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Explaining the facts with adaptive agents: The case of mutual fund flows

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  1. Jaqueson K. Galimberti & Sergio da Silva, 2012. "An empirical case against the use of genetic-based learning classifier systems as forecasting devices," Economics Bulletin, AccessEcon, vol. 32(1), pages 354-369.
  2. Palczewski, Jan & Schenk-Hoppé, Klaus Reiner & Wang, Tongya, 2016. "Itchy feet vs cool heads: Flow of funds in an agent-based financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 63(C), pages 53-68.
  3. J. Wiesinger & D. Sornette & J. Satinover, 2013. "Reverse Engineering Financial Markets with Majority and Minority Games Using Genetic Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 475-492, April.
  4. Allen, Todd W. & Carroll, Christopher D., 2001. "Individual Learning About Consumption," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 255-271, April.
  5. Min Zheng & Duo Wang & Xue-Zhong He, 2009. "Asymmetry of technical analysis and market price volatility," Published Paper Series 2009-6, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  6. Luo, Guo Ying, 2003. "Evolution, efficiency and noise traders in a one-sided auction market," Journal of Financial Markets, Elsevier, vol. 6(2), pages 163-197, April.
  7. Meissner, Thomas & Rostam-Afschar, Davud, 2017. "Learning Ricardian Equivalence," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 273-288.
  8. Arifovic, Jasmina & Karaivanov, Alexander, 2010. "Learning by doing vs. learning from others in a principal-agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 1967-1992, October.
  9. Jing Yang, 1999. "Heterogeneous Beliefs, Intelligent Agents, and Allocative Efficiency in an Artificial Stock Market," Computing in Economics and Finance 1999 612, Society for Computational Economics.
  10. Arvid Oskar Ivar Hoffmann & Wander Jager & J. H. Von Eije, 2007. "Social Simulation of Stock Markets: Taking It to the Next Level," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-7.
  11. Ryuichi YAMAMOTO, 2005. "Evolution with Individual and Social Learning in an Agent-Based Stock Market," Computing in Economics and Finance 2005 228, Society for Computational Economics.
  12. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
  13. Chueh-Yung Tsao & Ya-Chi Huang, 2018. "Revisiting the issue of survivability and market efficiency with the Santa Fe Artificial Stock Market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 537-560, October.
  14. Guglielmo Maria Caporale & Antoaneta Serguieva & Hao Wu, 2009. "Financial contagion: evolutionary optimization of a multinational agent‐based model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 111-125, January.
  15. Aleksandras Vytautas Rutkauskas & Tomas Ramanauskas, 2009. "Building an artificial stock market populated by reinforcement‐learning agents," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(4), pages 329-341, September.
  16. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
  17. Palomino, F.A., 1997. "Relative Performance Equilibrium in Financial Markets," Discussion Paper 1997-99, Tilburg University, Center for Economic Research.
  18. Chen, Shu-Heng & Huang, Ya-Chi, 2008. "Risk preference, forecasting accuracy and survival dynamics: Simulations based on a multi-asset agent-based artificial stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 702-717, September.
  19. Lucia Milone & Paolo Pellizzari, 2009. "Mutual Funds Flows and the “Sheriff of Nottingham” Effect," Lecture Notes in Economics and Mathematical Systems, in: Cesáreo Hernández & Marta Posada & Adolfo López-Paredes (ed.), Artificial Economics, chapter 0, pages 117-128, Springer.
  20. Igan, Deniz & Pinheiro, Marcelo, 2016. "Delegated Portfolio Management, Benchmarking, and the Effects on Financial Markets," Journal of Financial Transformation, Capco Institute, vol. 43, pages 144-157.
  21. Ya-Chi Huang & Chueh-Yung Tsao, 2018. "Evolutionary Frequency and Forecasting Accuracy: Simulations Based on an Agent-Based Artificial Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 79-104, June.
  22. Goriaev, A.P. & Palomino, F.A. & Prat, A., 2000. "Mutual Fund Tournament : Risk Taking Incentives Induced by Ranking Objectives," Other publications TiSEM 41aeada1-3d53-4828-bfae-2, Tilburg University, School of Economics and Management.
  23. Shira Fano & Marco LiCalzi & Paolo Pellizzari, 2013. "Convergence of outcomes and evolution of strategic behavior in double auctions," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 513-538, July.
  24. repec:dgr:rugsom:04b25 is not listed on IDEAS
  25. Paolo Pin, 2006. "Selection matters," Working Papers 138, Department of Applied Mathematics, Università Ca' Foscari Venezia.
  26. Kaniel, Ron & Starks, Laura T & Gallaher, Steven, 2015. "Advertising and Mutual Funds: From Families to Individual Funds," CEPR Discussion Papers 10329, C.E.P.R. Discussion Papers.
  27. Roman Šperka & Marek Spišák, 2013. "Transaction costs influence on the stability of financial market: agent-based simulation," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(sup1), pages 1-12, June.
  28. Andrew Lo & Nicholas Chan & Blake LeBaron & Tomaso Poggio, 1999. "Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders," Computing in Economics and Finance 1999 653, Society for Computational Economics.
  29. Noe, Thomas H. & Rebello, Michael & Wang, Jun, 2012. "Learning to bid: The design of auctions under uncertainty and adaptation," Games and Economic Behavior, Elsevier, vol. 74(2), pages 620-636.
  30. Igan, Deniz & Pinheiro, Marcelo, 2012. "The effects of relative performance objectives on financial markets," MPRA Paper 43452, University Library of Munich, Germany.
  31. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
  32. Alejandro Reveiz Herault, 2008. "Artificial Markets under a Complexity Perspective," Borradores de Economia 4616, Banco de la Republica.
  33. Miguel Martinez Sedano, 2003. "Legal constraints, transaction costs and the evaluation of mutual funds," The European Journal of Finance, Taylor & Francis Journals, vol. 9(3), pages 199-218.
  34. James Sprigg & Mark Ehlen, 2007. "Comparative dynamics in an overlapping-generations model: the effects of quasi-rational discrete choice on finding and maintaining Nash equilibrium," Computational Economics, Springer;Society for Computational Economics, vol. 29(1), pages 69-96, February.
  35. Jens Grossklags & Carsten Schmidt, 2002. "Artificial Software Agents on Thin Double Auction Markets - A Human Trader Experiment," Papers on Strategic Interaction 2002-45, Max Planck Institute of Economics, Strategic Interaction Group.
  36. Palomino, Frederic, 2005. "Relative performance objectives in financial markets," Journal of Financial Intermediation, Elsevier, vol. 14(3), pages 351-375, July.
  37. Palomino, F.A. & Prat, A., 1998. "Dynamic incentives in the money management tournament," Discussion Paper 1998-107, Tilburg University, Center for Economic Research.
  38. Chen, Shu-Heng & Chie, Bin-Tzong, 2008. "Lottery markets design, micro-structure, and macro-behavior: An ACE approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 463-480, August.
  39. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
  40. Palomino, F.A., 1997. "Relative Performance Equilibrium in Financial Markets," Other publications TiSEM 08a7d29b-8d3c-4ba2-9b43-3, Tilburg University, School of Economics and Management.
  41. Iris Lucas & Michel Cotsaftis & Cyrille Bertelle, 2017. "Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems," Post-Print hal-02114933, HAL.
  42. Gil Bazo, Javier & Moreno Muñoz, Jesús David & Tapia, Mikel, 2005. "Price dynamics, informational efficiency and wealth distribution in continuous double auction markets," DEE - Working Papers. Business Economics. WB wb057819, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
  43. Hoffmann, Arvid O.I. & Jager, Wander, 2004. "The effect of different needs, decisionmaking processes and networkstructures on investor behavior and stock market dynamics : a simulation approach," Research Report 04B25, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  44. Witte, Björn-Christopher, 2011. "Fund managers - why the best might be the worst: On the evolutionary vigor of risk-seeking behavior," BERG Working Paper Series 81, Bamberg University, Bamberg Economic Research Group.
  45. Woertman, W.H., 2008. "Learning in consumer choice," Other publications TiSEM c467376b-ae4e-49ad-a336-7, Tilburg University, School of Economics and Management.
  46. Smith, Peter, 2004. "Reworking the Standard Model of Competitive Markets: The Role of Fuzzy Logic and Genetic Algorithms in Modelling Complex Non-Linear Economic System," General Discussion Papers 30569, University of Manchester, Institute for Development Policy and Management (IDPM).
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