. Simone Alfarano & Thomas Lux, 2007. "A Minimal Noise Trader Model with Realistic Time Series Properties," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 345-361, Springer.
    6. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.
    7. Benoit B. Mandelbrot, 2005. "Parallel cartoons of fractal models of finance," Annals of Finance, Springer, vol. 1(2), pages 179-192, October.
    8. Laurent Calvet & Adlai Fisher, 2003. "Regime-Switching and the Estimation of Multifractal Processes," Harvard Institute of Economic Research Working Papers 1999, Harvard - Institute of Economic Research.
    9. T. Di Matteo & T. Aste & Michel M. Dacorogna, 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Econometrics 0503004, University Library of Munich, Germany.
    10. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
    11. Hans B Sieburg & Giulio Cattarossi & Christa E Muller-Sieburg, 2013. "Lifespan Differences in Hematopoietic Stem Cells are Due to Imperfect Repair and Unstable Mean-Reversion," PLOS Computational Biology, Public Library of Science, vol. 9(4), pages 1-15, April.
    12. M. A. H. Dempster, 2011. "Benoit B. Mandelbrot (1924-2010): a father of Quantitative Finance," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 155-156.
    13. Eric Hillebrand, 2003. "Overlaying Time Scales and Persistence Estimation in GARCH(1,1) Models," Econometrics 0301003, University Library of Munich, Germany.
    14. Chen, Shengming & Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "The Russia–Ukraine war and energy market volatility: A novel application of the volatility ratio in the context of natural gas," Resources Policy, Elsevier, vol. 85(PA).
    15. Mathieu, Philippe & Morvan, Rémi, 2019. "A deterministic behaviour for realistic price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 33-49.
    16. Sio Chong U & Jacky So & Deng Ding & Lihong Liu, 2016. "An efficient Fourier expansion method for the calculation of value-at-risk: Contributions of extra-ordinary risks," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-27, March.
    17. Davide Lauria & W. Brent Lindquist & Svetlozar T. Rachev & Yuan Hu, 2023. "Unifying Market Microstructure and Dynamic Asset Pricing," Papers 2304.02356, arXiv.org, revised Feb 2024.
    18. Jonathan A. Batten & Cetin Ciner & Brian M. Lucey & Peter G. Szilagyi, 2013. "The structure of gold and silver spread returns," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 561-570, March.
    19. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
    20. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.

  6. B. B. Mandelbrot, 2001. "Scaling in financial prices: I. Tails and dependence," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 113-123.

    Cited by:

    1. Arun Kumar & Palaniappan Vellaisamy, 2012. "Fractional Normal Inverse Gaussian Process," Methodology and Computing in Applied Probability, Springer, vol. 14(2), pages 263-283, June.
    2. Benoit B. Mandelbrot, 2005. "Parallel cartoons of fractal models of finance," Annals of Finance, Springer, vol. 1(2), pages 179-192, October.
    3. 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).
    4. Sutthisit Jamdee & Cornelis A. Los, 2005. "Multifractal Modeling of the US Treasury Term Structure and Fed Funds Rate," Finance 0502021, University Library of Munich, Germany.
    5. Dr. Brian J. Jacobsen, 2005. "The Use of Downside Risk Measures in Portfolio Construction and Evaluation," Computing in Economics and Finance 2005 5, Society for Computational Economics.
    6. A. K. M. Azhar & Vincent B. Y. Gan & W. A. T. Wan Abdullah & H. Zainuddin, 2015. "On the Fractal Geometry of the Balance Sheet and the Fractal Index of Insolvency Risk," Papers 1512.09280, arXiv.org.
    7. M. A. H. Dempster, 2011. "Benoit B. Mandelbrot (1924-2010): a father of Quantitative Finance," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 155-156.
    8. Wilhelm Berghorn & Martin T. Schulz & Markus Vogl & Sascha Otto, 2021. "Trend Momentum II: Driving Forces of Low Volatility and Momentum," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 300-319, May.
    9. Iacopo Giampaoli & Wing Lon Ng & Nick Constantinou, 2013. "Periodicities Of Foreign Exchange Markets And The Directional Change Power Law," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(3), pages 189-206, July.
    10. 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.
    11. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    12. Gao-Feng Gu & Wei-Xing Zhou, 2006. "Statistical properties of daily ensemble variables in the Chinese stock markets," Papers physics/0603147, arXiv.org.
    13. Heinrich, Torsten, 2016. "The Narrow and the Broad Approach to Evolutionary Modeling in Economics," MPRA Paper 75797, University Library of Munich, Germany.
    14. Jean de Carufel & Martin Brooks & Michael Stieber & Paul Britton, 2017. "A Topological Approach to Scaling in Financial Data," Papers 1710.08860, arXiv.org.
    15. Chris Heyde, 2009. "Scaling issues for risky asset modelling," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 593-603, July.
    16. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).

  7. B. B. Mandelbrot, 2001. "Scaling in financial prices: IV. Multifractal concentration," Quantitative Finance, Taylor & Francis Journals, vol. 1(6), pages 641-649.

    Cited by:

    1. 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.
    2. Sutthisit Jamdee & Cornelis A. Los, 2005. "Multifractal Modeling of the US Treasury Term Structure and Fed Funds Rate," Finance 0502021, University Library of Munich, Germany.
    3. M. A. H. Dempster, 2011. "Benoit B. Mandelbrot (1924-2010): a father of Quantitative Finance," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 155-156.
    4. Wilhelm Berghorn & Martin T. Schulz & Markus Vogl & Sascha Otto, 2021. "Trend Momentum II: Driving Forces of Low Volatility and Momentum," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 300-319, May.
    5. 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.
    6. Gencay, Ramazan & Selcuk, Faruk, 2004. "Extreme value theory and Value-at-Risk: Relative performance in emerging markets," International Journal of Forecasting, Elsevier, vol. 20(2), pages 287-303.
    7. Mehmet Ali Balcı & Larissa M. Batrancea & Ömer Akgüller & Lucian Gaban & Mircea-Iosif Rus & Horia Tulai, 2022. "Fractality of Borsa Istanbul during the COVID-19 Pandemic," Mathematics, MDPI, vol. 10(14), pages 1-33, July.
    8. Chris Heyde, 2009. "Scaling issues for risky asset modelling," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 593-603, July.

  8. B. B. Mandelbrot, 2001. "Scaling in financial prices: III. Cartoon Brownian motions in multifractal time," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 427-440.

    Cited by:

    1. Benoit B. Mandelbrot, 2005. "Parallel cartoons of fractal models of finance," Annals of Finance, Springer, vol. 1(2), pages 179-192, October.
    2. Suárez-García, Pablo & Gómez-Ullate, David, 2014. "Multifractality and long memory of a financial index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 226-234.
    3. Krenar Avdulaj & Ladislav Kristoufek, 2020. "On Tail Dependence and Multifractality," Mathematics, MDPI, vol. 8(10), pages 1-13, October.
    4. 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).
    5. Sutthisit Jamdee & Cornelis A. Los, 2005. "Multifractal Modeling of the US Treasury Term Structure and Fed Funds Rate," Finance 0502021, University Library of Munich, Germany.
    6. M. A. H. Dempster, 2011. "Benoit B. Mandelbrot (1924-2010): a father of Quantitative Finance," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 155-156.
    7. 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.
    8. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    9. Pablo Su'arez-Garc'ia & David G'omez-Ullate, 2013. "Multifractality and long memory of a financial index," Papers 1306.0490, arXiv.org.
    10. Rossitsa Yalamova, 2012. "Fractal Measures in Market Microstructure Research," Multinational Finance Journal, Multinational Finance Journal, vol. 16(1-2), pages 137-154, March - J.
    11. Calabrese, Armando & Capece, Guendalina & Costa, Roberta & Di Pillo, Francesca & Giuffrida, Stefania, 2018. "A ‘power law’ based method to reduce size-related bias in indicators of knowledge performance: An application to university research assessment," Journal of Informetrics, Elsevier, vol. 12(4), pages 1263-1281.
    12. Jean de Carufel & Martin Brooks & Michael Stieber & Paul Britton, 2017. "A Topological Approach to Scaling in Financial Data," Papers 1710.08860, arXiv.org.

  9. Mandelbrot, Benoit B., 1999. "Renormalization and fixed points in finance, since 1962," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 263(1), pages 477-487.

    Cited by:

    1. Gregory G. Brunk, 2003. "Swarming of innovations, fractal patterns, and the historical time series of US patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(1), pages 61-80, January.
    2. Antoniou, Antonios & Vorlow, Constantinos E., 2005. "Price clustering and discreteness: is there chaos behind the noise?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 389-403.
    3. Leontitsis, Alexandros & Vorlow, Constantinos E., 2006. "Accounting for outliers and calendar effects in surrogate simulations of stock return sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(2), pages 522-530.

  10. Cioczek-Georges, R. & Mandelbrot, B. B., 1996. "Alternative micropulses and fractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 64(2), pages 143-152, November.

    Cited by:

    1. Mine Caglar, 2011. "Stock Price Processes with Infinite Source Poisson Agents," Papers 1106.6300, arXiv.org.
    2. Serge Cohen & Murad S. Taqqu, 2004. "Small and Large Scale Behavior of the Poissonized Telecom Process," Methodology and Computing in Applied Probability, Springer, vol. 6(4), pages 363-379, December.
    3. Gaigalas, Raimundas, 2006. "A Poisson bridge between fractional Brownian motion and stable Lévy motion," Stochastic Processes and their Applications, Elsevier, vol. 116(3), pages 447-462, March.
    4. Jumarie, Guy, 2007. "Lagrangian mechanics of fractional order, Hamilton–Jacobi fractional PDE and Taylor’s series of nondifferentiable functions," Chaos, Solitons & Fractals, Elsevier, vol. 32(3), pages 969-987.
    5. Hermine Biermé & Anne Estrade & Ingemar Kaj, 2010. "Self-similar Random Fields and Rescaled Random Balls Models," Journal of Theoretical Probability, Springer, vol. 23(4), pages 1110-1141, December.
    6. Jumarie, Guy, 2009. "Probability calculus of fractional order and fractional Taylor’s series application to Fokker–Planck equation and information of non-random functions," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1428-1448.
    7. Jumarie, Guy, 2009. "From Lagrangian mechanics fractal in space to space fractal Schrödinger’s equation via fractional Taylor’s series," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1590-1604.
    8. Nuugulu, Samuel M & Gideon, Frednard & Patidar, Kailash C, 2021. "A robust numerical scheme for a time-fractional Black-Scholes partial differential equation describing stock exchange dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    9. Jumarie, Guy, 2008. "Stock exchange fractional dynamics defined as fractional exponential growth driven by (usual) Gaussian white noise. Application to fractional Black-Scholes equations," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 271-287, February.
    10. Luis G. Gorostiza & Reyla A. Navarro & Eliane R. Rodrigues, 2004. "Some Long-Range Dependence Processes Arising from Fluctuations of Particle Systems," RePAd Working Paper Series lrsp-TRS401, Département des sciences administratives, UQO.
    11. Jumarie, Guy, 2006. "Fractionalization of the complex-valued Brownian motion of order n using Riemann–Liouville derivative. Applications to mathematical finance and stochastic mechanics," Chaos, Solitons & Fractals, Elsevier, vol. 28(5), pages 1285-1305.

  11. Cioczek-Georges, R. & Mandelbrot, B. B., 1995. "A class of micropulses and antipersistent fractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 60(1), pages 1-18, November.

    Cited by:

    1. Gil-Alana, Luis A., 2003. "A Univariate Analysis of Unemployment and Inflation in Italy: A Fractionally Integrated Approach," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(2), November.
    2. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
    3. Luis Gil-Alana, 2003. "Stochastic behavior of nominal exchange rates," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 31(2), pages 159-173, June.
    4. Jumarie, Guy, 2005. "Merton's model of optimal portfolio in a Black-Scholes Market driven by a fractional Brownian motion with short-range dependence," Insurance: Mathematics and Economics, Elsevier, vol. 37(3), pages 585-598, December.
    5. 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).
    6. Christian Fischer & Luis Gil-Alana, 2009. "The nature of the relationship between international tourism and international trade: the case of German imports of Spanish wine," Applied Economics, Taylor & Francis Journals, vol. 41(11), pages 1345-1359.
    7. L. A. Gil-Alana, 2003. "A fractional integration analysis of the population in some OECD countries," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1147-1159.
    8. Cioczek-Georges, R. & Mandelbrot, B. B., 1996. "Alternative micropulses and fractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 64(2), pages 143-152, November.
    9. Manmohan S. Kumar & Tatsuyoshi Okimoto, 2007. "Dynamics of Persistence in International Inflation Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1457-1479, September.
    10. L.A. Gil-Alana & G.M. caporale, 2004. "Long-run and Cyclical Dynamics in the US Stock Market," Econometric Society 2004 Latin American Meetings 344, Econometric Society.
    11. Francis W. Ahking, 2004. "Non-Parametric Tests of Real Exchange rates in the Post-Bretton Woods Era," Working papers 2004-05, University of Connecticut, Department of Economics.
    12. Jumarie, Guy, 2007. "Lagrangian mechanics of fractional order, Hamilton–Jacobi fractional PDE and Taylor’s series of nondifferentiable functions," Chaos, Solitons & Fractals, Elsevier, vol. 32(3), pages 969-987.
    13. Rea, William & Oxley, Les & Reale, Marco & Brown, Jennifer, 2013. "Not all estimators are born equal: The empirical properties of some estimators of long memory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 29-42.
    14. Luis Gil-Alana, 2004. "The dynamics of the real exchange rates in Europe: a comparative study across countries using fractional integration," Applied Economics Letters, Taylor & Francis Journals, vol. 11(7), pages 429-432.
    15. Hermine Biermé & Anne Estrade & Ingemar Kaj, 2010. "Self-similar Random Fields and Rescaled Random Balls Models," Journal of Theoretical Probability, Springer, vol. 23(4), pages 1110-1141, December.
    16. Jumarie, Guy, 2009. "Probability calculus of fractional order and fractional Taylor’s series application to Fokker–Planck equation and information of non-random functions," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1428-1448.
    17. Jumarie, Guy, 2009. "From Lagrangian mechanics fractal in space to space fractal Schrödinger’s equation via fractional Taylor’s series," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1590-1604.
    18. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "High and low prices and the range in the European stock markets: A long-memory approach," Research in International Business and Finance, Elsevier, vol. 52(C).
    19. Francis X. Diebold & Atsushi Inoue, 2000. "Long Memory and Regime Switching," NBER Technical Working Papers 0264, National Bureau of Economic Research, Inc.
    20. Richard T. Baillie & George Kapetanios, 2006. "Nonlinear Models with Strongly Dependent Processes and Applications to Forward Premia and Real Exchange Rates," Working Papers 570, Queen Mary University of London, School of Economics and Finance.
    21. Barros, Carlos P. & Gil-Alana, Luis A. & Wanke, Peter, 2016. "Energy production in Brazil: Empirical facts based on persistence, seasonality and breaks," Energy Economics, Elsevier, vol. 54(C), pages 88-95.
    22. Gil-Alana, Luis A., 2004. "Modelling the U.S. interest rate in terms of I(d) statistical models," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(4), pages 475-486, September.
    23. Gourieroux, Christian & Jasiak, Joann, 2001. "Memory and infrequent breaks," Economics Letters, Elsevier, vol. 70(1), pages 29-41, January.
    24. Jumarie, Guy, 2006. "Fractionalization of the complex-valued Brownian motion of order n using Riemann–Liouville derivative. Applications to mathematical finance and stochastic mechanics," Chaos, Solitons & Fractals, Elsevier, vol. 28(5), pages 1285-1305.

  12. Evertsz, Carl J.G. & Mandelbrot, Benoit B., 1992. "Self-similarity of harmonic measure on DLA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 185(1), pages 77-86.

    Cited by:

    1. Dai, Meifeng & Zhang, Cheng & Zhang, Danping, 2014. "Multifractal and singularity analysis of highway volume data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 332-340.
    2. Li, Xuewei & Shang, Pengjian, 2007. "Multifractal classification of road traffic flows," Chaos, Solitons & Fractals, Elsevier, vol. 31(5), pages 1089-1094.
    3. Dai, Meifeng & Hou, Jie & Gao, Jianyu & Su, Weiyi & Xi, Lifeng & Ye, Dandan, 2016. "Mixed multifractal analysis of China and US stock index series," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 268-275.

  13. Mandelbrot, Benoit B., 1990. "New “anomalous” multiplicative multifractals: Left sided ƒ(α) and the modelling of DLA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 168(1), pages 95-111.

    Cited by:

    1. Zhou, Wei-Xing & Sornette, Didier, 2009. "Numerical investigations of discrete scale invariance in fractals and multifractal measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(13), pages 2623-2639.
    2. Zhao, Zhen-yu & Zhu, Jiang & Xia, Bo, 2016. "Multi-fractal fluctuation features of thermal power coal price in China," Energy, Elsevier, vol. 117(P1), pages 10-18.

  14. Mandelbrot, Benoit B, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices: Comment," Econometrica, Econometric Society, vol. 41(1), pages 157-159, January.

    Cited by:

    1. L. Ingber, 1996. "Canonical momenta indicators of financial markets and neocortical EEG," Lester Ingber Papers 96cm, Lester Ingber.
    2. Benjamin Blau & Matthew Hill & Hao Wang, 2011. "REIT Short Sales and Return Predictability," The Journal of Real Estate Finance and Economics, Springer, vol. 42(4), pages 481-503, May.
    3. Rangel, José Gonzalo, 2011. "Macroeconomic news, announcements, and stock market jump intensity dynamics," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1263-1276, May.
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    3. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
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    151. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
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    154. Riyadh Rustam Al-Mosawi & Shahjahan Khan, 2018. "Estimating moments of a selected Pareto population under asymmetric scale invariant loss function," Statistical Papers, Springer, vol. 59(1), pages 183-198, March.
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    156. Lafond, François & Farmer, J. Doyne & Koutroumpis, Pantelis & Winkler, Julian & Heinrich, Torsten & Yang, Jangho, 2019. "Measuring productivity dispersion: a parametric approach using the Lévy alpha-stable distribution," INET Oxford Working Papers 2019-14, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    157. De Giovanni, Domenico & Ortobelli, Sergio & Rachev, Svetlozar, 2008. "Delta hedging strategies comparison," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1615-1631, March.
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    160. Rongjiang Cai & Tao Lv & Xu Deng, 2021. "Evaluation of Environmental Information Disclosure of Listed Companies in China’s Heavy Pollution Industries: A Text Mining-Based Methodology," Sustainability, MDPI, vol. 13(10), pages 1-23, May.
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  24. Benoit Mandelbrot, 1962. "Paretian Distributions and Income Maximization," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 76(1), pages 57-85.

    Cited by:

    1. Derek Neal & Sherwin Rosen, 1998. "Theories of the Distribution of Labor Earnings," NBER Working Papers 6378, National Bureau of Economic Research, Inc.
    2. James J. Heckman & Tomas Jagelka & Tim Kautz, 2019. "Some Contributions of Economics to the Study of Personality," Working Papers 2019-069, Human Capital and Economic Opportunity Working Group.
    3. Sergio Ocampo, 2019. "A task-based theory of occupations with multidimensional heterogeneity," 2019 Meeting Papers 477, Society for Economic Dynamics.
    4. Ismael Mourifie & Marc Henry & Romuald Meango, 2017. "Sharp bounds and testability of a Roy model of STEM major choices," Papers 1709.09284, arXiv.org, revised Nov 2019.
    5. Paul J. Taubman, 1977. "Schooling, Ability, Nonpecuniary Rewards, Socioeconomic Background, and the Lifetime Distribution of Earnings," NBER Chapters, in: The Distribution of Economic Well-Being, pages 419-510, National Bureau of Economic Research, Inc.
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    7. John Dagsvik & Zhiyang Jia & Bjørn Vatne & Weizhen Zhu, 2013. "Is the Pareto–Lévy law a good representation of income distributions?," Empirical Economics, Springer, vol. 44(2), pages 719-737, April.
    8. Paul J. Taubman, 1973. "Schooling, Ability, Non Pecuniary Rewards, Socioeconomic Background and the Lifetime Distribution of Earnings," NBER Working Papers 0017, National Bureau of Economic Research, Inc.
    9. Gary S. Becker & Nigel Tomes, "undated". "Human Capital and the Rise and Fall of Families," University of Chicago - Population Research Center 84-10, Chicago - Population Research Center.
    10. Inga Heiland & Wilhelm Kohler, 2013. "Heterogeneous Workers, Trade, and Migration," CESifo Working Paper Series 4387, CESifo.
    11. Santiago Pindado & Carlos Pindado & Javier Cubas, 2017. "Fréchet Distribution Applied to Salary Incomes in Spain from 1999 to 2014. An Engineering Approach to Changes in Salaries’ Distribution," Economies, MDPI, vol. 5(2), pages 1-19, May.
    12. Tavneet Suri, 2006. "Selection and Comparative Advantage in Technology Adoption," Working Papers 944, Economic Growth Center, Yale University.
    13. Leopoldo S'anchez-Cant'u & Carlos Arturo Soto-Campos & Andriy Kryvko, 2016. "Evidence of Self-Organization in Time Series of Capital Markets," Papers 1604.03996, arXiv.org, revised Mar 2017.
    14. Michael Kateregga & Sure Mataramvura & David Taylor, 2017. "Parameter estimation for stable distributions with application to commodity futures log returns," Papers 1706.09756, arXiv.org.
    15. Eshaghnia, Sadegh S. M. & Heckman, James J. & Landerso, Rasmus, 2023. "Maximum Impact Intergenerational Associations," IZA Discussion Papers 16038, Institute of Labor Economics (IZA).
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    17. Philippe Choné & Francis Kramarz, 2021. "Matching Workers' Skills and Firms' Technologies: From Bundling to Unbundling," Working Papers 2021-10, Center for Research in Economics and Statistics.
    18. Marcos Gómez & Francisco Parro, 2018. "The Fundamental Contradiction Of Capitalism Revisited," Bulletin of Economic Research, Wiley Blackwell, vol. 70(4), pages 381-399, October.
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    22. Rémillard Bruno & Theodorescu Radu, 2000. "Inference Based On The Empirical Probability Generating Function For Mixtures Of Poisson Distributions," Statistics & Risk Modeling, De Gruyter, vol. 18(4), pages 349-366, April.

Chapters

  1. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    See citations under working paper version above.
  2. Benoit B. Mandelbrot, 1972. "Statistical Methodology for Nonperiodic Cycles: From the Covariance To R/S Analysis," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 3, pages 259-290, National Bureau of Economic Research, Inc.

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    1. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Trinidad Segovia, J.E., 2013. "Measuring the self-similarity exponent in Lévy stable processes of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5330-5345.
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    3. Assaf, Ata, 2016. "MENA stock market volatility persistence: Evidence before and after the financial crisis of 2008," Research in International Business and Finance, Elsevier, vol. 36(C), pages 222-240.
    4. Fu, Hui & Chen, Wenting & He, Xin-Jiang, 2018. "On a class of estimation and test for long memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 906-920.
    5. Sanjay Rajagopal, 2012. "A Study of the Returns Behavior of Small Capitalization REITs," Journal of Economics and Behavioral Studies, AMH International, vol. 4(8), pages 457-466.
    6. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    7. Samet Günay, 2016. "Performance of the Multifractal Model of Asset Returns (MMAR): Evidence from Emerging Stock Markets," IJFS, MDPI, vol. 4(2), pages 1-17, May.
    8. Mitra, Subrata Kumar & Bawa, Jaslene & Kannadhasan, M. & Goyal, Vinay & Chattopadhyay, Manojit, 2017. "Can profitability through momentum strategies be enhanced applying a range to standard deviation filter?," Finance Research Letters, Elsevier, vol. 20(C), pages 269-273.
    9. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    10. Francisco Gerardo Benavides-Bravo & Dulce Martinez-Peon & Ángela Gabriela Benavides-Ríos & Otoniel Walle-García & Roberto Soto-Villalobos & Mario A. Aguirre-López, 2021. "A Climate-Mathematical Clustering of Rainfall Stations in the Río Bravo-San Juan Basin (Mexico) by Using the Higuchi Fractal Dimension and the Hurst Exponent," Mathematics, MDPI, vol. 9(21), pages 1-11, October.
    11. Shaher Al-Gounmeein Remal & Ismail Mohd Tahir, 2021. "Modelling and forecasting monthly Brent crude oil prices: a long memory and volatility approach," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 29-54, March.
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    24. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
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