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Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models

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Intelligent Systems and Applications (IntelliSys 2020)

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Abstract

The history of research in finance and economics has been widely impacted by the field of Agent-based Computational Economics (ACE). While at the same time being popular among natural science researchers for its proximity to the successful methods of physics and chemistry for example, the field of ACE has also received critics by a part of the social science community for its lack of empiricism. Yet recent trends have shifted the weights of these general arguments and potentially given ACE a whole new range of realism. At the base of these trends are found two present-day major scientific breakthroughs: the steady shift of psychology towards a hard science due to the advances of neuropsychology, and the progress of reinforcement learning due to increasing computational power and big data. We outline here the main lines of a computational research study where each agent would trade by reinforcement learning.

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References

  1. Bollerslev, T.: CREATES research paper 2008, p. 49 (2008)

    Google Scholar 

  2. Engle, R.F.: Econometrica 50(4), 987 (1982)

    Article  MathSciNet  Google Scholar 

  3. Brownlees, C.T., Engle, R.F., Kelly, B.T.: J. Risk 14(2), 3 (2011)

    Article  Google Scholar 

  4. Sbordone, A.M., Tambalotti, A., Rao, K., Walsh, K.J.: Econ. Policy Rev. 16(2) (2010)

    Google Scholar 

  5. Evans, G.W., Honkapohja, S.: Learning and Expectations in Macroeconomics. Princeton University Press, Princeton (2001)

    Book  Google Scholar 

  6. Eusepi, S., Preston, B.: Am. Econ. Rev. 101, 2844 (2011)

    Article  Google Scholar 

  7. Massaro, D.: J. Econ. Dyn. Control 37, 680 (2013)

    Article  MathSciNet  Google Scholar 

  8. Farmer, J.D., Foley, D.: Nature 460(7256), 685 (2009)

    Article  Google Scholar 

  9. Grauwe, P.D.: Public Choice 144(3–4), 413 (2010)

    Article  Google Scholar 

  10. Tesfatsion, L., Judd, K.L.: Handbook of Computational Economics: Agent-Based Computational Economics, vol. II. Elsevier, Amsterdam (2006)

    MATH  Google Scholar 

  11. Samanidou, E., Zschischang, E., Stauffer, D., Lux, T.: Rep. Prog. Phys. 70(3), 409 (2007)

    Article  Google Scholar 

  12. LeBaron, B.: Building the Santa Fe Artificial Stock Market (2002)

    Google Scholar 

  13. Bonabeau, E.: Harvard Bus. Rev. 80(3), 109 (2002)

    Google Scholar 

  14. Smith, E., Farmer, D.J., Gillemot, L., Krishnamurthy, S.: Quant. Finance 3, 481 (2003)

    Article  MathSciNet  Google Scholar 

  15. Huang, W., Lehalle, C.-A., Rosenbaum, M.: J. Am. Stat. Assoc. 110, 509 (2015)

    Google Scholar 

  16. Mota, R., Larralde, H.: arXiv:1601.00229 (2016)

  17. Macal, C.M., North, M.J.: J. Simul. 4, 151 (2010)

    Article  Google Scholar 

  18. Axelrod, R.M.: The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, Princeton (1997)

    Book  Google Scholar 

  19. Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G., et al.: Ecol. Model. 198(1), 115 (2006)

    Article  Google Scholar 

  20. Bush, R.R., Mosteller, F.: Stochastic Models for Learning. Wiley, Oxford (1955)

    Book  MATH  Google Scholar 

  21. Smith, J., Price, D.: Nature 246, 15 (1973)

    Article  Google Scholar 

  22. Taylor, P.D., Jonker, L.B.: Math. Biosci. 40, 145 (1978)

    Article  MathSciNet  Google Scholar 

  23. Mookherjee, D., Sopher, B.: Games Econ. Behav. 7, 62 (1994)

    Article  Google Scholar 

  24. Erev, I., Roth, A.E.: Am. Econ. Rev. 88, 848 (1998)

    Google Scholar 

  25. Erev, I., Roth, A.E.: PNAS 111, 10818 (2014)

    Article  Google Scholar 

  26. Camerer, C.F., Ho, T.H.: PNAS 67, 827 (1999)

    Google Scholar 

  27. Fudenberg, D., Levine, D.: The Theory of Learning in Games. MIT Press, Cambridge (1998)

    MATH  Google Scholar 

  28. Colander, D., Howitt, P., Kirman, A., Leijonhufvud, A., Mehrling, P.: Am. Econ. Rev. 236–240 (2008)

    Google Scholar 

  29. Dosi, G., Fagiolo, G., Napoletano, M., Roventini, A.: J. Econ. Dyn. Control 37(8), 1598 (2013)

    Article  Google Scholar 

  30. Gualdi, S., Tarzia, M., Zamponi, F., Bouchaud, J.-P.: J. Econ. Interact. Coord. 1–31 (2016)

    Google Scholar 

  31. Gualdi, S., Tarzia, M., Zamponi, F., Bouchaud, J.-P.: J. Econ. Dyn. Control 50, 29 (2015)

    Article  Google Scholar 

  32. Westerhoff, F.H.: Jahrbucher Fur Nationalokonomie Und Statistik 228(2), 195 (2008)

    Article  Google Scholar 

  33. Xu, H.-C., Zhang, W., Xiong, X., Zhou, W.-X.: Math. Prob. Eng. 2014, 563912 (2014)

    Google Scholar 

  34. Boero, R., Morini, M., Sonnessa, M., Terna, P.: Agent-Based Models of the Economy, From Theories to Applications. Palgrave Macmillan, New York (2015)

    Google Scholar 

  35. LeBaron, B.: Agent-based computational finance. In: The Handbook of Computational Economics, vol. 2. Elsevier, Amsterdam (2005)

    Google Scholar 

  36. Heylighen, F.: Complexity and Self-Organization. CRC Press, Boca Raton (2008)

    Google Scholar 

  37. Plerou, V., Gopikrishnan, P., Stanley, H.E.: Nature 421, 130 (2003)

    Article  Google Scholar 

  38. Hamill, L., Gilbert, N.: Agent-Based Modelling in Economics. Wiley, Hoboken (2016)

    Google Scholar 

  39. Wilcox, D., Gebbie, T.: arXiv:1408.5585 (2014)

  40. Hanson, T.A.: Midwest finance association 2012 annual meetings paper (2011)

    Google Scholar 

  41. Bartolozzi, M.: Eur. Phys. J. B 78, 265 (2010)

    Article  Google Scholar 

  42. Wah, E., Wellman, M.P.: Proceedings of the Fourteenth ACM Conference on Electronic Commerce, pp. 855–872 (2013)

    Google Scholar 

  43. Paddrik, M.E., Hayes, R.L., Todd, A., Yang, S.Y., Scherer, W., Beling, P.: SSRN 1932152 (2011)

    Google Scholar 

  44. Aloud, M., Tsang, E., Olsen, R.: Business science reference, Hershey (2013)

    Google Scholar 

  45. Challet, D., Marsili, M., Zhang, Y.-C.: Minority Games: Interacting Agents in Financial Markets. Oxford University Press, Oxford (2005)

    MATH  Google Scholar 

  46. Martino, A.D., Marsili, M.: J. Phys. A 39, 465 (2006)

    Article  MathSciNet  Google Scholar 

  47. Kyle, A.S., O. A.: Economertrica forthcoming (2016)

    Google Scholar 

  48. Preis, T., Golke, S., Paul, W., Schneider, J.J.: Europhys. Lett. 75(3), 510 (2006)

    Article  MathSciNet  Google Scholar 

  49. Farmer, J.D., Patelli, P., Zovko, I.I.: Proc. Natl. Acad. Sci. U.S.A. 102(6), 2254 (2005)

    Article  Google Scholar 

  50. Maslov, S.: Phys. A 278(3), 571 (2000)

    Article  MathSciNet  Google Scholar 

  51. Challet, D., Stinchcombe, R.: Quant. Finance 3(3), 155 (2003)

    Article  Google Scholar 

  52. Schmitt, T.A., Schfer, R., Mnnix, M.C., Guhr, T.: Europhys. Lett. 100 (2012)

    Google Scholar 

  53. Lux, T., Marchesi, M.: J. Theor. Appl. Finance 3, 67 (2000)

    Google Scholar 

  54. Cont, R.: Volatility clustering in financial markets: empirical facts and agent-based models. Springer (2007)

    Google Scholar 

  55. Bertella, M.A., Pires, F.R., Feng, L., Stanley, H.E.: PLoS ONE 9(1), e83488 (2014)

    Article  Google Scholar 

  56. Alfi, V., Cristelli, M., Pietronero, L., Zaccaria, A.: Eur. Phys. J. B 67(3), 385 (2009)

    Article  Google Scholar 

  57. Kim, G., Markowitz, H.M.: J. Portfolio Manag. 16, 45 (1989)

    Article  Google Scholar 

  58. Levy, M., Solomon, S.: Int. J. Mod. Phys. C 7, 595 (1996)

    Article  Google Scholar 

  59. Levy, M., Levy, H., Solomon, S.: Econ. Lett. 45, 103 (1994)

    Article  Google Scholar 

  60. Levy, M., Levy, H., Solomon, S.: J. Phys. I 5, 1087 (1995)

    Google Scholar 

  61. Levy, M., Solomon, S.: Int. J. Mod. Phys. C 7, 65 (1996)

    Article  Google Scholar 

  62. Levy, M., Persky, N., Solomon, S.: Int. J. High Speed Comput. 8, 93 (1996)

    Article  Google Scholar 

  63. Levy, M., Levy, H., Solomon, S.: Phys. A 242, 90 (1997)

    Article  Google Scholar 

  64. Levy, M., Levy, H., Solomon, S.: Microscopic Simulation of Financial Markets. Academic Press, New York (2000)

    MATH  Google Scholar 

  65. Cont, R., Bouchaud, J.P.: Macroecon. Dyn. 4, 170 (2000)

    Article  Google Scholar 

  66. Solomon, S., Weisbuch, G., de Arcangelis, L., Jan, N., Stauffer, D.: Phys. A 277(1), 239 (2000)

    Article  Google Scholar 

  67. Lux, T., Marchesi, M.: Nature 397, 498 (1999)

    Article  Google Scholar 

  68. Donangelo, R., Hansen, A., Sneppen, K., Souza, S.R.: Phys. A 283, 469 (2000)

    Article  Google Scholar 

  69. Donangelo, R., Sneppen, K.: Phys. A 276, 572 (2000)

    Article  Google Scholar 

  70. Bak, P., Norrelykke, S., Shubik, M.: Phys. Rev. E 60, 2528 (1999)

    Article  Google Scholar 

  71. Bak, P., Norrelykke, S., Shubik, M.: Quant. Finance 1, 186 (2001)

    Article  MathSciNet  Google Scholar 

  72. Huang, Z.F., Solomon, S.: Eur. Phys. J. B 20, 601 (2000)

    Article  Google Scholar 

  73. Lipski, J., Kutner, R.: arXiv:1310.0762 (2013)

  74. Barde, S.: School of economics discussion papers 04. University of Kent (2015)

    Google Scholar 

  75. Potters, M., Bouchaud, J.-P.: Phys. A 299, 60 (2001)

    Article  Google Scholar 

  76. Plerou, V., Gopikrishnan, P., Amaral, L.A., Meyer, M., Stanley, H.E.: Phys. Rev. E 60(6), 6519 (1999)

    Article  Google Scholar 

  77. Cristelli, M.: Complexity in Financial Markets. Springer, Cham (2014)

    Book  Google Scholar 

  78. Weron, R.: Int. J. Mod. Phys. C 12, 209 (2001)

    Article  Google Scholar 

  79. Eisler, Z., Kertesz, J.: Eur. Phys. J. B 51, 145 (2006)

    Article  Google Scholar 

  80. Mandelbrot, B.: J. Bus. 394–419 (1963)

    Google Scholar 

  81. Cont, R.: Quant. Finance 1, 223 (2001)

    Article  Google Scholar 

  82. Bouchaud, J., Cont, R., Potters, M.: Scale invariance and beyond. In: Proceedings of CNRS Workshop on Scale Invariance. Springer, Les Houches (1997)

    Google Scholar 

  83. Ding, Z., Engle, R., Granger, C.: J. Empir. Finance 1, 83 (1993)

    Article  Google Scholar 

  84. Lobato, I.N., Savin, N.E.: J. Bus. Econ. Stat. 16, 261 (1998)

    Google Scholar 

  85. Vandewalle, N., Ausloos, M.: Phys. A 246, 454 (1997)

    Article  Google Scholar 

  86. Mandelbrot, B., Fisher, A., Calvet, L.: A multifractal model of asset returns. Cowles Foundation for Research and Economics (1997)

    Google Scholar 

  87. de Vries, C., Leuven, K.: Stylized facts of nominal exchange rate returns. Working Papers from Purdue University, Krannert School of Management Center for International Business Education and Research (CIBER) (1994)

    Google Scholar 

  88. Pagan, A.: J. Empir. Finance 3, 15 (1996)

    Article  Google Scholar 

  89. Cont, R.: Volatility clustering in financial markets: empirical facts and agent-based models. In: Kirman, A., Teyssiere, G. (eds.) Long Memory in Economics. Springer (2005)

    Google Scholar 

  90. Fama, E.: J. Finance 25, 383 (1970)

    Article  Google Scholar 

  91. Bera, A.K., Ivliev, S., Lillo, F.: Financial Econometrics and Empirical Market Microstructure. Springer, Cham (2015)

    Book  Google Scholar 

  92. Wiesinger, J., Sornette, D., Satinover, J.: Comput. Econ. 41(4), 475 (2012)

    Article  Google Scholar 

  93. Andersen, J.V., Sornette, D.: Europhys. Lett. 70(5), 697 (2005)

    Article  MathSciNet  Google Scholar 

  94. Zhang, Q.: Disentangling financial markets and social networks: models and empirical tests. Ph.D. thesis, ETH Zurich (2013)

    Google Scholar 

  95. Friedman, M.: Essays in Positive Economics. Chicago University Press, Chicago (1953)

    Google Scholar 

  96. Canova, F., Sala, L.: J. Monetary Econ. 56(4), 431 (2009)

    Article  Google Scholar 

  97. Chiarella, C., Iori, G., Perello, J.: J. Econ. Dyn. Control 33, 525 (2009)

    Article  Google Scholar 

  98. Leal, S.J., Napoletano, M., Roventini, A., Fagiolo, G.: J. Evol. Econ. 26, 49 (2016)

    Article  Google Scholar 

  99. Fabretti, A.: J. Econ. Interact. Coord. 8, 277 (2013)

    Article  Google Scholar 

  100. Axtell, R.: Center on social and economic dynamics working paper 17 (2000)

    Google Scholar 

  101. Gilli, M., Winker, P.: Comput. Stat. Data Anal. 42, 299 (2003)

    Article  Google Scholar 

  102. Farmer, J.D., Joshi, S.: J. Econ. Behav. Organ. 49, 149 (2002)

    Article  Google Scholar 

  103. Kirman, A.: Epidemics of opinion and speculative bubbles in financial markets. In: Money and Financial Markets. Macmillan, New York (1991)

    Google Scholar 

  104. Glimcher, P.W., Camerer, C.F., Fehr, E., Poldrack, R.A.: Neuroeconomics: Decision Making and the Brain. Academic Press, Cambridge (2009)

    Google Scholar 

  105. Camerer, C.: J. Econ. Lit. 51(4), 1155 (2013)

    Article  Google Scholar 

  106. Martino, B.D., Doherty, J.P.O., Ray, D., Bossaerts, P., Camerer, C.: Neuron 79(6), 1222 (2013)

    Article  Google Scholar 

  107. Camerer, C.: Ann. Rev. Econ. 5, 425 (2013)

    Article  Google Scholar 

  108. Camerer, C.: Neuroscience, game theory, monkeys. TEDx talk (2013)

    Google Scholar 

  109. Kahneman, D., Tversky, A.: Econometrica 47(2), 263 (1979)

    Article  MathSciNet  Google Scholar 

  110. Frydman, C., Barberis, N., Camerer, C., Bossaerts, P., Rangel, A.: NBER working paper 18562 (2012)

    Google Scholar 

  111. Camerer, C.F.: Behavioral Game Theory: Experiments on Strategic Interaction. Princeton University Press, Princeton (2003)

    MATH  Google Scholar 

  112. Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., et al.: Science 362, 1140 (2018)

    Article  MathSciNet  Google Scholar 

  113. Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., et al.: Nature 550, 354 (2017)

    Article  Google Scholar 

  114. Doll, B.B., Duncan, K.D., Simon, D.A., Shohamy, D.S., Daw, N.D.: Nat. Neurosci. 18, 767 (2015)

    Article  Google Scholar 

  115. Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)

    MATH  Google Scholar 

  116. Schmidhuber, J.: Neural Netw. 61, 85 (2015)

    Article  Google Scholar 

  117. Turchenko, V., Beraldi, P., Simone, F.D., Grandinetti, L.: The 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (2011)

    Google Scholar 

  118. Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., et al.: Nature 529, 484 (2016)

    Article  Google Scholar 

  119. Tuyls, K., Weiss, G.: AI Mag. Fall (2012)

    Google Scholar 

  120. Heinrich, J., Silver, D.: AAAI Workshop (2014)

    Google Scholar 

  121. Heinrich, J., Silver, D.: IJCAI (2015)

    Google Scholar 

  122. Reed, S., Akata, Z., Yan, X., Logeswaran, L., Lee, H., Schiele, B.: ICML (2016)

    Google Scholar 

  123. Lerer, A., Gross, S., Fergus, R.: ICML (2016)

    Google Scholar 

  124. Biondo, A.E.: J. Econ. Interact. Coord. 14(3) (2018)

    Google Scholar 

  125. Spooner, T., Fearnley, J., Savani, R., Koukorinis, A.: Proceedings of the 17th AAMAS (2018)

    Google Scholar 

  126. Ganesh, S., Vadori, N., Xu, M., Zheng, H., Reddy, P., Veloso, M.: arXiv:1911.05892 (2019)

  127. Lefebvre, G., Lebreton, M., Meyniel, F., BourgeoisGironde, S., Palminteri, S.: Nat. Hum. Behav. 1, 1 (2017)

    Article  Google Scholar 

  128. Duncan, K., Doll, B.B., Daw, N.D., Shohamy, D.: Neuron 98, 645 (2018)

    Article  Google Scholar 

  129. Momennejad, I., Russek, E., Cheong, J., Botvinick, M., Daw, N.D., Gershman, S.J.: Nat. Hum. Behav. 1, 680–692 (2017)

    Article  Google Scholar 

  130. Palminteri, S., Khamassi, M., Joffily, M., Coricelli, G.: Nat. Commun. 1–14 (2015)

    Google Scholar 

  131. Laibson, D.: Q. J. Econ. 112(2), 443 (1997)

    Article  Google Scholar 

  132. The financial crisis inquiry report. Official government edition (2011)

    Google Scholar 

  133. Fouque, J.-P., Langsam, J.A.: Handbook on Systemic Risk. Cambridge University Press, Cambridge (2013)

    Book  MATH  Google Scholar 

  134. Bikhchandani, S., Sharma, S.: Int. Monetary Fund. 47(3) (2001)

    Google Scholar 

  135. Bikhchandani, S., Hirshleifer, D., Welch, I.: J. Polit. Econ. 100(5), 992 (1992)

    Article  Google Scholar 

  136. Fama, E.: J. Bus. 38, 34 (1965)

    Article  Google Scholar 

  137. Sornette, D.: arXiv:1404.0243v1 (2014)

  138. da Costa Pereira, C., Mauri, A., Tettamanzi, A.G.B.: IEEE Computer Society WIC ACM (2009)

    Google Scholar 

  139. Kyle, A.S.: Econometrica 53, 1315 (1985)

    Article  Google Scholar 

  140. Sanford, G.J., Miller, M.H.: J. Finance 43, 617 (1988)

    Article  Google Scholar 

  141. Grossman, S.J., Stiglitz, J.E.: Am. Econ. Rev. 70, 393 (1980)

    Google Scholar 

  142. Cason, T.N., Friedman, D.: Exp. Econ. 2, 77 (1999)

    Article  Google Scholar 

  143. Evstigneev, I.V., Hens, T., Schenk-Hopp, K.R.: Evolutionary finance. In: Handbook of Financial Markets, Dynamics and Evolution. North-Holland, Elsevier (2009)

    Google Scholar 

  144. Saichev, A., Malevergne, Y., Sornette, D.: Theory of Zipf’s Law and Beyond. Lecture Notes in Economics and Mathematical Systems, vol. 632. Springer, Heidelberg (2010)

    Book  MATH  Google Scholar 

  145. Malevergne, Y., Saichev, A., Sornette, D.: J. Econ. Dyn. Control 37(6), 1195 (2013)

    Article  Google Scholar 

  146. Hasanhodzic, J., Lo, A.W., Viola, E.: Quant. Finance 11(7), 1043 (2011)

    Article  MathSciNet  Google Scholar 

  147. Malkiel, B.G.: A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing, 10th revised edn. W. W. Norton and Company (2012)

    Google Scholar 

  148. Black, F.: J. Finance 41(3), 529 (1985)

    Article  Google Scholar 

  149. Lussange, J., Bourgeois-Gironde, S., Palminteri, S., Gutkin, B.: arXiv:1909.07748 (2019)

  150. Lussange, J., Belianin, A., Bourgeois-Gironde, S., Gutkin, B.: arXiv:1801.08222 (2018)

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Acknowledgment

This work was supported by the RFFI grant nr. 16-51-150007 and CNRS PRC nr. 151199, and received support from FrontCog ANR-17-EURE-0017. A preliminary preprint of this work was uploaded to arXiv  [150].

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Authors and Affiliations

  1. Laboratoire des Neurosciences Cognitives, INSERM U960, Département des Études Cognitives, École Normale Supérieure PSL University, 29 rue d’Ulm, 75005, Paris, France

    Johann Lussange & Boris Gutkin

  2. ICEF, National Research University Higher School of Economics and Primakov Institute for World Economy and International Relations, Russian Academy of Sciences, 8 Myasnitskaya st., 101000, Moscow, Russia

    Alexis Belianin

  3. Institut Jean-Nicod, UMR 8129, Département des Études Cognitives, École Normale Supérieure PSL University, 29 rue d’Ulm, 75005, Paris, France

    Sacha Bourgeois-Gironde

  4. Laboratoire d’Économie Mathématique et de Microéconomie Appliquée, EA 4442, Université Paris II Panthéon-Assas, 4 rue Blaise Desgoffe, 75006, Paris, France

    Sacha Bourgeois-Gironde

  5. Center for Cognition and Decision Making, Department of Psychology, NU University Higher School of Economics, 8 Myasnitskaya st., 101000, Moscow, Russia

    Boris Gutkin

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  1. Johann Lussange
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Correspondence to Johann Lussange .

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    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Lussange, J., Belianin, A., Bourgeois-Gironde, S., Gutkin, B. (2021). Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1252. Springer, Cham. https://doi.org/10.1007/978-3-030-55190-2_19

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