RT Report T1 El modelo SFI : propuesta de inclusión de variables informacionales y adaptación de la función de utilidad A1 Rojí Ferrari, Salvador AB Este trabajo propone adaptar el modelo bursátil artificial de Santa Fe en varios puntos resumidos en: sustitución de la función de utilidad exponencial por la potencial, heterogeneidad parcial de dicha función, mejora del proceso de aprendizaje, inclusión de normas de contagio, de creencias, y de influencia informacional, y heterogeneidad de horizontes temporales. El trabajo ofrece una introducción a la Econofísica, las disciplinas ACE y ACF, y los sistemas adaptativos complejos, e incluye otro modelo representativo basados en los agentes como marco para poder analizar el modelo de Santa Fe. PB Facultad de Ciencias Económicas y Empresariales. Decanato SN 2255-5471 YR 2003 FD 2003 LK https://hdl.handle.net/20.500.14352/64483 UL https://hdl.handle.net/20.500.14352/64483 LA spa NO Arifovic, J. (1996): “The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economics”, Journal of Political Economy, 104, pág. 510-541.Anderies, J. (2002): “The Transition from Local to Global Dynamics: a Proposed Framework for Agent-Based Thinking in Social-Ecological Systems”, en: Jansen, M., Complexity and Ecosystem Management. Elgar Ed., MA, EE UU.Arthur, B., (1994): “Inductive Reasoning and Bounded Rationality”, American Economic Review, 84, 406-411.Arthur, B., Holland, J., LeBaron, Palmer, R., Tayler, P., (1997): “Asset Princing Under Endogenous Expectations in an Artificial Stock Market”, en: Arthur, B., Durlauf, S., Lane, D., The Economy as an Evolving Complex System II. Reading, MA: Addison-Wesley.Axelrod, R. (1997): The Complexity of Cooperation. Ed. Princeton, Nueva Jersey.Axelrod, R., y Cohen, M. (1999): Harnessing Complexity. The Free Press, NY.Bak, P., Pczuski, M., y Shubik, M., (1997): “Price Variations in a Stock Market with Many Agents”, Physica A 246.Bergh, W. van der, Boer, K., Bruin, A.de, Kaymak, U., y Spronk, J. (2002): “On Intelligent-Agent Based Analysis of Financial Markets”, Erasmus U. Rotterdam, Faculty of Economics, {kboer, kaymak}@few.eur.nl.Capra, M., Goeree, J., Gomez, R., Holt, Ch. (2003): “Anomalous Behavior in a Traveler´s Dilemma, American Economic Review, próxima publicación.Castiglione, F. y Stauffer, D. (2001): “Multi-scaling in the Cont-Bouchaud Microscopic Stock Market Model, Physica A 300.Chiaromonte, F., y Berté, M. (1998): “Some Preliminary Experiments with the Financial”Toy-Room”. I.I.A.S.A., informe interno.Dechert, W., y Hommes, C. (2000): “Complex Nonlinear Dynamics and Computational Methods”, Journal of Economic Dynamics & Control, 24, pág. 651-662.Even, R. y Mishra, B. (1996): “CAFÉ: A Complex Adaptive Financial Environment”. Procedings of the IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, IEEE Press, pág. 20-25.Farmer, J., (1998): “Market Force, Ecology and Evolution”. E-impreso adaporg/9812005.Hayek, F. (1948): Individualism and Economic Order. University of Chicago Press.Holland, J., (1995): Hidden Order. Helixbooks, Cambridge.Holland, J. (1998): Emergence. Ed. Perseus, Cambridge.Ishinishi, M. y Namatame, A. (1999): “Co-Evolution in a Competitive Market”, Computing in Economics and Finance, 1212.Kauffman, S., (1995): The Origens of Order. Self-Organization and Selection in Evolution, Oxford University Press, Oxford. Laibson, D. (1997): “Golden Eggs and Hyperbolic Discounting”, Quaterly Journal of Economics, vol. 112, ·2, pág. 443-478.Laslier, J-F., Topol, R., y Walliser, B. (1998): “Behavioral Learning”, en Lesourne, J. (dir.), Advances in Self-Organization & Evolutionary Economics. Economica, Londres.LeBaron, B. (2001): “A Builder´s Guide to Agent Based Financial Markets”, Quantitative Finance, vol. 1, nº 2, pp. 254-261.LeBaron, B. (1999): “Evolution and Time Horizons in an Agent-Based Stock Market”, Computing in Economics and Finance, 1342.Levy, M., Levy, H, y Solomon, S. (2000): Microscopic Simulation of Financial Markets. Academic Press, NuevaYork. Lo, A. (1991): “Long-Term Memory in Stock Market Prices, Econometrica, 59.Luenberger, D. (1998): Investment Science. Oxford University Press.Lux, T., y Marchesi, M., (1999): “Volatility Clustering in Financial Markets: A MicroSimulation of Interacting Agents”, Nature, 397, 498.Mantegna, R. y Stanley, E., (2000): An Introduction to Econophysics. Correlations and Complexity in Finance. Cambridge U.Press.Mauboussin, M. (2002): “Revisiting Market Efficiency: The Stock Market as a Complex Adaptive System”. Journal of Applied Corporate Finance, 14, #4.Mitchell, M. (1998): An Introduction to Generic Algorithms. The MIT Press, Londres.Parker, P. (2000): Physioeconomics. The MIT Press, Londres.Rabin, D. (1998): “Psychology and Economics”. Journal of Economic Literature, vol. XXXVI, marzo, pág. 11-46.Roth, A. (1994): “Let´s Keep the Con Out of Experimental Econ.: A Methodological Note”, en la edición de Hey, J., Experimental Economics, Physica Verlag, Heidelberg, pág. 99-109.Shiller, R. (2001): Irrational Exuberance, Princeton University.Sutton, R. y Barto, A. (1998): Reinforcement Learning: An Introduction. The MIT Press, Londres.Tesfatsion, L. (2002): “Agent-Based Computational Economics: Growing Economies from the Bottom Up”. Iowa StateUniversity, Economic Working Paper nº 1.Tordjman, H. (1998): “Evolution: History, Change and Progress”, en Lesourne, J. (dir.), Advances in Self-Organization & Evolutionary Economics. Economica, Londres.Vriend, N. (1999): “Was Hayek an ACE?”. Queen Mary and Westfield College, Working Paper 403, Reino Unido.Tversky, A., y Kahneman, D. (1992): Advances in Prospect Theory: Cumulative Representation of Uncertainty, Journal of Risk and Uncertainty, 5.Waldrop, M. (1992): Complexity. Penguin Books, NY.Weibull, J. (1995): Evolutionary Game Theory. MIT Press, Cambridge. DS Docta Complutense RD 5 may 2024