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Yannick Malevergne

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. José da Fonseca & Yannick Malevergne, 2021. "A simple microstructure model based on the Cox-BESQ process with application to optimal execution policy," Post-Print halshs-03590382, HAL.

    Cited by:

    1. Lee Kyungsub, 2024. "Multi-kernel property in high-frequency price dynamics under Hawkes model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(4), pages 605-624.
    2. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.
    3. Kyungsub Lee, 2023. "Multi-kernel property in high-frequency price dynamics under Hawkes model," Papers 2302.11822, arXiv.org.

  2. Henri Loubergé & Yannick Malevergne & Béatrice Rey, 2019. "New Results for Additive and Multiplicative Risk Apportionment," Working Papers 1915, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.

    Cited by:

    1. Heinzel, Christoph, 2023. "Comparing utility derivative premia under additive and multiplicative risks," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 23-40.
    2. Ignacia Benitez & Claudio A. Bonilla & Marcos Vergara, 2024. "Hybrid entrepreneurship and risk," Small Business Economics, Springer, vol. 63(3), pages 1171-1196, October.

  3. Marc Senneret & Yannick Malevergne & Patrice Abry & Gerald Perrin & Laurent Jaffres, 2016. "Covariance Versus Precision Matrix Estimation for Efficient Asset Allocation," Post-Print halshs-03590388, HAL.

    Cited by:

    1. Paola Stolfi & Mauro Bernardi & Davide Vergni, 2022. "Robust estimation of time-dependent precision matrix with application to the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    2. László PáL, 2022. "Asset Allocation Strategies Using Covariance Matrix Estimators," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 10(1), pages 133-144, September.
    3. Nadège Ribau-Peltre & Pascal Damel & An Lethi, 2018. "A methodology to avoid over-diversification of funds of equity funds An implementation case study for equity funds of funds in bull markets," Post-Print hal-03027770, HAL.
    4. Caner, Mehmet & Medeiros, Marcelo & Vasconcelos, Gabriel F.R., 2023. "Sharpe Ratio analysis in high dimensions: Residual-based nodewise regression in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 393-417.
    5. Jack Jewson & Li Li & Laura Battaglia & Stephen Hansen & David Rossell & Piotr Zwiernik, 2022. "Graphical model inference with external network data," CeMMAP working papers 20/22, Institute for Fiscal Studies.

  4. Jeroen Rozendaal & Yannick Malevergne & Didier Sornette, 2015. "Macroeconomic Dynamics of Assets, Leverage and Trust," Papers 1512.03618, arXiv.org.

    Cited by:

    1. Marco Desogus & Beatrice Venturi, 2023. "Stability and Bifurcations in Banks and Small Enterprises—A Three-Dimensional Continuous-Time Dynamical System," JRFM, MDPI, vol. 16(3), pages 1-20, March.
    2. von der Becke Susanne & Sornette Didier, 2019. "An Asset-Based Framework of Credit Creation (applied to the Global Financial Crisis)," Accounting, Economics, and Law: A Convivium, De Gruyter, vol. 9(2), pages 1-21, July.

  5. Andreas D. Huesler & Yannick Malevergne & Didier Sornette, 2012. "Investors’ Expectations, Management Fees and the Underperformance of Mutual Funds," Swiss Finance Institute Research Paper Series 12-01, Swiss Finance Institute.

    Cited by:

    1. Paulo Matos & Guilherme Padilha & Maurício Benegas, 2016. "On the management efficiency of Brazilian stock mutual funds," Operational Research, Springer, vol. 16(3), pages 365-399, October.

  6. Xiaohui NI & Yannick MALEVERGNE & Didier SORNETTE & Peter WOEHRMANN, 2011. "Robust reverse engineering of crosssectional returns and improved portfolio allocation performance using the CAPM," Swiss Finance Institute Research Paper Series 11-03, Swiss Finance Institute.

    Cited by:

    1. Clark, Ephraim & Kassimatis, Konstantinos, 2014. "Exploiting stochastic dominance to generate abnormal stock returns," Journal of Financial Markets, Elsevier, vol. 20(C), pages 20-38.
    2. Sandro Claudio Lera & Didier Sornette, 2015. "Currency target zone modeling: An interplay between physics and economics," Papers 1508.04754, arXiv.org, revised Oct 2015.
    3. David Ardia & Kris Boudt, 2013. "Implied Expected Returns and the Choice of a Mean-Variance Efficient Portfolio Proxy," Cahiers de recherche 1328, CIRPEE.
    4. Clark, Ephraim & Kassimatis, Konstantinos, 2012. "An empirical analysis of marginal conditional stochastic dominance," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1144-1151.
    5. Bellu, Mirko & Conversano, Claudio, 2020. "Protected Adaptive Asset Allocation," Finance Research Letters, Elsevier, vol. 32(C).

  7. Y. Malevergne & A. Saichev & D. Sornette, 2010. "Zipf's law and maximum sustainable growth," Papers 1012.0199, arXiv.org.

    Cited by:

    1. Vandermarliere, B. & Ryckebusch, J. & Schoors, K. & Cauwels, P. & Sornette, D., 2017. "Discrete hierarchy of sizes and performances in the exchange-traded fund universe," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 111-123.
    2. Corrado Di Guilmi & Yoshi Fujiwara, 2020. "Does the supply network shape the firm size distribution? The Japanese case," CAMA Working Papers 2020-66, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Christian Schluter & Mark Trede, 2019. "Size distributions reconsidered," Econometric Reviews, Taylor & Francis Journals, vol. 38(6), pages 695-710, July.
    4. Gabaix, Xavier & Moll, Benjamin & Lasry, Jean-Michel & Lions, Pierre-Louis, 2015. "The Dynamics of Inequality," CEPR Discussion Papers 11028, C.E.P.R. Discussion Papers.
    5. Ke Wu & Spencer Wheatley & Didier Sornette, 2018. "Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations," Papers 1803.03088, arXiv.org, revised May 2018.
    6. Didier Sornette & Thomas Maillart & Giacomo Ghezzi, 2014. "How Much Is the Whole Really More than the Sum of Its Parts? 1 ⊞ 1 = 2.5: Superlinear Productivity in Collective Group Actions," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-15, August.
    7. Charles I. Jones & Jihee Kim, 2014. "A Schumpeterian Model of Top Income Inequality," NBER Working Papers 20637, National Bureau of Economic Research, Inc.
    8. 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.
    9. Edouard Ribes, 2018. "Growth patterns of US professional services firms," Working Papers hal-01762381, HAL.
    10. Toda, Alexis Akira, 2016. "Zipf's Law: A Microfoundation," MPRA Paper 78985, University Library of Munich, Germany.
    11. Anindya S. Chakrabarti, 2017. "Scale-free distribution as an economic invariant: a theoretical approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 1-26, April.
    12. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    13. Yu Zhang & Claudio Tessone, 2024. "Bitcoin Transaction Behavior Modeling Based on Balance Data," Papers 2409.10407, arXiv.org.
    14. Davide Fiaschi & Imre Kondor & Matteo Marsili & Valerio Volpati, 2013. "The Interrupted Power Law and The Size of Shadow Banking," Papers 1309.2130, arXiv.org, revised Apr 2014.
    15. Jo~ao Pedro Jerico & Franc{c}ois P. Landes & Matteo Marsili & Isaac P'erez Castillo & Valerio Volpati, 2016. "When does inequality freeze an economy?," Papers 1602.07300, arXiv.org, revised Apr 2016.
    16. Sandro Claudio Lera & Didier Sornette, 2017. "Quantification of the evolution of firm size distributions due to mergers and acquisitions," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-16, August.
    17. Gregor Semieniuk & Ellis Scharfenaker, 2014. "A Bayesian Latent Variable Mixture Model for Filtering Firm Profit Rate," SCEPA working paper series. 2014-1, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.

  8. Yannick Malevergne & B. Rey, 2010. "Preserving preference rankings under non-financial background risk," Post-Print hal-02312501, HAL.

    Cited by:

    1. Henri Loubergé & Yannick Malevergne & Béatrice Rey, 2020. "New Results for additive and multiplicative risk apportionment," Post-Print halshs-02930294, HAL.
    2. Gebhard Geiger, 2020. "Conditional non-expected utility preferences induced by mixture of lotteries: a note on the normative invalidity of expected utility theory," Annals of Operations Research, Springer, vol. 289(2), pages 431-448, June.
    3. Jiang, Chonghui & Ma, Yongkai & An, Yunbi, 2013. "International portfolio selection with exchange rate risk: A behavioural portfolio theory perspective," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 648-659.

  9. Yannick Malevergne & Alex Saichev & Didier Sornette, 2010. "Theory of Zipf's Law and Beyond," Post-Print hal-02298139, HAL.

    Cited by:

    1. Rujirutana Mandhachitara & Randall Shannon, 2016. "The Formation and Sustainability of same Product Retail Store Clusters in A Modern Mega City," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 107(5), pages 567-581, December.
    2. Ishikawa, Atushi & 石川, 温 & イシカワ, アツシ & Fujimoto, Shoji & 藤本, 祥二 & フジモト, ショウジ & Watanabe, Tsutomu & 渡辺, 努 & ワタナベ, ツトム & Mizuno, Takayuki & 水野, 貴之 & ミズノ, タカユキ, 2011. "Emergence of power laws with different power-law exponents from reversal quasi-symmetry and Gibrat’s law," Working Paper Series 9, Center for Interfirm Network, Institute of Economic Research, Hitotsubashi University.
    3. Cornelia Metzig & Mirta B. Gordon, 2013. "A Model for Scaling in Firms' Size and Growth Rate Distribution," Papers 1304.4311, arXiv.org, revised Nov 2013.
    4. Hideaki Aoyama & Hiroshi Yoshikawa & Hiroshi Iyetomi & Yoshi Fujiwara, 2010. "Productivity dispersion: facts, theory, and implications," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(1), pages 27-54, June.
    5. Montebruno, Piero & Bennett, Robert J. & van Lieshout, Carry & Smith, Harry, 2019. "A tale of two tails: Do Power Law and Lognormal models fit firm-size distributions in the mid-Victorian era?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 858-875.
    6. Frank Schweitzer & Giorgio Fagiolo & Didier Sornette & Fernando Vega-Redondo & Douglas R. White, "undated". "Economic Networks: What do we know and what do we need to know?," Working Papers CCSS-09-010, ETH Zurich, Chair of Systems Design.
    7. , & Lorenz, Jan & ,, 2016. "Innovation vs. imitation and the evolution of productivity distributions," Theoretical Economics, Econometric Society, vol. 11(3), September.
    8. D. Rybski & S. Buldyrev & S. Havlin & F. Liljeros & H. Makse, 2011. "Communication activity in social networks: growth and correlations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 84(1), pages 147-159, November.
    9. Puga, Diego & Duranton, Gilles, 2019. "Urban growth and its aggregate implications," CEPR Discussion Papers 14215, C.E.P.R. Discussion Papers.
    10. Gordon Mulligan & Mark Partridge & John Carruthers, 2012. "Central place theory and its reemergence in regional science," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(2), pages 405-431, April.
    11. V. I. Yukalov & D. Sornette, 2012. "Statistical Outliers and Dragon-Kings as Bose-Condensed Droplets," Papers 1205.1364, arXiv.org.
    12. Atushi Ishikawa & Shouji Fujimoto & Tsutomu Watanabe & Takayuki Mizuno, 2012. "The Emergence of Different Tail Exponents in the Distributions of Firm Size Variables," UTokyo Price Project Working Paper Series 003, University of Tokyo, Graduate School of Economics, revised Dec 2012.
    13. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    14. A. Saichev & D. Sornette, 2011. "Time-Bridge Estimators of Integrated Variance," Papers 1108.2611, arXiv.org.
    15. Kaldasch, Joachim, 2013. "Evolutionary model of the bank size distribution," Economics Discussion Papers 2013-55, Kiel Institute for the World Economy (IfW Kiel).
    16. Misako Takayasu & Hayafumi Watanabe & Hideki Takayasu, 2013. "Generalised central limit theorems for growth rate distribution of complex systems," Papers 1301.2728, arXiv.org, revised Jan 2014.
    17. Sandro Claudio Lera & Didier Sornette, 2017. "Quantification of the evolution of firm size distributions due to mergers and acquisitions," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-16, August.
    18. Kaldasch, Joachim, 2012. "Evolutionary model of the growth and size of firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(14), pages 3751-3769.
    19. Atushi Ishikawa & Shouji Fujimotoa & Tsutomu Watanabe & Takayuki Mizuno, 2012. "The Emergence of Different Tail Exponents in the Distributions of Firm Size Variables," CARF F-Series CARF-F-297, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

  10. Y. Malevergne & V. Pisarenko & D. Sornette, 2009. "Gibrat’s law for cities: uniformly most powerful unbiased test of the Pareto against the lognormal," Swiss Finance Institute Research Paper Series 09-40, Swiss Finance Institute.

    Cited by:

    1. Rafael González-Val, 2011. "Deviations from Zipf’s Law for American Cities," Urban Studies, Urban Studies Journal Limited, vol. 48(5), pages 1017-1035, April.
    2. González-Val, Rafael, 2010. "A Nonparametric Estimation of the Local Zipf Exponent for all US Cities," MPRA Paper 26720, University Library of Munich, Germany.
    3. Bee, Marco & Riccaboni, Massimo & Schiavo, Stefano, 2017. "Where Gibrat meets Zipf: Scale and scope of French firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 265-275.
    4. Ichiki, Shingo & Nishinari, Katsuhiro, 2015. "Simple stochastic order-book model of swarm behavior in continuous double auction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 304-314.
    5. Arshad, Sidra & Hu, Shougeng & Ashraf, Badar Nadeem, 2019. "Zipf’s law, the coherence of the urban system and city size distribution: Evidence from Pakistan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 87-103.
    6. Gilberto Seravalli, 2016. "Dimensioni e crescita delle citt? in Europa: l?incertezza danneggia soprattutto le citt? medie," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2016(2), pages 91-108.
    7. Josep Roca & Blanca Arellano, 2011. "DOES THE SIZE MATTER? Zipf's Law for cities Revisited," ERSA conference papers ersa11p374, European Regional Science Association.
    8. Aura Reggiani & Peter Nijkamp, 2015. "Did Zipf Anticipate Spatial Connectivity Structures?," Environment and Planning B, , vol. 42(3), pages 468-489, June.
    9. Jakub Growiec & Fabio Pammolli & Massimo Riccaboni, 2020. "Innovation and Corporate Dynamics: A Theoretical Framework," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(1), pages 1-45, March.
    10. Shingo Ichiki & Katsuhiro Nishinari, 2014. "Simple Stochastic Order-Book Model of Swarm Behavior in Continuous Double Auction," Papers 1411.2215, arXiv.org.
    11. Hisano, Ryohei & Mizuno, Takayuki, 2011. "Sales distribution of consumer electronics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 309-318.
    12. Marco Bee, 2020. "On discriminating between lognormal and Pareto tail: A mixture-based approach," DEM Working Papers 2020/9, Department of Economics and Management.
    13. Rafael GONZÀLEZ-VAL, 2012. "Zipf’S Law: Main Issues In Empirical Work," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 36, pages 147-164.

  11. Shengsui HU & Yannick MALEVERGNE & Didier SORNETTE, 2009. "Investors’ Misperception: A Hidden Source of High Markups in the Mutual Fund Industry," Swiss Finance Institute Research Paper Series 09-04, Swiss Finance Institute.

    Cited by:

    1. Semushin, Anton & Parshakov, Petr, 2012. "Data frequency and mutual fund performance measures," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 25(1), pages 95-114.

  12. Yannick Malevergne & B. Rey, 2009. "On cross-risk vulnerability," Post-Print hal-02312539, HAL.

    Cited by:

    1. David Crainich & Louis Eeckhoudt & Olivier Le Courtois, 2017. "Health and portfolio choices : a diffidence approach," Post-Print hal-02311924, HAL.
    2. Christophe Courbage & Guillem Montoliu-Montes & Béatrice Rey, 2018. "How vulnerable is risk aversion to wealth, health and other risks? An empirical analysis for Europe," Working Papers halshs-01935846, HAL.
    3. Christophe Courbage & Guillem Montoliu-Montes & Béatrice Rey, 2018. "How vulnerable is risk aversion to wealth, health and other risks? An empirical analysis for Europe," Working Papers 1827, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    4. Björn Bos & Moritz A. Drupp & Jasper N. Meya & Martin F. Quaas, 2023. "Financial Risk-Taking under Health Risk," CESifo Working Paper Series 10387, CESifo.
    5. David Crainich & Louis Eeckhoudt & Olivier Le Courtois, 2013. "An index of (absolute) correlation aversion: theory and some implications," Working Papers 2013-ECO-12, IESEG School of Management.
    6. Lu Li & Andreas Richter & Petra Steinorth, 2023. "Mental health changes and the willingness to take risks," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 48(1), pages 31-62, March.
    7. Stefani Milovanska-Farrington & Stephen Farrington, 2021. "Discipline, risk, and the endogeneity between financial decisionmaking and health," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 596-636, October.

  13. Yannick Malevergne & Pedro Santa-Clara & Didier Sornette, 2009. "Professor Zipf goes to Wall Street," NBER Working Papers 15295, National Bureau of Economic Research, Inc.

    Cited by:

    1. David Chambers & Elroy Dimson & Christophe Spaenjers, 0. "Art as an Asset: Evidence from Keynes the Collector," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(3), pages 490-520.
    2. Li Gu & Dayong Huang, 2017. "The Effect of the Growth in Labor Hours per Worker on Future Stock Returns, Hiring, and Profitability," Review of Finance, European Finance Association, vol. 21(6), pages 2249-2276.
    3. Xavier Gabaix, 2011. "The Granular Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 79(3), pages 733-772, May.
    4. Jannati, Sima, 2020. "Geographic spillover of dominant firms’ shocks," Journal of Banking & Finance, Elsevier, vol. 118(C).
    5. Alexandre Alles Rodrigues & Fabrizio Casalin, 2022. "Factor investing in Brazil: Diversifying across factor tilts and allocation strategies," Post-Print hal-03968011, HAL.
    6. Belo, Frederico & Lin, Xiaoji, 2012. "Labor Heterogeneity and Asset Prices: The Importance of Skilled Labor," Working Paper Series 2012-25, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    7. Frederico Belo & Xiaoji Lin & Jun Li & Xiaofei Zhao, 2015. "Labor-Force Heterogeneity and Asset Prices: the Importance of Skilled Labor," NBER Working Papers 21487, National Bureau of Economic Research, Inc.
    8. Saman Banafti & Tae-Hwy Lee, 2022. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Papers 2201.06605, arXiv.org, revised Sep 2023.
    9. Dror Y Kenett & Yoash Shapira & Asaf Madi & Sharron Bransburg-Zabary & Gitit Gur-Gershgoren & Eshel Ben-Jacob, 2011. "Index Cohesive Force Analysis Reveals That the US Market Became Prone to Systemic Collapses Since 2002," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.
    10. Sandro Claudio Lera & Didier Sornette, 2017. "Quantification of the evolution of firm size distributions due to mergers and acquisitions," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-16, August.
    11. 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.
    12. Wai Ching Poon & Gareth D. Leeves, 2017. "Research output: evidence from economics departments in the Asia-Pacific region," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 22(4), pages 604-620, October.

  14. A. Saichev & Y. Malevergne & D. Sornette, 2008. "Theory of Zipf's Law and of General Power Law Distributions with Gibrat's law of Proportional Growth," Papers 0808.1828, arXiv.org.

    Cited by:

    1. Petra Štamfestová & Lukáš Sobíšek & Jiří Hnilica, 2023. "Firm Size Distribution in the Central European Context," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 151-175.
    2. G. A. Kohring, 2009. "Complex Dependencies In Large Software Systems," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(06), pages 565-581.
    3. Montebruno, Piero & Bennett, Robert J. & van Lieshout, Carry & Smith, Harry, 2019. "A tale of two tails: Do Power Law and Lognormal models fit firm-size distributions in the mid-Victorian era?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 858-875.
    4. Domingo Docampo & Lawrence Cram, 2017. "Academic performance and institutional resources: a cross-country analysis of research universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 739-764, February.
    5. M Ángeles Serrano & Alessandro Flammini & Filippo Menczer, 2009. "Modeling Statistical Properties of Written Text," PLOS ONE, Public Library of Science, vol. 4(4), pages 1-8, April.

  15. Jerome Coulon & Yannick Malevergne, 2008. "Heterogeneous expectations and long range correlation of the volatility of asset returns," Papers 0808.1538, arXiv.org.

    Cited by:

    1. Samuel E. Vazquez, 2009. "Scale Invariance, Bounded Rationality and Non-Equilibrium Economics," Papers 0902.3840, arXiv.org.

  16. Y. Malevergne & D. Sornette, 2007. "A two-Factor Asset Pricing Model and the Fat Tail Distribution of Firm Sizes," Papers physics/0702027, arXiv.org.

    Cited by:

    1. Zoltan Kuscsik & Denis Horvath, 2007. "Statistical properties of agent-based market area model," Papers 0710.0459, arXiv.org.

  17. Y. Malevergne & D. Sornette, 2006. "Self-Consistent Asset Pricing Models," Papers physics/0608284, arXiv.org.

    Cited by:

    1. Krzysztof Urbanowicz & Peter Richmond & Janusz A. Holyst, 2006. "Risk evaluation with enhaced covariance matrix," Papers physics/0612059, arXiv.org, revised May 2007.
    2. Dror Y Kenett & Yoash Shapira & Asaf Madi & Sharron Bransburg-Zabary & Gitit Gur-Gershgoren & Eshel Ben-Jacob, 2011. "Index Cohesive Force Analysis Reveals That the US Market Became Prone to Systemic Collapses Since 2002," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.

  18. Yannick Malevergne & Didier Sornette, 2006. "Extreme Financial Risks : From Dependence to Risk Management," Post-Print hal-02298069, HAL.

    Cited by:

    1. Li-Xin Wang, 2014. "Dynamical Models of Stock Prices Based on Technical Trading Rules Part I: The Models," Papers 1401.1888, arXiv.org, revised Feb 2016.
    2. Alves, L.G.A. & Ribeiro, H.V. & Lenzi, E.K. & Mendes, R.S., 2014. "Empirical analysis on the connection between power-law distributions and allometries for urban indicators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 175-182.
    3. Nuerxiati Abudurexiti & Kai He & Dongdong Hu & Svetlozar T. Rachev & Hasanjan Sayit & Ruoyu Sun, 2021. "Portfolio analysis with mean-CVaR and mean-CVaR-skewness criteria based on mean-variance mixture models," Papers 2111.04311, arXiv.org, revised Feb 2023.
    4. Peng Liu & Yanyan Zheng, 2022. "Precision measurement of the return distribution property of the Chinese stock market index," Papers 2209.08521, arXiv.org, revised Nov 2023.
    5. Fry, John, 2014. "Multivariate bubbles and antibubbles," MPRA Paper 56081, University Library of Munich, Germany.
    6. Damien Bosc & Alfred Galichon, 2014. "Extreme dependence for multivariate data," SciencePo Working papers Main hal-03470461, HAL.
    7. Donatien Hainaut & Renaud MacGilchrist, 2012. "Strategic asset allocation with switching dependence," Annals of Finance, Springer, vol. 8(1), pages 75-96, February.
    8. Diana, Tony, 2011. "Improving schedule reliability based on copulas: An application to five of the most congested US airports," Journal of Air Transport Management, Elsevier, vol. 17(5), pages 284-287.
    9. Dietmar Pfeifer & Olena Ragulina, 2018. "Generating VaR Scenarios under Solvency II with Product Beta Distributions," Risks, MDPI, vol. 6(4), pages 1-15, October.
    10. Hernández-Ramírez, E. & del Castillo-Mussot, M. & Hernández-Casildo, J., 2021. "World per capita gross domestic product measured nominally and across countries with purchasing power parity: Stretched exponential or Boltzmann–Gibbs distribution?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    11. Kozłowska, M. & Denys, M. & Wiliński, M. & Link, G. & Gubiec, T. & Werner, T.R. & Kutner, R. & Struzik, Z.R., 2016. "Dynamic bifurcations on financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 126-142.
    12. Rémy Chicheportiche & Jean-Philippe Bouchaud, 2012. "The Joint Distribution Of Stock Returns Is Not Elliptical," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 1-23.
    13. Tang, Qihe & Yang, Fan, 2012. "On the Haezendonck–Goovaerts risk measure for extreme risks," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 217-227.
    14. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.
    15. Hernández-Lobato, José Miguel & Suárez, Alberto, 2011. "Semiparametric bivariate Archimedean copulas," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2038-2058, June.
    16. Sornette, Didier & Woodard, Ryan & Yan, Wanfeng & Zhou, Wei-Xing, 2013. "Clarifications to questions and criticisms on the Johansen–Ledoit–Sornette financial bubble model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4417-4428.
    17. Didier Sornette & Wei-Xing Zhou, 2005. "Importance of Positive Feedbacks and Over-confidence in a Self-Fulfilling Ising Model of Financial Markets," Papers cond-mat/0503607, arXiv.org, revised Mar 2005.
    18. Nelsen, Roger B. & Quesada-Molina, José Juan & Rodri­guez-Lallena, José Antonio & Úbeda-Flores, Manuel, 2008. "On the construction of copulas and quasi-copulas with given diagonal sections," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 473-483, April.
    19. Wiliński, M. & Sienkiewicz, A. & Gubiec, T. & Kutner, R. & Struzik, Z.R., 2013. "Structural and topological phase transitions on the German Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5963-5973.
    20. Alexandru V. Asimit & Raluca Vernic & Riċardas Zitikis, 2013. "Evaluating Risk Measures and Capital Allocations Based on Multi-Losses Driven by a Heavy-Tailed Background Risk: The Multivariate Pareto-II Model," Risks, MDPI, vol. 1(1), pages 1-20, March.
    21. Alfred Galichon & Damien Bosc, 2010. "Extreme dependence for multivariate data," Working Papers hal-03588294, HAL.
    22. 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.
    23. F. N. M. de Sousa Filho & J. N. Silva & M. A. Bertella & E. Brigatti, 2020. "The leverage effect and other stylized facts displayed by Bitcoin returns," Papers 2004.05870, arXiv.org, revised Jan 2021.
    24. M. Wili'nski & A. Sienkiewicz & T. Gubiec & R. Kutner & Z. R. Struzik, 2013. "Structural and topological phase transitions on the German Stock Exchange," Papers 1301.2530, arXiv.org, revised Jul 2013.
    25. Haas, Armin & Onischka, Mathias & Fucik, Markus, 2013. "Black swans, dragon kings, and Bayesian risk management," Economics Discussion Papers 2013-11, Kiel Institute for the World Economy (IfW Kiel).
    26. Sandro Claudio Lera & Didier Sornette, 2015. "Currency target zone modeling: An interplay between physics and economics," Papers 1508.04754, arXiv.org, revised Oct 2015.
    27. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 187-208.
    28. Li-Xin Wang, 2014. "Dynamical Models of Stock Prices Based on Technical Trading Rules Part II: Analysis of the Models," Papers 1401.1891, arXiv.org, revised Feb 2016.
    29. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions. II," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 23(3), pages 98-132.
    30. Mateusz Denys & Maciej Jagielski & Tomasz Gubiec & Ryszard Kutner & H. Eugene Stanley, 2015. "Universality of market superstatistics," Papers 1509.06315, arXiv.org.
    31. Yannick Malevergne & Vladilen Pisarenko & Didier Sornette, 2006. "On the Power of Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) Estimators for Empirical Distributions of Stock Returns," Post-Print hal-02311834, HAL.
    32. Reiichiro Kawai, 2009. "A multivariate Levy process model with linear correlation," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 597-606.
    33. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
    34. Zhan Liu & Gang-Zhi Fan & Kian Lim, 2009. "Extreme Events and the Copula Pricing of Commercial Mortgage-Backed Securities," The Journal of Real Estate Finance and Economics, Springer, vol. 38(3), pages 327-349, April.
    35. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    36. Martin Eling & Simone Farinelli & Damiano Rossello & Luisa Tibiletti, 2010. "Skewness in hedge funds returns: classical skewness coefficients vs Azzalini's skewness parameter," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 6(4), pages 290-304, September.
    37. Christian Genest & Michel Gendron & Michaël Bourdeau-Brien, 2009. "The Advent of Copulas in Finance," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 609-618.
    38. Stefan Kassberger & Rüdiger Kiesel, 2006. "A fully parametric approach to return modelling and risk management of hedge funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(4), pages 472-491, December.
    39. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical distributions of Chinese stock returns at different microscopic timescales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 495-502.
    40. T. Maillart & D. Sornette, 2010. "Heavy-tailed distribution of cyber-risks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 357-364, June.
    41. Alfred Galichon & Damien Bosc, 2010. "Extreme dependence for multivariate data," SciencePo Working papers Main hal-03588294, HAL.
    42. Liu, Wei-han, 2018. "Hidden Markov model analysis of extreme behaviors of foreign exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1007-1019.
    43. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    44. León, Carlos & Leiton, Karen & Pérez, Jhonatan, 2014. "Extracting the sovereigns’ CDS market hierarchy: A correlation-filtering approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 407-420.
    45. Wei-Xing Zhou, 2009. "Finite-size effect and the components of multifractality in financial volatility," Papers 0912.4782, arXiv.org.
    46. Wei-han Liu, 2013. "Detecting structural breaks in tail behaviour -- from the perspective of fitting the generalized Pareto distribution," Applied Economics, Taylor & Francis Journals, vol. 45(10), pages 1273-1286, April.
    47. Franzke, Christian L.E., 2021. "Towards the development of economic damage functions for weather and climate extremes," Ecological Economics, Elsevier, vol. 189(C).
    48. Leonidas Sandoval Junior & Italo De Paula Franca, 2011. "Shocks in financial markets, price expectation, and damped harmonic oscillators," Papers 1103.1992, arXiv.org, revised Sep 2011.
    49. Alexander Saichev & Thomas Maillart & Didier Sornette, 2013. "Hierarchy of temporal responses of multivariate self-excited epidemic processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(4), pages 1-19, April.
    50. Daniel Berg, 2009. "Copula goodness-of-fit testing: an overview and power comparison," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 675-701.
    51. A. Sienkiewicz & T. Gubiec & R. Kutner & Z. R. Struzik, 2013. "Dynamic structural and topological phase transitions on the Warsaw Stock Exchange: A phenomenological approach," Papers 1301.6506, arXiv.org.
    52. Mu, Guo-Hua & Zhou, Wei-Xing, 2008. "Relaxation dynamics of aftershocks after large volatility shocks in the SSEC index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5211-5218.
    53. Stefan Hochrainer, 2008. "Reservefonds gegen Naturkatastrophen auf nationaler und europäischer Ebene," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 77(4), pages 69-79.
    54. John Fry & McMillan David, 2015. "Stochastic modelling for financial bubbles and policy," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1002152-100, December.
    55. Osvaldo C. Silva Filho & Flavio A. Ziegelmann & Michael J. Dueker, 2014. "Assessing dependence between financial market indexes using conditional time-varying copulas: applications to Value at Risk (VaR)," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2155-2170, December.
    56. Peter Marko & Petr Svarc, 2008. "Firms formation and growth in the model with heterogeneous agents and monitoring," Working Papers IES 2008/31, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2008.
    57. Jos'e Vin'icius de Miranda Cardoso & Jiaxi Ying & Daniel Perez Palomar, 2020. "Algorithms for Learning Graphs in Financial Markets," Papers 2012.15410, arXiv.org.
    58. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    59. Volovoi, Vitali, 2013. "Universal failure model for multi-unit systems with shared functionality," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 141-149.
    60. Marcela de Marillac Carvalho & Luiz Otávio de Oliveira Pala & Gabriel Rodrigo Gomes Pessanha & Thelma Sáfadi, 2021. "Asymmetric dependence of intraday frequency components in the Brazilian stock market," SN Business & Economics, Springer, vol. 1(6), pages 1-18, June.
    61. Leonidas Sandoval Junior & Italo De Paula Franca, 2011. "Correlation of financial markets in times of crisis," Papers 1102.1339, arXiv.org, revised Mar 2011.
    62. Damien Bosc & Alfred Galichon, 2014. "Extreme dependence for multivariate data," Post-Print hal-03470461, HAL.
    63. Rehman, Mobeen Ur & Katsiampa, Paraskevi & Zeitun, Rami & Vo, Xuan Vinh, 2023. "Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies," Emerging Markets Review, Elsevier, vol. 55(C).
    64. Toan Luu Duc Huynh, 2019. "Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    65. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    66. Veni Arakelian & Shatha Qamhieh Hashem, 2020. "The Leaders, the Laggers, and the “Vulnerables”," Risks, MDPI, vol. 8(1), pages 1-32, March.
    67. Vladimir Filimonov & Didier Sornette, 2014. "Power law scaling and "Dragon-Kings" in distributions of intraday financial drawdowns," Papers 1407.5037, arXiv.org, revised Apr 2015.
    68. Li-Xin Wang, 2014. "Gaussian-Chain Filters for Heavy-Tailed Noise with Application to Detecting Big Buyers and Big Sellers in Stock Market," Papers 1405.2220, arXiv.org.

  19. Yannick Malevergne & Ali Chabaane & Jean-Paul Laurent & Françoise Turpin, 2006. "Alternative Risk Measures for Alternative Investments," Post-Print hal-02311832, HAL.

    Cited by:

    1. H. Fink & S. Geissel & J. Herbinger & F. T. Seifried, 2019. "Portfolio Optimization with Optimal Expected Utility Risk Measures," Working Paper Series 2019-07, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    2. Thapar, Rishi & Minsky, Bernard & Obradovic, M & Tang, Qi, 2009. "Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation," MPRA Paper 17099, University Library of Munich, Germany.
    3. El Kalak, Izidin & Azevedo, Alcino & Hudson, Robert, 2016. "Reviewing the hedge funds literature I: Hedge funds and hedge funds' managerial characteristics," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 85-97.
    4. Adam, Alexandre & Houkari, Mohamed & Laurent, Jean-Paul, 2008. "Spectral risk measures and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1870-1882, September.
    5. S. Geissel & H. Graf & J. Herbinger & F. T. Seifried, 2022. "Portfolio optimization with optimal expected utility risk measures," Annals of Operations Research, Springer, vol. 309(1), pages 59-77, February.
    6. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.

  20. Yannick Malevergne & Vladilen Pisarenko & Didier Sornette, 2006. "On the Power of Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) Estimators for Empirical Distributions of Stock Returns," Post-Print hal-02311834, HAL.

    Cited by:

    1. V. F. Pisarenko & D. Sornette, 2004. "New statistic for financial return distributions: power-law or exponential?," Papers physics/0403075, arXiv.org.
    2. Montshioa, Keitumetse & Muteba Mwamba, John Weirstrass & Bonga-Bonga, Lumengo, 2021. "Asset allocation in extreme market conditions: a comparative analysis between developed and emerging economies," MPRA Paper 106248, University Library of Munich, Germany.
    3. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical distributions of Chinese stock returns at different microscopic timescales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 495-502.
    4. Wei-Zhen Li & Jin-Rui Zhai & Zhi-Qiang Jiang & Gang-Jin Wang & Wei-Xing Zhou, 2020. "Predicting tail events in a RIA-EVT-Copula framework," Papers 2004.03190, arXiv.org, revised Apr 2020.
    5. George Haiman, 2018. "Level Hitting Probabilities and Extremal Indexes for Some Particular Dynamical Systems," Methodology and Computing in Applied Probability, Springer, vol. 20(2), pages 553-562, June.
    6. Matteo Gentilucci & Alessandro Rossi & Niccolò Pelagagge & Domenico Aringoli & Maurizio Barbieri & Gilberto Pambianchi, 2023. "GEV Analysis of Extreme Rainfall: Comparing Different Time Intervals to Analyse Model Response in Terms of Return Levels in the Study Area of Central Italy," Sustainability, MDPI, vol. 15(15), pages 1-25, July.
    7. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    8. Salhi, Khaled & Deaconu, Madalina & Lejay, Antoine & Champagnat, Nicolas & Navet, Nicolas, 2016. "Regime switching model for financial data: Empirical risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 148-157.
    9. José L. B. Fernandes & Augusto Hasman & Juan Ignacio Peña, 2006. "Risk Premium: Insights Over The Threshold," Working Papers Series 126, Central Bank of Brazil, Research Department.
    10. Bonga-Bonga, Lumengo & Montshioa, Keitumetse, 2024. "Navigating extreme market fluctuations: asset allocation strategies in developed vs. emerging economies," MPRA Paper 119910, University Library of Munich, Germany.
    11. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    12. Rakhee Dinubhai Patel & Frederic Paik Schoenberg, 2011. "A graphical test for local self-similarity in univariate data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2547-2562, January.

  21. Yannick Malevergne & Vladilen Pisarenko & Didier Sornette, 2005. "Empirical Distributions of Stock Returns : Between the Stretched Exponential and the Power Law?," Post-Print hal-02311833, HAL.

    Cited by:

    1. Lucas Fievet & Zal`an Forr`o & Peter Cauwels & Didier Sornette, 2014. "Forecasting future oil production in Norway and the UK: a general improved methodology," Papers 1407.3652, arXiv.org.
    2. Y. Malevergne & V. Pisarenko & D. Sornette, 2006. "The modified weibull distribution for asset returns: reply," Quantitative Finance, Taylor & Francis Journals, vol. 6(6), pages 451-451.
    3. Derksen, M. & Kleijn, B. & de Vilder, R., 2022. "Heavy tailed distributions in closing auctions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    4. Mendes, Rui Vilela & Oliveira, Maria J., 2008. "A Data-Reconstructed Fractional Volatility Model," Economics Discussion Papers 2008-22, Kiel Institute for the World Economy (IfW Kiel).
    5. Bertrand Groslambert & Wan-Ni Lai, 2020. "Ranking tail risk across international stock markets," Economics Bulletin, AccessEcon, vol. 40(2), pages 1756-1768.
    6. Pablo Su'arez-Garc'ia & David G'omez-Ullate, 2012. "Scaling, stability and distribution of the high-frequency returns of the IBEX35 index," Papers 1208.0317, arXiv.org.
    7. Hernández-Ramírez, E. & del Castillo-Mussot, M. & Hernández-Casildo, J., 2021. "World per capita gross domestic product measured nominally and across countries with purchasing power parity: Stretched exponential or Boltzmann–Gibbs distribution?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    8. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "The stylized facts of prediction markets: Analysis of price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 159-170.
    9. De Domenico, Federica & Livan, Giacomo & Montagna, Guido & Nicrosini, Oreste, 2023. "Modeling and simulation of financial returns under non-Gaussian distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    10. Nassim Dehouche, 2021. "Scale matters: The daily, weekly and monthly volatility and predictability of Bitcoin, Gold, and the S&P 500," Papers 2103.00395, arXiv.org.
    11. Gao-Feng Gu & Wei-Xing Zhou, 2006. "Statistical properties of daily ensemble variables in the Chinese stock markets," Papers physics/0603147, arXiv.org.
    12. Saralees Nadarajah & Samuel Kotz, 2006. "The modified Weibull distribution for asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 6(6), pages 449-449.
    13. Didier Sornette & Wei-Xing Zhou, 2005. "Importance of Positive Feedbacks and Over-confidence in a Self-Fulfilling Ising Model of Financial Markets," Papers cond-mat/0503607, arXiv.org, revised Mar 2005.
    14. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    15. Ethan Ratliff-Crain & Colin M. Van Oort & James Bagrow & Matthew T. K. Koehler & Brian F. Tivnan, 2023. "Revisiting Cont's Stylized Facts for Modern Stock Markets," Papers 2311.07738, arXiv.org, revised May 2024.
    16. 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.
    17. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "Statistical properties of volume and calendar effects in prediction markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1150-1160.
    18. Andrew Balthrop, 2016. "Power laws in oil and natural gas production," Empirical Economics, Springer, vol. 51(4), pages 1521-1539, December.
    19. Federica De Domenico & Giacomo Livan & Guido Montagna & Oreste Nicrosini, 2023. "Modeling and Simulation of Financial Returns under Non-Gaussian Distributions," Papers 2302.02769, arXiv.org.
    20. Ekaterina Morozova & Vladimir Panov, 2021. "Extreme Value Analysis for Mixture Models with Heavy-Tailed Impurity," Mathematics, MDPI, vol. 9(18), pages 1-24, September.
    21. 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.
    22. Filimonov, Vladimir & Sornette, Didier, 2015. "Power law scaling and “Dragon-Kings” in distributions of intraday financial drawdowns," Chaos, Solitons & Fractals, Elsevier, vol. 74(C), pages 27-45.
    23. Kim Ristolainen, 2024. "Narrative triggers of information sensitivity," Quantitative Finance, Taylor & Francis Journals, vol. 24(3-4), pages 499-520, April.
    24. M. Derksen & B. Kleijn & R. de Vilder, 2020. "Heavy tailed distributions in closing auctions," Papers 2012.10145, arXiv.org.
    25. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    26. Andrew T. Balthrop, 2021. "Gibrat’s law in the trucking industry," Empirical Economics, Springer, vol. 61(1), pages 339-354, July.
    27. Pisarenko, V. & Sornette, D., 2006. "New statistic for financial return distributions: Power-law or exponential?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 387-400.
    28. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical distributions of Chinese stock returns at different microscopic timescales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 495-502.
    29. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    30. Gzyl, Henryk & ter Horst, Enrique & Molina, Germán, 2019. "A model-free, non-parametric method for density determination, with application to asset returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 210-221.
    31. Jevgeni Tarassov & Nicolas Houli'e, 2023. "Bitcoin: A life in crises," Papers 2304.09939, arXiv.org.
    32. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    33. Ramit Sawhney & Shivam Agarwal & Vivek Mittal & Paolo Rosso & Vikram Nanda & Sudheer Chava, 2022. "Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models," Papers 2206.06320, arXiv.org.
    34. Bax, Karoline & Sahin, Özge & Czado, Claudia & Paterlini, Sandra, 2023. "ESG, risk, and (tail) dependence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    35. Pablo Su'arez-Garc'ia & David G'omez-Ullate, 2013. "Multifractality and long memory of a financial index," Papers 1306.0490, arXiv.org.
    36. Makoto Nirei & Theodoros Stamatiou & Vladyslav Sushko, 2012. "Stochastic Herding in Financial Markets Evidence from Institutional Investor Equity Portfolios," BIS Working Papers 371, Bank for International Settlements.
    37. Saralees Nadarajah, 2012. "Models for stock returns," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 411-424, February.
    38. Suárez-García, Pablo & Gómez-Ullate, David, 2013. "Scaling, stability and distribution of the high-frequency returns of the Ibex35 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1409-1417.
    39. Naumoski, Aleksandar & Gaber, Stevan & Gaber-Naumoska, Vasilka, 2017. "Empirical Distribution Of Stock Returns Of Southeast European Emerging Markets," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 8(2), pages 67-77.
    40. Sosa-Correa, William O. & Ramos, Antônio M.T. & Vasconcelos, Giovani L., 2018. "Investigation of non-Gaussian effects in the Brazilian option market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 525-539.
    41. Sandro Claudio Lera & Didier Sornette, 2017. "GDP growth rates as confined L\'evy flights," Papers 1709.05594, arXiv.org.
    42. Fiévet, L. & Forró, Z. & Cauwels, P. & Sornette, D., 2015. "A general improved methodology to forecasting future oil production: Application to the UK and Norway," Energy, Elsevier, vol. 79(C), pages 288-297.
    43. Jan-Christian Gerlach & Jerome Kreuser & Didier Sornette, 2020. "Awareness of crash risk improves Kelly strategies in simulated financial time series," Papers 2004.09368, arXiv.org.
    44. Stijn De Backer & Luis E. C. Rocha & Jan Ryckebusch & Koen Schoors, 2024. "On the potential of quantum walks for modeling financial return distributions," Papers 2403.19502, arXiv.org.
    45. Vladimir Filimonov & Didier Sornette, 2014. "Power law scaling and "Dragon-Kings" in distributions of intraday financial drawdowns," Papers 1407.5037, arXiv.org, revised Apr 2015.
    46. Rakhee Dinubhai Patel & Frederic Paik Schoenberg, 2011. "A graphical test for local self-similarity in univariate data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2547-2562, January.
    47. Karoline Bax & Ozge Sahin & Claudia Czado & Sandra Paterlini, 2021. "ESG, Risk, and (Tail) Dependence," Papers 2105.07248, arXiv.org, revised Nov 2021.
    48. Marc Ditzhaus & Daniel Gaigall, 2022. "Testing marginal homogeneity in Hilbert spaces with applications to stock market returns," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 749-770, September.
    49. Ko, Bonggyun & Song, Jae Wook, 2018. "A simple analytics framework for evaluating mean escape time in different term structures with stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 398-412.

  22. Yannick Malevergne & Didier Sornette, 2004. "How to account for extreme co-movements between individual stocks and the market," Post-Print hal-02312885, HAL.

    Cited by:

    1. Y. Malevergne & D. Sornette, 2003. "VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions," Papers physics/0301009, arXiv.org.
    2. Maarten R C van Oordt & Chen Zhou, 2019. "Estimating Systematic Risk under Extremely Adverse Market Conditions," Journal of Financial Econometrics, Oxford University Press, vol. 17(3), pages 432-461.
    3. Avramidis, Panagiotis & Pasiouras, Fotios, 2015. "Calculating systemic risk capital: A factor model approach," Journal of Financial Stability, Elsevier, vol. 16(C), pages 138-150.
    4. Bücher Axel, 2014. "A note on nonparametric estimation of bivariate tail dependence," Statistics & Risk Modeling, De Gruyter, vol. 31(2), pages 151-162, June.
    5. Ranoua Bouchouicha, 2010. "Dépendance entre risques extrêmes : Application aux Hedge Funds," Working Papers 1013, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    6. Akanksha Jalan & Roman Matkovskyy & Larisa Yarovaya, 2021. "“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic," Post-Print hal-03512893, HAL.
    7. Y. Malevergne & D. Sornette, 2002. "Hedging Extreme Co-Movements," Papers cond-mat/0205636, arXiv.org.
    8. Roman Matkovskyy, 2020. "A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula," Post-Print hal-03163619, HAL.
    9. Aguilar, Mike & Hill, Jonathan B., 2015. "Robust score and portmanteau tests of volatility spillover," Journal of Econometrics, Elsevier, vol. 184(1), pages 37-61.

  23. Yannick Malevergne & Didier Sornette, 2004. "Value-at-Risk-efficient portfolios for class of super- and sub-exponentially decaying assets return distributions," Post-Print hal-02312887, HAL.

    Cited by:

    1. Chen, Qian & Gerlach, Richard H., 2013. "The two-sided Weibull distribution and forecasting financial tail risk," International Journal of Forecasting, Elsevier, vol. 29(4), pages 527-540.
    2. Saralees Nadarajah & Samuel Kotz, 2006. "The modified Weibull distribution for asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 6(6), pages 449-449.
    3. Vicente Medina Martínez & Ángel Pardo Tornero, 2012. "Stylized facts of CO2 returns," Working Papers. Serie AD 2012-14, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    4. Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.
    5. Chao Wang & Qian Chen & Richard Gerlach, 2017. "Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution," Papers 1707.03715, arXiv.org.

  24. Yannick Malevergne & Didier Sornette, 2004. "Collective origin of the coexistence of apparent random matrix theory noise and of factors in large sample correlation matrices," Post-Print hal-02312894, HAL.

    Cited by:

    1. Antti J. Tanskanen & Jani Lukkarinen & Kari Vatanen, 2016. "Random selection of factors preserves the correlation structure in a linear factor model to a high degree," Papers 1604.05896, arXiv.org, revised Dec 2018.
    2. Thomas Conlon & Heather J. Ruskin & Martin Crane, 2010. "Cross-Correlation Dynamics in Financial Time Series," Papers 1002.0321, arXiv.org.
    3. Anshul Verma & Riccardo Junior Buonocore & Tiziana di Matteo, 2017. "A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering," Papers 1712.02138, arXiv.org, revised May 2018.
    4. Eterovic, Nicolas A. & Eterovic, Dalibor S., 2013. "Separating the wheat from the chaff: Understanding portfolio returns in an emerging market," Emerging Markets Review, Elsevier, vol. 16(C), pages 145-169.
    5. Stephan Süss, 2012. "The pricing of idiosyncratic risk: evidence from the implied volatility distribution," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(2), pages 247-267, June.
    6. Martins, André C.R., 2007. "Non-stationary correlation matrices and noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 552-558.
    7. Bommarito, Michael J. & Duran, Ahmet, 2018. "Spectral analysis of time-dependent market-adjusted return correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 273-282.
    8. Ñíguez, Trino-Manuel & Perote, Javier, 2016. "Multivariate moments expansion density: Application of the dynamic equicorrelation model," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 216-232.
    9. Dalibor Eterovic & Nicolas Eterovic, 2012. "Separating the Wheat from the Chaff: Understanding Portfolio Returns in an Emerging Market," Working Papers wp_025, Adolfo Ibáñez University, School of Government.
    10. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    11. Antti J Tanskanen & Jani Lukkarinen & Kari Vatanen, 2018. "Random selection of factors preserves the correlation structure in a linear factor model to a high degree," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-22, December.

  25. Y. Malevergne & D. Sornette, 2003. "VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions," Papers physics/0301009, arXiv.org.

    Cited by:

    1. Y. Malevergne & V. Pisarenko & D. Sornette, 2006. "The modified weibull distribution for asset returns: reply," Quantitative Finance, Taylor & Francis Journals, vol. 6(6), pages 451-451.
    2. Chen, Qian & Gerlach, Richard H., 2013. "The two-sided Weibull distribution and forecasting financial tail risk," International Journal of Forecasting, Elsevier, vol. 29(4), pages 527-540.
    3. Saralees Nadarajah & Samuel Kotz, 2006. "The modified Weibull distribution for asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 6(6), pages 449-449.
    4. Ibragimov, Rustam & Walden, Johan, 2008. "Portfolio diversification under local and moderate deviations from power laws," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 594-599, April.
    5. Vicente Medina Martínez & Ángel Pardo Tornero, 2012. "Stylized facts of CO2 returns," Working Papers. Serie AD 2012-14, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. Roger Bowden, 2006. "The generalized value at risk admissible set: constraint consistency and portfolio outcomes," Quantitative Finance, Taylor & Francis Journals, vol. 6(2), pages 159-171.
    7. Walden, Johan & Ibragimov, Rustam, 2008. "Portfolio Diversification under Local and Moderate Deviations from Power Laws," Scholarly Articles 2640586, Harvard University Department of Economics.
    8. C. James Hueng & Ruey Yau, 2006. "Investor preferences and portfolio selection: is diversification an appropriate strategy?," Quantitative Finance, Taylor & Francis Journals, vol. 6(3), pages 255-271.
    9. Chao Wang & Qian Chen & Richard Gerlach, 2017. "Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution," Papers 1707.03715, arXiv.org.
    10. Jan-Christian Gerlach & Jerome Kreuser & Didier Sornette, 2020. "Awareness of crash risk improves Kelly strategies in simulated financial time series," Papers 2004.09368, arXiv.org.

  26. Y. Malevergne & V. F. Pisarenko & D. Sornette, 2003. "Empirical Distributions of Log-Returns: between the Stretched Exponential and the Power Law?," Papers physics/0305089, arXiv.org.

    Cited by:

    1. Y. Malevergne & V. Pisarenko & D. Sornette, 2006. "The modified weibull distribution for asset returns: reply," Quantitative Finance, Taylor & Francis Journals, vol. 6(6), pages 451-451.
    2. Mendes, Rui Vilela & Oliveira, Maria J., 2008. "A Data-Reconstructed Fractional Volatility Model," Economics Discussion Papers 2008-22, Kiel Institute for the World Economy (IfW Kiel).
    3. Saralees Nadarajah & Samuel Kotz, 2006. "The modified Weibull distribution for asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 6(6), pages 449-449.
    4. Didier Sornette & Wei-Xing Zhou, 2005. "Importance of Positive Feedbacks and Over-confidence in a Self-Fulfilling Ising Model of Financial Markets," Papers cond-mat/0503607, arXiv.org, revised Mar 2005.
    5. V. F. Pisarenko & D. Sornette, 2004. "New statistic for financial return distributions: power-law or exponential?," Papers physics/0403075, arXiv.org.
    6. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    7. Guilmi, Corrado Di & Gallegati, Mauro & Ormerod, Paul, 2004. "Scaling invariant distributions of firms’ exit in OECD countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 267-273.
    8. Jan-Christian Gerlach & Jerome Kreuser & Didier Sornette, 2020. "Awareness of crash risk improves Kelly strategies in simulated financial time series," Papers 2004.09368, arXiv.org.

  27. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Papers cond-mat/0203166, arXiv.org.

    Cited by:

    1. Y. Malevergne & D. Sornette, 2002. "Hedging Extreme Co-Movements," Papers cond-mat/0205636, arXiv.org.
    2. Harry. M Kat, 2002. "The Dangers of Using Correlation to Measure Dependence," ICMA Centre Discussion Papers in Finance icma-dp2002-23, Henley Business School, University of Reading.
    3. Leonidas Sandoval Junior & Italo De Paula Franca, 2011. "Shocks in financial markets, price expectation, and damped harmonic oscillators," Papers 1103.1992, arXiv.org, revised Sep 2011.
    4. Y. Malevergne & V. F. Pisarenko & D. Sornette, 2003. "Empirical Distributions of Log-Returns: between the Stretched Exponential and the Power Law?," Papers physics/0305089, arXiv.org.
    5. Leonidas Sandoval Junior & Italo De Paula Franca, 2011. "Correlation of financial markets in times of crisis," Papers 1102.1339, arXiv.org, revised Mar 2011.

  28. Y. Malevergne & D. Sornette, 2002. "Collective Origin of the Coexistence of Apparent RMT Noise and Factors in Large Sample Correlation Matrices," Papers cond-mat/0210115, arXiv.org.

    Cited by:

    1. Thomas Conlon & Heather J. Ruskin & Martin Crane, 2010. "Cross-Correlation Dynamics in Financial Time Series," Papers 1002.0321, arXiv.org.
    2. Dalibor Eterovic & Nicolas Eterovic, 2012. "Separating the Wheat from the Chaff: Understanding Portfolio Returns in an Emerging Market," Working Papers wp_025, Adolfo Ibáñez University, School of Government.

  29. Y. Malevergne & D. Sornette, 2002. "Multi-Moments Method for Portfolio Management: Generalized Capital Asset Pricing Model in Homogeneous and Heterogeneous markets," Papers cond-mat/0207475, arXiv.org.

    Cited by:

    1. Y. Malevergne & D. Sornette, 2003. "VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions," Papers physics/0301009, arXiv.org.
    2. Ba Chu, 2012. "Approximation of Asymmetric Multivariate Return Distributions," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 19(3), pages 293-318, September.
    3. Yannick Malevergne & Didier Sornette, 2007. "Self-consistent asset pricing models," Post-Print hal-02311789, HAL.
    4. Rockafellar, R. Tyrrell & Uryasev, Stan & Zabarankin, Michael, 2006. "Master funds in portfolio analysis with general deviation measures," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 743-778, February.
    5. Y. Malevergne & V. F. Pisarenko & D. Sornette, 2003. "Empirical Distributions of Log-Returns: between the Stretched Exponential and the Power Law?," Papers physics/0305089, arXiv.org.

  30. Yannick Malevergne & Didier Sornette, 2002. "Minimizing extremes," Post-Print hal-02312889, HAL.

    Cited by:

    1. Y. Malevergne & D. Sornette, 2003. "VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions," Papers physics/0301009, arXiv.org.
    2. Ranoua Bouchouicha, 2010. "Dépendance entre risques extrêmes : Application aux Hedge Funds," Working Papers 1013, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.

  31. Y. Malevergne & D. Sornette, 2002. "Tail Dependence of Factor Models," Papers cond-mat/0202356, arXiv.org.

    Cited by:

    1. Einmahl, J.H.J. & Krajina, A. & Segers, J., 2011. "An M-Estimator for Tail Dependence in Arbitrary Dimensions," Discussion Paper 2011-013, Tilburg University, Center for Economic Research.
    2. Pourkhanali, Armin & Kim, Jong-Min & Tafakori, Laleh & Fard, Farzad Alavi, 2016. "Measuring systemic risk using vine-copula," Economic Modelling, Elsevier, vol. 53(C), pages 63-74.
    3. Krajina, A., 2010. "An M-estimator of multivariate tail dependence," Other publications TiSEM 66518e07-db9a-4446-81be-c, Tilburg University, School of Economics and Management.
    4. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Papers cond-mat/0203166, arXiv.org.

  32. D. Sornette & Y. Malevergne & J. F. Muzy, 2002. "Volatility fingerprints of large shocks: Endogeneous versus exogeneous," Papers cond-mat/0204626, arXiv.org.

    Cited by:

    1. A. Johansen & D. Sornette, 2002. "Endogenous versus Exogenous Crashes in Financial Markets," Papers cond-mat/0210509, arXiv.org.
    2. Pier Paolo Peirano & Damien Challet, 2012. "Baldovin-Stella stochastic volatility process and Wiener process mixtures," Post-Print hal-00734355, HAL.
    3. O. A. Vladimirova, 2018. "Influence Of A News Background On Company Cost: Review Of Literature And Direction Of Future Researches," Strategic decisions and risk management, Real Economy Publishing House, issue 4.
    4. D. Sornette, 2008. "Nurturing breakthroughs: lessons from complexity theory," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(2), pages 165-181, December.
    5. Eyal Carmi & Gal OEstreicher-Singer & Arun Sundararajan, 2010. "Is Oprah Contagious? Identifying Demand Spillovers in Product Networks," Working Papers 10-18, NET Institute.
    6. D. Sornette & A. Helmstetter, 2002. "Endogeneous Versus Exogeneous Shocks in Systems with Memory," Papers cond-mat/0206047, arXiv.org.

  33. Y. Malevergne & D. Sornette, 2001. "General framework for a portfolio theory with non-Gaussian risks and non-linear correlations," Papers cond-mat/0103020, arXiv.org.

    Cited by:

    1. L. Ingber, 2006. "Statistical mechanics of neocortical interactions: Portfolio of physiological indicators," Lester Ingber Papers 06pp, Lester Ingber.
    2. Davies, G.B. & Satchell, S.E., 2004. "Continuous Cumulative Prospect Theory and Individual Asset Allocation," Cambridge Working Papers in Economics 0467, Faculty of Economics, University of Cambridge.

  34. Yannick Malevergne & Didier Sornette, 2001. "Multi-dimensional rational bubbles and fat tails," Post-Print hal-02312893, HAL.

    Cited by:

    1. Li Lin & Didier Sornette, 2023. "The inverse Cox-Ingersoll-Ross process for parsimonious financial price modeling," Papers 2302.11423, arXiv.org, revised Jun 2023.
    2. D. Sornette & Y. Malevergne, 2001. "From Rational Bubbles to Crashes," Papers cond-mat/0102305, arXiv.org.
    3. Jerome L Kreuser & Didier Sornette, 2017. "Super-Exponential RE Bubble Model with Efficient Crashes," Swiss Finance Institute Research Paper Series 17-33, Swiss Finance Institute.
    4. Choi, Jaehyung, 2012. "Spontaneous symmetry breaking of arbitrage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3206-3218.
    5. Zhou, Wei-Xing & Sornette, Didier, 2003. "Evidence of a worldwide stock market log-periodic anti-bubble since mid-2000," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(3), pages 543-583.
    6. Sornette, D., 2002. "“Slimming” of power-law tails by increasing market returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 309(3), pages 403-418.
    7. 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.
    8. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    9. D. Sornette, 2000. ""Slimming" of power law tails by increasing market returns," Papers cond-mat/0010112, arXiv.org, revised Sep 2001.
    10. Y. Malevergne & V. F. Pisarenko & D. Sornette, 2003. "Empirical Distributions of Log-Returns: between the Stretched Exponential and the Power Law?," Papers physics/0305089, arXiv.org.
    11. Jan-Christian Gerlach & Jerome Kreuser & Didier Sornette, 2020. "Awareness of crash risk improves Kelly strategies in simulated financial time series," Papers 2004.09368, arXiv.org.

  35. Y. Malevergne & D. Sornette, 2001. "Testing the Gaussian Copula Hypothesis for Financial Assets Dependences," Papers cond-mat/0111310, arXiv.org.

    Cited by:

    1. Cyril Caillault & Dominique Guegan, 2005. "Empirical Estimation of Tail Dependence Using Copulas. Application to Asian Markets," Post-Print halshs-00180865, HAL.
    2. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
    3. Y. Malevergne & D. Sornette, 2003. "VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions," Papers physics/0301009, arXiv.org.
    4. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2010. "Out-of-sample comparison of copula specifications in multivariate density forecasts," Post-Print hal-00732675, HAL.
    5. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375765, HAL.
    6. Yanqin Fan & Xiaohong Chen & Andrew Patton, 2004. "(IAM Series No 003) Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates," FMG Discussion Papers dp483, Financial Markets Group.
    7. Huang, Hung-Hsi & Lin, Shin-Hung & Wang, Ching-Ping & Chiu, Chia-Yung, 2014. "Adjusting MV-efficient portfolio frontier bias for skewed and non-mesokurtic returns," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 59-83.
    8. Waël Louhichi & Hassen Rais, 2019. "Refinement of the hedging ratio using copula-GARCH models," Journal of Asset Management, Palgrave Macmillan, vol. 20(5), pages 403-411, September.
    9. Panchenko, Valentyn, 2005. "Goodness-of-fit test for copulas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 176-182.
    10. Shulin Zhang & Qian M. Zhou & Huazhen Lin, 2021. "Goodness-of-fit test of copula functions for semi-parametric univariate time series models," Statistical Papers, Springer, vol. 62(4), pages 1697-1721, August.
    11. Matthieu Garcin & Maxime L. D. Nicolas, 2021. "Nonparametric estimator of the tail dependence coefficient: balancing bias and variance," Papers 2111.11128, arXiv.org, revised Jul 2023.
    12. Riadh Aloui & Rangan Gupta & Stephen M. Miller, 2015. "Uncertainty and crude oil returns," Working papers 2015-03, University of Connecticut, Department of Economics.
    13. Gregor Weiß, 2013. "Copula-GARCH versus dynamic conditional correlation: an empirical study on VaR and ES forecasting accuracy," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 179-202, August.
    14. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
    15. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, August.
    16. Gregor Weiß, 2011. "Copula parameter estimation by maximum-likelihood and minimum-distance estimators: a simulation study," Computational Statistics, Springer, vol. 26(1), pages 31-54, March.
    17. Benoumechiara Nazih & Bousquet Nicolas & Michel Bertrand & Saint-Pierre Philippe, 2020. "Detecting and modeling critical dependence structures between random inputs of computer models," Dependence Modeling, De Gruyter, vol. 8(1), pages 263-297, January.
    18. Aloui, Riadh & Ben Aïssa, Mohamed Safouane & Nguyen, Duc Khuong, 2013. "Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 719-738.
    19. Michael C. Munnix & Rudi Schafer, 2011. "A Copula Approach on the Dynamics of Statistical Dependencies in the US Stock Market," Papers 1102.1099, arXiv.org, revised Mar 2011.
    20. Adam, Alexandre & Houkari, Mohamed & Laurent, Jean-Paul, 2008. "Spectral risk measures and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1870-1882, September.
    21. Cong, Rong-Gang & Brady, Mark, 2012. "The Interdependence between Rainfall and Temperature: Copula Analyses," MPRA Paper 112149, University Library of Munich, Germany.
    22. Hayette Gatfaoui, 2018. "Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures," Papers 1811.02382, arXiv.org.
    23. Y. Malevergne & D. Sornette, 2002. "Multi-Moments Method for Portfolio Management: Generalized Capital Asset Pricing Model in Homogeneous and Heterogeneous markets," Papers cond-mat/0207475, arXiv.org.
    24. Lopez, Claude & Delatte, Anne-Laure, 2013. "Commodity and Equity Markets: Some Stylized Facts from a Copula Approach," CEPR Discussion Papers 9558, C.E.P.R. Discussion Papers.
    25. Bilbao-Terol, Amelia & Arenas-Parra, Mar & Cañal-Fernández, Verónica, 2016. "A model based on Copula Theory for sustainable and social responsible investments," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 19(1), pages 55-76.
    26. Bastien Lextrait, 2022. "Optimizing portfolios in the illiquid, unlisted market of SME crowdlending," EconomiX Working Papers 2022-23, University of Paris Nanterre, EconomiX.
    27. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Papers cond-mat/0203166, arXiv.org.
    28. Kenourgios, Dimitris & Samitas, Aristeidis & Paltalidis, Nikos, 2011. "Financial crises and stock market contagion in a multivariate time-varying asymmetric framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 92-106, February.
    29. Qu, Leming & Yin, Wotao, 2012. "Copula density estimation by total variation penalized likelihood with linear equality constraints," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 384-398.
    30. Matthieu Garcin & Maxime L. D. Nicolas, 2024. "Nonparametric estimator of the tail dependence coefficient: balancing bias and variance," Statistical Papers, Springer, vol. 65(8), pages 4875-4913, October.
    31. Debasis Kundu, 2017. "On Multivariate Log Birnbaum-Saunders Distribution," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(2), pages 292-315, November.
    32. Münnix, Michael C. & Schäfer, Rudi, 2011. "A copula approach on the dynamics of statistical dependencies in the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4251-4259.
    33. Amjad, Muhammad & Akbar, Muhammad & Ullah, Hamd, 2022. "A copula-based approach for creating an index of micronutrient intakes at household level in Pakistan," Economics & Human Biology, Elsevier, vol. 46(C).
    34. Consiglio, Andrea & Russino, Annalisa, 2007. "How does learning affect market liquidity? A simulation analysis of a double-auction financial market with portfolio traders," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1910-1937, June.
    35. Tiziano Bellini, 2010. "Detecting atypical observations in financial data: the forward search for elliptical copulas," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 4(4), pages 287-299, December.
    36. Robert B. Durand & Markus Junker & Alex Szimayer, 2010. "The flight‐to‐quality effect: a copula‐based analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 50(2), pages 281-299, June.
    37. Cerqueti, Roy & Giacalone, Massimiliano & Panarello, Demetrio, 2019. "A Generalized Error Distribution Copula-based method for portfolios risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 687-695.
    38. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Post-Print halshs-00375765, HAL.
    39. Bücher, Axel & Jäschke, Stefan & Wied, Dominik, 2015. "Nonparametric tests for constant tail dependence with an application to energy and finance," Journal of Econometrics, Elsevier, vol. 187(1), pages 154-168.
    40. Bücher, Axel & Dette, Holger, 2010. "Some comments on goodness-of-fit tests for the parametric form of the copula based on L2-distances," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 749-763, March.
    41. Jean-David Fermanian, 2012. "An overview of the goodness-of-fit test problem for copulas," Papers 1211.4416, arXiv.org.
    42. Kole, H.J.W.G. & Koedijk, C.G. & Verbeek, M.J.C.M., 2003. "Stress Testing with Student's t Dependence," ERIM Report Series Research in Management ERS-2003-056-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    43. Bartram, Söhnke M. & Wang, Yaw-Huei, 2015. "European financial market dependence: An industry analysis," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 146-163.
    44. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    45. Sentana, Enrique & Amengual, Dante, 2015. "Is a normal copula the right copula?," CEPR Discussion Papers 10809, C.E.P.R. Discussion Papers.
    46. Yahdih Semlali & Musaddag Elrayah & Mekimah Sabri & Zighed Rahma & Ismail Bengana, 2024. "How Can Industrial SMEs Achieve Sustainability through Cleaner Production? Green Marketing’s Role as a Mediator," Sustainability, MDPI, vol. 16(19), pages 1-25, October.
    47. Bartram, Sohnke M. & Taylor, Stephen J. & Wang, Yaw-Huei, 2007. "The Euro and European financial market dependence," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1461-1481, May.
    48. Fischer, Matthias J., 2003. "Tailoring copula-based multivariate generalized hyperbolic secant distributions to financial return data: an empirical investigation," Discussion Papers 47/2003, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    49. Wu, Chih-Chiang & Liang, Shin-Shun, 2011. "The economic value of range-based covariance between stock and bond returns with dynamic copulas," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 711-727, September.
    50. Zhang, Shulin & Okhrin, Ostap & Zhou, Qian M. & Song, Peter X.-K., 2016. "Goodness-of-fit test for specification of semiparametric copula dependence models," Journal of Econometrics, Elsevier, vol. 193(1), pages 215-233.
    51. Roch, Oriol & Alegre, Antonio, 2006. "Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1312-1329, November.
    52. Carol Alexander & Emese Lazar & Silvia Stanescu, 2011. "Analytic Approximations to GARCH Aggregated Returns Distributions with Applications to VaR and ETL," ICMA Centre Discussion Papers in Finance icma-dp2011-08, Henley Business School, University of Reading.
    53. Yiran Chen & Giray Ökten, 2022. "A goodness-of-fit test for copulas based on the collision test," Statistical Papers, Springer, vol. 63(5), pages 1369-1385, October.
    54. Hayette Gatfaoui, 2010. "Investigating the Dependence Structure between Credit Default Swap Spreads and the U.S. Financial Market," Post-Print hal-00565525, HAL.
    55. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    56. Junker, Markus & Szimayer, Alex & Wagner, Niklas, 2006. "Nonlinear term structure dependence: Copula functions, empirics, and risk implications," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1171-1199, April.
    57. Söehnke Bartram & Stephen Taylor & Yaw-Huei Wang, 2004. "The Euro and European Financial Market Integration," Money Macro and Finance (MMF) Research Group Conference 2004 49, Money Macro and Finance Research Group, revised 13 Oct 2004.
    58. Weiß, Gregor N.F., 2011. "Are Copula-GoF-tests of any practical use? Empirical evidence for stocks, commodities and FX futures," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 173-188, May.
    59. Gad, Samar & Andrikopoulos, Panagiotis, 2019. "Diversification benefits of Shari'ah compliant equity ETFs in emerging markets," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 133-144.
    60. Cao, Guangxi & Zhang, Minjia, 2015. "Extreme values in the Chinese and American stock markets based on detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 25-35.
    61. Grundke, Peter & Polle, Simone, 2012. "Crisis and risk dependencies," European Journal of Operational Research, Elsevier, vol. 223(2), pages 518-528.
    62. Y. Malevergne & D. Sornette, 2002. "Tail Dependence of Factor Models," Papers cond-mat/0202356, arXiv.org.
    63. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    64. Mendoza-Velázquez, Alfonso & Galvanovskis, Evalds, 2009. "Introducing the GED-Copula with an application to Financial Contagion in Latin America," MPRA Paper 46669, University Library of Munich, Germany, revised 01 Feb 2010.
    65. Lourme, Alexandre & Maurer, Frantz, 2017. "Testing the Gaussian and Student's t copulas in a risk management framework," Economic Modelling, Elsevier, vol. 67(C), pages 203-214.
    66. Chen, Xiaohong & Fan, Yanqin & Patton, Andrew J., 2004. "Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates," LSE Research Online Documents on Economics 24681, London School of Economics and Political Science, LSE Library.
    67. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," PSE-Ecole d'économie de Paris (Postprint) halshs-00375765, HAL.
    68. Boris Brodsky & Henry Penikas & Irina Safaryan, 2012. "Copula structural shift identification," HSE Working papers WP BRP 05/FE/2012, National Research University Higher School of Economics.
    69. Brodsky, Boris & Penikas, Henry & Safaryan, Irina, 2009. "Detection of Structural Breaks in Copula Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 16(4), pages 3-15.
    70. Toan Luu Duc Huynh, 2019. "Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    71. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions. III," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 24(4), pages 100-130.
    72. Martin Eling & Denis Toplek, 2009. "Modeling and Management of Nonlinear Dependencies–Copulas in Dynamic Financial Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 651-681, September.
    73. Lo, Simon M.S. & Mammen, Enno & Wilke, Ralf A., 2020. "A nested copula duration model for competing risks with multiple spells," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    74. Quatto, Piero & Vacca, Gianmarco & Zoia, Maria Grazia, 2021. "A new copula for modeling portfolios with skewed, leptokurtic and high-order dependent risk factors," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    75. Dobric, Jadran & Schmid, Friedrich, 2007. "A goodness of fit test for copulas based on Rosenblatt's transformation," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4633-4642, May.
    76. Berger, T. & Missong, M., 2014. "Financial crisis, Value-at-Risk forecasts and the puzzle of dependency modeling," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 33-38.

  36. A. Corcos & J. -P. Eckmann & A. Malaspinas & Y. Malevergne & D. Sornette, 2001. "Imitation and contrarian behavior: hyperbolic bubbles, crashes and chaos," Papers cond-mat/0109410, arXiv.org.

    Cited by:

    1. Егорова Людмила Геннадьевна, 2014. "Эффективность Торговых Стратегий Мелких Трейдеров," Проблемы управления, CyberLeninka;Общество с ограниченной ответственностью "СенСиДат-Контрол", issue 5, pages 34-41.
    2. Carmen Pellicer-Lostao & Ricardo Lopez-Ruiz, 2010. "Transition from Exponential to Power Law Distributions in a Chaotic Market," Papers 1011.5187, arXiv.org.
    3. Der Chyan Lin, 2013. "Synchrony in Broadband Fluctuation and the 2008 Financial Crisis," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-9, October.
    4. Westerhoff, Frank H., 2004. "Greed, fear and stock market dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 635-642.
    5. Patrick Bayer & Kyle Mangum & James W. Roberts, 2021. "Speculative Fever: Investor Contagion in the Housing Bubble," American Economic Review, American Economic Association, vol. 111(2), pages 609-651, February.
    6. Kaizoji, Taisei & Leiss, Matthias & Saichev, Alexander & Sornette, Didier, 2015. "Super-exponential endogenous bubbles in an equilibrium model of fundamentalist and chartist traders," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 289-310.
    7. Omurtag, Ahmet & Sirovich, Lawrence, 2006. "Modeling a large population of traders: Mimesis and stability," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 562-576, December.
    8. Hongler, Max-Olivier & Gallay, Olivier & Hülsmann, Michael & Cordes, Philip & Colmorn, Richard, 2010. "Centralized versus decentralized control—A solvable stylized model in transportation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4162-4171.
    9. Li Lin & Didier Sornette, 2009. "Diagnostics of Rational Expectation Financial Bubbles with Stochastic Mean-Reverting Termination Times," Papers 0911.1921, arXiv.org.
    10. Toth, Gabor & Galam, Serge, 2022. "Deviations from the majority: A local flip model," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    11. Julia Gray, 2009. "International Organization as a Seal of Approval: European Union Accession and Investor Risk," American Journal of Political Science, John Wiley & Sons, vol. 53(4), pages 931-949, October.
    12. BRATIAN Vasile & BUCUR Amelia, 2017. "The Development And The Current Status Of The Capital Market Hypotheses: A Few Benchmarks," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(1), pages 22-28, April.
    13. Lleo, Sebastien & Ziemba, Bill, 2014. "Some historical perspectives on the Bond-Stock Earnings Yield Model for crash prediction around the world," LSE Research Online Documents on Economics 60960, London School of Economics and Political Science, LSE Library.
    14. Shiryaev, Albert N. & Zhitlukhin, Mikhail N. & Ziemba, William T., 2014. "Land and stock bubbles, crashes and exit strategies in Japan circa 1990 and in 2013," LSE Research Online Documents on Economics 59288, London School of Economics and Political Science, LSE Library.
    15. Jean-Philippe Bouchaud, 2002. "An introduction to statistical finance," Science & Finance (CFM) working paper archive 313238, Science & Finance, Capital Fund Management.
    16. D. Sornette & R. Woodard, "undated". "Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis," Working Papers CCSS-09-003, ETH Zurich, Chair of Systems Design.
    17. Damian Smug & Peter Ashwin & Didier Sornette, 2018. "Predicting financial market crashes using ghost singularities," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-20, March.
    18. Deng, Lei & Liu, Yun & Xiong, Fei, 2013. "An opinion diffusion model with clustered early adopters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3546-3554.
    19. Norman Schofield, 2015. "Climate Change, Collapse and Social Choice Theory," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 9(1), pages 007-035, October.
    20. Didier Sornette & Ryan Woodard, 2009. "Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis," Papers 0905.0220, arXiv.org.
    21. Khalil, Nagi & Toral, Raúl, 2019. "The noisy voter model under the influence of contrarians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 81-92.
    22. T. Kaizoji & M. Leiss & A. Saichev & D. Sornette, 2011. "Super-exponential endogenous bubbles in an equilibrium model of rational and noise traders," Papers 1109.4726, arXiv.org, revised Mar 2014.
    23. Frederik Herzberg, 2008. "Black-Scholes theory for an underlying with multiple attractors," Quantitative Finance, Taylor & Francis Journals, vol. 8(5), pages 453-457.
    24. Lorenzo Zanello RIva, 2012. "El efecto día en cinco índices bursátiles de América Latina," Documentos Departamento de Economía 18081, Universidad del Norte.

  37. D. Sornette & Y. Malevergne, 2001. "From Rational Bubbles to Crashes," Papers cond-mat/0102305, arXiv.org.

    Cited by:

    1. Neil Terry & Anne Macy & Amjad Abdullat, 2010. "Stock Market Volatility: A Comparison Of Computer And Cellular Hardware Companies," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 4(3), pages 11-24.
    2. Ariane Szafarz, 2015. "Market Efficiency and Crises: Don’t Throw the Baby out with the Bathwater," ULB Institutional Repository 2013/239874, ULB -- Universite Libre de Bruxelles.
    3. Jaehyung Choi, 2011. "Spontaneous symmetry breaking of arbitrage," Papers 1107.5122, arXiv.org, revised Apr 2012.
    4. Brière, Marie & Chapelle, Ariane & Szafarz, Ariane, 2012. "No contagion, only globalization and flight to quality," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1729-1744.
    5. Choi, Jaehyung, 2012. "Spontaneous symmetry breaking of arbitrage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3206-3218.
    6. Ariane Szafarz, 2012. "Financial crises in efficient markets: How fundamentalists fuel volatility," ULB Institutional Repository 2013/149191, ULB -- Universite Libre de Bruxelles.
    7. Fry, J. M., 2010. "Bubbles and crashes in finance: A phase transition from random to deterministic behaviour in prices," MPRA Paper 24778, University Library of Munich, Germany.
    8. Zhou, Wei-Xing & Sornette, Didier, 2003. "Evidence of a worldwide stock market log-periodic anti-bubble since mid-2000," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(3), pages 543-583.
    9. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Papers cond-mat/0106520, arXiv.org.
    10. Sornette, D., 2002. "“Slimming” of power-law tails by increasing market returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 309(3), pages 403-418.
    11. Fry, J. M., 2009. "Bubbles and contagion in English house prices," MPRA Paper 17687, University Library of Munich, Germany.
    12. Jennifer Jhun & Patricia Palacios & James Owen Weatherall, 2017. "Market Crashes as Critical Phenomena? Explanation, Idealization, and Universality in Econophysics," Papers 1704.02392, arXiv.org.
    13. Fry, J. M., 2010. "Gaussian and non-Gaussian models for financial bubbles via econophysics," MPRA Paper 27307, University Library of Munich, Germany.
    14. John M. Fry, 2009. "Statistical modelling of financial crashes: Rapid growth, illusion of certainty and contagion," EERI Research Paper Series EERI_RP_2009_10, Economics and Econometrics Research Institute (EERI), Brussels.
    15. D. Sornette, 2000. ""Slimming" of power law tails by increasing market returns," Papers cond-mat/0010112, arXiv.org, revised Sep 2001.
    16. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    17. Cajueiro, Daniel O. & Tabak, Benjamin M., 2006. "Testing for rational bubbles in banking indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 365-376.

Articles

  1. Da Fonseca, José & Malevergne, Yannick, 2021. "A simple microstructure model based on the Cox-BESQ process with application to optimal execution policy," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    See citations under working paper version above.
  2. Loubergé, Henri & Malevergne, Yannick & Rey, Béatrice, 2020. "New Results for additive and multiplicative risk apportionment," Journal of Mathematical Economics, Elsevier, vol. 90(C), pages 140-151.
    See citations under working paper version above.
  3. Malevergne, Y. & Saichev, A. & Sornette, D., 2013. "Zipf's law and maximum sustainable growth," Journal of Economic Dynamics and Control, Elsevier, vol. 37(6), pages 1195-1212.
    See citations under working paper version above.
  4. J. Coulon & Y. Malevergne, 2011. "Heterogeneous expectations and long-range correlation of the volatility of asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1329-1356, November.
    See citations under working paper version above.
  5. Y Malevergne & B Rey, 2010. "Preserving preference rankings under non-financial background risk," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(8), pages 1302-1308, August.
    See citations under working paper version above.
  6. Malevergne, Y. & Rey, B., 2009. "On cross-risk vulnerability," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 224-229, October.
    See citations under working paper version above.
  7. Malevergne, Y. & Sornette, D., 2007. "Self-consistent asset pricing models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 149-171.
    See citations under working paper version above.
  8. Y. Malevergne & V. Pisarenko & D. Sornette, 2005. "Empirical distributions of stock returns: between the stretched exponential and the power law?," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 379-401.
    See citations under working paper version above.
  9. Malevergne, Y. & Sornette, D., 2004. "Collective origin of the coexistence of apparent random matrix theory noise and of factors in large sample correlation matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(3), pages 660-668.
    See citations under working paper version above.
  10. Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 231-250.
    See citations under working paper version above.
  11. A. Corcos & J-P Eckmann & A. Malaspinas & Y. Malevergne & D. Sornette, 2002. "Imitation and contrarian behaviour: hyperbolic bubbles, crashes and chaos," Quantitative Finance, Taylor & Francis Journals, vol. 2(4), pages 264-281.
    See citations under working paper version above.
  12. Sornette, D & Malevergne, Y, 2001. "From rational bubbles to crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 40-59.
    See citations under working paper version above.
  13. Y. Malevergne & D. Sornette, 2001. "Multi-dimensional rational bubbles and fat tails," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 533-541.
    See citations under working paper version above.Sorry, no citations of articles recorded.

Chapters

    Sorry, no citations of chapters recorded.

Books

  1. Alex Saichev & Yannick Malevergne & Didier Sornette, 2010. "Theory of Zipf's Law and Beyond," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-02946-2, October.
    See citations under working paper version above.Sorry, no citations of books recorded.
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