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Time variation of higher moments in a financial market with heterogeneous agents: An analytical approach

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Cited by:

  1. Gontis, V. & Havlin, S. & Kononovicius, A. & Podobnik, B. & Stanley, H.E., 2016. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1091-1102.
  2. Chiarella Carl & Di Guilmi Corrado, 2015. "The limit distribution of evolving strategies in financial markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 137-159, April.
  3. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2015. "Markets, herding and response to external information," Papers 1506.03708, arXiv.org, revised Jun 2015.
  4. Anufriev, Mikhail & Bao, Te & Tuinstra, Jan, 2016. "Microfoundations for switching behavior in heterogeneous agent models: An experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 129(C), pages 74-99.
  5. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2016. "The noisy voter model on complex networks," Papers 1602.06935, arXiv.org, revised Apr 2016.
  6. Catalano, Michele & Di Guilmi, Corrado, 2019. "Uncertainty, rationality and complexity in a multi-sectoral dynamic model: The dynamic stochastic generalized aggregation approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 117-144.
  7. Aleksejus Kononovicius & Vygintas Gontis, 2012. "Three-state herding model of the financial markets," Papers 1210.1838, arXiv.org, revised Jan 2013.
  8. Chiarella, Carl & Di Guilmi, Corrado, 2011. "The financial instability hypothesis: A stochastic microfoundation framework," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1151-1171, August.
  9. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
  10. Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.
  11. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
  12. Roy Cerqueti & Giulia Rotundo, 2015. "A review of aggregation techniques for agent-based models: understanding the presence of long-term memory," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1693-1717, July.
  13. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
  14. Friedrich Wagner, 2011. "Market clearing by maximum entropy in agent models of stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(2), pages 121-138, November.
  15. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
  16. Vygintas Gontis & Shlomo Havlin & Aleksejus Kononovicius & Boris Podobnik & H. Eugene Stanley, 2015. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Papers 1507.05203, arXiv.org, revised Oct 2016.
  17. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.
  18. Aleksejus Kononovicius & Vygintas Gontis & Valentas Daniunas, 2012. "Agent-based Versus Macroscopic Modeling of Competition and Business Processes in Economics and Finance," Papers 1202.3533, arXiv.org, revised Jun 2012.
  19. Albrecht Irle & Jonas Kauschke & Thomas Lux & Mishael Milaković, 2011. "Switching Rates And The Asymptotic Behavior Of Herding Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 359-376.
  20. M. Cristelli & L. Pietronero & A. Zaccaria, 2011. "Critical Overview of Agent-Based Models for Economics," Papers 1101.1847, arXiv.org.
  21. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda, 2017. "Informative Contagion Dynamics in a Multilayer Network Model of Financial Markets," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 343-366, November.
  22. Palczewski, Jan & Schenk-Hoppé, Klaus Reiner, 2010. "From discrete to continuous time evolutionary finance models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(5), pages 913-931, May.
  23. Hohnisch, Martin & Westerhoff, Frank, 2008. "Business cycle synchronization in a simple Keynesian macro-model with socially transmitted economic sentiment and international sentiment spill-over," Structural Change and Economic Dynamics, Elsevier, vol. 19(3), pages 249-259, September.
  24. Alfarano Simone & Milakovic Mishael, 2012. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(4), pages 1-23, October.
  25. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2013. "Signal amplification in an agent-based herding model," Papers 1302.6477, arXiv.org, revised Sep 2015.
  26. Simone Landini & Mauro Gallegati, 2014. "Heterogeneity, interaction and emergence: effects of composition," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(3/4), pages 339-361.
  27. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
  28. Yamamoto, Ryuichi, 2019. "Dynamic Predictor Selection And Order Splitting In A Limit Order Market," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1757-1792, July.
  29. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-31, October.
  30. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
  31. Makoto Nirei & John Stachurski & Tsutomu Watanabe, 2018. "Trade Clustering and Power Laws in Financial Markets (Published in Theoretical Economics, 15:1365?1398, 2020)," CARF F-Series CARF-F-450, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  32. Chen, Zhenxi, 2016. "Regimes dependent speculative trading: Evidence from the United States housing market," FinMaP-Working Papers 66, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  33. Lux, Thomas, 2012. "Estimation of an agent-based model of investor sentiment formation in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1284-1302.
  34. Emna Mnif & Anis Jarboui & M. Kabir Hassan & Khaireddine Mouakhar, 2020. "Big data tools for Islamic financial analysis," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 10-21, January.
  35. Chen, Zhenxi & Zheng, Huanhuan, 2022. "Herding in the Chinese and US stock markets: Evidence from a micro-founded approach," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 597-604.
  36. Peralta, Antonio F. & Khalil, Nagi & Toral, Raúl, 2020. "Ordering dynamics in the voter model with aging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
  37. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
  38. Mengling Li & Huanhuan Zheng, 2017. "Heterogeneous trading and complex price dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 437-442, July.
  39. Haijun Yang & Harry Wang & Gui Sun & Li Wang, 2015. "A comparison of U.S and Chinese financial market microstructure: heterogeneous agent-based multi-asset artificial stock markets approach," Journal of Evolutionary Economics, Springer, vol. 25(5), pages 901-924, November.
  40. Di Guilmi, Corrado & He, Xue-Zhong & Li, Kai, 2014. "Herding, trend chasing and market volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 349-373.
  41. Ali Naqvi & Miriam Rehm, 2014. "A multi-agent model of a low income economy: simulating the distributional effects of natural disasters," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 275-309, October.
  42. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2020. "Robust Mathematical Formulation And Probabilistic Description Of Agent-Based Computational Economic Market Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(06), pages 1-41, September.
  43. Domenico Delli Gatti & Tommaso Ferraresi & Filippo Gusella & Lilit Popoyan & Giorgio Ricchiuti & Andrea Roventini, 2024. "The complex interplay between exchange rate and real markets: an agent-based model exploration," LEM Papers Series 2024/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  44. Ghonghadze, Jaba & Lux, Thomas, 2015. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," FinMaP-Working Papers 38, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  45. Giovanni Campisi & Silvia Muzzioli, 2020. "Investor sentiment and trading behavior," Department of Economics 0163, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  46. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
  47. Menkhoff, Lukas & Rebitzky, Rafael R. & Schröder, Michael, 2009. "Heterogeneity in exchange rate expectations: Evidence on the chartist-fundamentalist approach," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 241-252, May.
  48. Domenico Delli Gatti & Tommaso Ferraresi & Filippo Gusella & Lilit Popoyan & Giorgio Ricchiuti & Andrea Roventini, 2024. "The interplay between real and exchange rate market: an agent-based model approach," Working Papers - Economics wp2024_10.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
  49. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
  50. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.
  51. Kononovicius, A. & Gontis, V., 2014. "Control of the socio-economic systems using herding interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 80-84.
  52. Malliaris, A.G. & Kyrtsou, C., 2009. "Editorial introduction of the special issue: "Energy sector pricing and macroeconomic dynamics"," Energy Economics, Elsevier, vol. 31(6), pages 825-826, November.
  53. Tang, Yinan & Chen, Ping, 2014. "Time varying moments, regime switch, and crisis warning: The birth–death process with changing transition probability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 56-64.
  54. Lux, Thomas, 2009. "Mass psychology in action: identification of social interaction effects in the German stock market," Kiel Working Papers 1514, Kiel Institute for the World Economy (IfW Kiel).
  55. H. Lamba, 2009. "A queueing theory description of fat-tailed price returns in imperfect financial markets," Papers 0908.0949, arXiv.org, revised Aug 2010.
  56. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2019. "Robust Mathematical Formulation and Probabilistic Description of Agent-Based Computational Economic Market Models," Papers 1904.04951, arXiv.org, revised Mar 2021.
  57. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
  58. Ghonghadze, Jaba & Lux, Thomas, 2016. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 1-19.
  59. Vygintas Gontis & Aleksejus Kononovicius & Stefan Reimann, 2012. "The class of nonlinear stochastic models as a background for the bursty behavior in financial markets," Papers 1201.3083, arXiv.org, revised May 2012.
  60. S. Alfarano & M. Milakovic & M. Raddant, 2013. "A note on institutional hierarchy and volatility in financial markets," The European Journal of Finance, Taylor & Francis Journals, vol. 19(6), pages 449-465, July.
  61. He, Xue-Zhong & Zheng, Huanhuan, 2016. "Trading heterogeneity under information uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 64-80.
  62. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harré, 2021. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model," SN Business & Economics, Springer, vol. 1(6), pages 1-21, June.
  63. Weihong Huang & Huanhuan Zheng & Wai-Mun Chia, 2013. "Asymmetric returns, gradual bubbles and sudden crashes," The European Journal of Finance, Taylor & Francis Journals, vol. 19(5), pages 420-437, May.
  64. Nils Bertschinger & Iurii Mozzhorin, 2021. "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 173-210, January.
  65. Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
  66. Daniele Giachini, 2018. "Rationality and Asset Prices under Belief Heterogeneity," LEM Papers Series 2018/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  67. Di Guilmi, Corrado & Carvalho, Laura, 2017. "The dynamics of leverage in a demand-driven model with heterogeneous firms," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 70-90.
  68. Lux, Thomas, 2020. "Bayesian estimation of agent-based models via adaptive particle Markov chain Monte Carlo," Economics Working Papers 2020-01, Christian-Albrechts-University of Kiel, Department of Economics.
  69. Makoto Nirei & Tsutomu Watanabe, 2014. "Beauty Contests and Fat Tails in Financial Markets," UTokyo Price Project Working Paper Series 024, University of Tokyo, Graduate School of Economics.
  70. Jovanovic, Franck & Schinckus, Christophe, 2016. "Breaking down the barriers between econophysics and financial economics," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 256-266.
  71. Kai Li, 2014. "Asset Price Dynamics with Heterogeneous Beliefs and Time Delays," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 13, July-Dece.
  72. Nirei, Makoto & Stachurski, John & Watanabe, Tsutomu, 2020. "Trade clustering and power laws in financial markets," Theoretical Economics, Econometric Society, vol. 15(4), November.
  73. Lux, Thomas, 2018. "Estimation of agent-based models using sequential Monte Carlo methods," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 391-408.
  74. Adrián Carro & Raúl Toral & Maxi San Miguel, 2015. "Markets, Herding and Response to External Information," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-28, July.
  75. Alfarano, Simone & Milaković, Mishael & Raddant, Matthias, 2009. "Network hierarchy in Kirman's ant model: fund investment can create systemic risk," Economics Working Papers 2009-09, Christian-Albrechts-University of Kiel, Department of Economics.
  76. Kai Li, 2014. "Asset Price Dynamics with Heterogeneous Beliefs and Time Delays," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2014, January-A.
  77. Nicolas, Maxime L.D., 2022. "Estimating a model of herding behavior on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
  78. Lux, Thomas, 2006. "Financial power laws: Empirical evidence, models, and mechanism," Economics Working Papers 2006-12, Christian-Albrechts-University of Kiel, Department of Economics.
  79. Zhenxi Chen & Jing Ru, 2021. "Herding and capitalization size in the Chinese stock market: a micro-foundation evidence," Empirical Economics, Springer, vol. 60(4), pages 1895-1911, April.
  80. 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.
  81. Luisanna Cocco & Giulio Concas & Michele Marchesi, 2017. "Using an artificial financial market for studying a cryptocurrency market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 345-365, July.
  82. Kononovicius, Aleksejus, 2021. "Supportive interactions in the noisy voter model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
  83. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
  84. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2010. "Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation," MPRA Paper 24719, University Library of Munich, Germany.
  85. Светлов К.В., 2019. "Стадное Поведение На Фондовом Рынке: Анализ И Прогнозирование," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(2), pages 81-97, апрель.
  86. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda, 2016. "Order Book, Financial Markets and Self-Organized Criticality," Papers 1602.08270, arXiv.org.
  87. Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
  88. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
  89. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
  90. Rytis Kazakeviv{c}ius & Aleksejus Kononovicius, 2023. "Anomalous diffusion and long-range memory in the scaled voter model," Papers 2301.08088, arXiv.org, revised Feb 2023.
  91. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
  92. Vidal-Tomás, David, 2022. "Which cryptocurrency data sources should scholars use?," International Review of Financial Analysis, Elsevier, vol. 81(C).
  93. Moran, José & Fosset, Antoine & Kirman, Alan & Benzaquen, Michael, 2021. "From ants to fishing vessels: a simple model for herding and exploitation of finite resources," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
  94. Kaltwasser, Pablo Rovira, 2010. "Uncertainty about fundamentals and herding behavior in the FOREX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1215-1222.
  95. Muhammad Arslan & Ahmed Imran Hunjra & Wajid Shakeel Ahmed & Younes Ben Zaied, 2024. "Forecasting multi‐frequency intraday exchange rates using deep learning models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1338-1355, August.
  96. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
  97. Di Guilmi, C. & Gallegati, M. & Landini, S. & Stiglitz, J.E., 2020. "An analytical solution for network models with heterogeneous and interacting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 189-220.
  98. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
  99. Aleksejus Kononovicius & Vygintas Gontis, 2013. "Control of the socio-economic systems using herding interactions," Papers 1309.6105, arXiv.org, revised Feb 2014.
  100. Kyrtsou, Catherine, 2008. "Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6785-6789.
  101. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.
  102. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.
  103. Rytis Kazakevicius & Aleksejus Kononovicius & Bronislovas Kaulakys & Vygintas Gontis, 2021. "Understanding the nature of the long-range memory phenomenon in socioeconomic systems," Papers 2108.02506, arXiv.org, revised Aug 2021.
  104. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.
  105. Thomas Lux, 2022. "Bayesian Estimation of Agent-Based Models via Adaptive Particle Markov Chain Monte Carlo," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 451-477, August.
  106. A. E. Biondo & A. Pluchino & A. Rapisarda, 2015. "Modelling Financial Markets by Self-Organized Criticality," Papers 1507.04298, arXiv.org, revised Oct 2015.
  107. Domenico Delli Gatti & Corrado Di Guilmi & Mauro Gallegati & Simone Landini, 2012. "Reconstructing Aggregate Dynamics in Heterogeneous Agents Models. A Markovian Approach," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 117-146.
  108. Jia-Ping Huang & Yang Zhang & Juanxi Wang, 2023. "Dynamic effects of social influence on asset prices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 671-699, July.
  109. Tang, Yinan & Chen, Ping, 2015. "Transition probability, dynamic regimes, and the critical point of financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 11-20.
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