M. Akian, J. Menaldi, and A. Sulem, On an investment-consumption model with transaction consts, SIAM Journal of Control and Optimization, vol.34, pp.329364-185, 2004.

P. Albin and D. Foley, Decentralized, dispersed exchange without an auctioneer, Journal of Economic Behavior & Organization, vol.18, issue.1, p.19, 1990.
DOI : 10.1016/0167-2681(92)90051-C

A. Alchian, Uncertainty, Evolution, and Economic Theory, Journal of Political Economy, vol.58, issue.3, p.211221, 1950.
DOI : 10.1086/256940

M. Allais, Le comportement de l'homme rationnel devant le risque: critique des postulats et axiomes de l'école américaine Expected Utility Hypothesis and the Allais Paradox, Dordrecht: D. Reidel, chap. The so-called Allais paradox and rational decisions under uncertainty, Econometrica, vol.21, issue.503546, pp.33-33, 1953.

L. Amaral, P. Cizeau, P. Gopikrishnan, Y. Liu, M. Meyer et al., Econophysics: can statistical physics contribute to the science of economics? Computer Communications, pp.121-122, 1999.

T. Andersen and T. Bollerslev, Heterogeneous information arrivals and returns volatility dynamics Intraday periodicity and volatility persistence in nancial markets, Journal of Finance Journal of Empirical Finance, vol.52, issue.4, pp.9751005-9751029, 1997.

M. Anufriev, G. Bottazzi, and F. Pancotto, Equilibria, stability and asymptotic dominance in a speculative market with heterogeneous agents, Journal of Economic Dynamics and Control, vol.30, pp.17871835-136, 2006.

J. Arifovic, The behavior of the exchange rate in the generic algorithm and experimental economics Evolutionary dynamics of currency substitution, Journal of Political Economy Journal of Economic Dynamics & Control, vol.104, issue.25, pp.60-395417, 1996.

A. Arnéodo, J. Muzy, and D. Sornette, ???Direct??? causal cascade in the stock market, The European Physical Journal B, vol.2, issue.2, 1998.
DOI : 10.1007/s100510050250

W. Arthur, Bounded rationality and inductive behavior (the el farol problem) Increasing Returns and Path Dependence in the Economy, American Economic Review Papers and Proceedings, vol.84, issue.406411 11, p.11, 1994.

S. Durlauf, S. Lane, J. Holland, B. Lebaron, R. Palmer et al., The Economy as an Evolving Complex System II Asset pricing under endougenous expectations in an articial stock market, Economic Notes, vol.24, issue.62, pp.61-297330, 1997.

T. Ashburn, E. Bonabeau, and I. Ecemis, Interactive inversion of agentbased models Agent-Based Simulation: from Modeling Methodologies to Real-World Applications, Japan Third International Workshop on Agent-Based Approaches in Economic and Social Complex Systems, pp.896-922, 2004.

R. Axelrod, Agent-based modeling as a bridge between disciplines, Handbook of Computational Economics, pp.15651584-15651602, 2006.

L. Tesfatsion, A guide for newcomers to agent-based modeling in the soccial sciences, Appendix in Handbook of Computational Economics. Agent- Based Computational Economics, p.19, 2005.

R. Axtell, Why agents? on the varied motivations for agent computing in the social sceinces Agent Simulation: Application, Models, and Tools, pp.123-139, 1999.

P. Bak, K. Chen, J. Scheinkman, and M. Woodford, Aggregate uctuations from independent sectoral shocks: Self-organized criticality in a model of production and inventory dynamics, Ricerche Economiche, pp.47-330, 1993.

N. Barberis and R. Thaler, Handbook of the Economics of Finance, Elsevier, chap. A survey of behavioral nance Ny:henry holt and company. The Predictors, p.10511121, 0198.

R. E. Bellman, Dynamic Programming, p.211, 1957.

A. Beltratti, S. Margarita, and P. Terna, Neural Networks for economic and nancial modeling, p.18, 1996.

L. Blume, D. Easley, O. Hara, and M. , Market Statistics and Technical Analysis: The Role of Volume, The Journal of Finance, vol.47, issue.1, p.153181, 0198.
DOI : 10.1111/j.1540-6261.1994.tb04424.x

K. Boer, U. Kayamak, and J. Spiering, From discrete-time models to continuous-time, asynchronous models of nancial markets, Computational Intelligence, vol.23, issue.51, p.75, 2007.

K. Boer-sorban, Agent-Based Simulation of Financial Markets. A modular , continuous-time approach, pp.56-73, 2008.

T. Bollerslev, R. Chou, and K. Kroner, Generalized autoregressive conditional heteroskedasticity Arch modeling in nance, Journal of Econometrics Journal of Econometrics, vol.31, issue.52, pp.559-580, 1986.

T. Bolleslev and I. Domowitz, The Double Auction Market: Institutions , Theories, and Evidence. Santa Fe Institute Studies in the Scinces of Complexity, p.55, 1993.

F. Boschetti and L. Moresi, Interactive inversion in geoschences, Geophysics, vol.66, pp.12261234-12261252, 2001.

H. Boswijk, C. Hommes, and S. Manzan, Behavioral heterogeneity in stock prices, IFAC symposium Computational Economics, p.66, 2003.

G. Bottazzi, G. Dosi, and I. Rebesco, Institutional architectures and behavioral ecologies in the dynamics of nancial markets, Journal of Mathematical Economics, vol.5, pp.41-136, 2005.

J. Bouchaud and M. Potter, Theory of Financial Risk, p.237, 2000.
URL : https://hal.archives-ouvertes.fr/hal-00121107

O. Brandouy, P. Mathieu, and I. Veryzhenko, A conceptual framework for the evaluation of agent-base trading and technical analysis. Articial Markets Modeling Ex-post optimal strategy for the trading of a single nancial asset, Methods and Applications. Lecture Notes in Economics and Mathematical Systems, vol.599, pp.6379-56, 2007.

T. Brenner, Agent learning representation advice in modelling economic leanrning, Handbook of Computational Economics, pp.896922-61, 2006.

S. Brianzoni, C. Mammana, and E. Michetti, Wealth distribution in an asset pricing model: the role of the switching mechanism Updating wealth in an asset pricing model with heterogeneous agents, Discrete Dynamics in Nature and Society, pp.27-90, 2010.

M. Broadie, Computing ecient frontiers using estimated parameters, Annals of Operations Research, vol.45, pp.2158-2194, 1993.
DOI : 10.1007/bf02282040

W. Brock and C. Hommes, A Rational Route to Randomness, Econometrica, vol.65, issue.5, pp.65-10591095, 1997.
DOI : 10.2307/2171879

J. Lakonishok and B. Lebaron, Simple technical trading rules and the stochastic properties of stock returns, Journal of Finance, vol.47, issue.30, p.17311764, 0198.

B. Lebaron, A structural model for stock return volatility and trading volume, Review of Economics and Statistics, vol.78, pp.94110-94134, 1996.

S. Brown, Optimal portfolio choice under uncertainty: A Bayesian approach The eect of estimation risk on capital market equilibrium, Journal of Financial and Quantitative Analysis, vol.163, issue.14, pp.215220-162, 1976.

J. Bullard and J. Duffy, LEARNING AND EXCESS VOLATILITY, Macroeconomic Dynamics, vol.5, issue.02, 1998.
DOI : 10.1017/S1365100501019071

R. Chakrabarti, Just another day in the inter-bank foreign exchange market, Journal of Financial Economics, vol.56, issue.1, pp.2964-3013, 2000.
DOI : 10.1016/S0304-405X(99)00058-6

R. Roll, Learning from others, reacitng and market quality, Journal of Financial Markets, vol.2, pp.153178-153227, 1999.

D. Challet, M. Marsili, and Y. Zhang, Minority Games: Interacting Agents in Financial Markets, p.50, 2005.

N. Chan, B. Lebaron, A. Lo, and T. Poggio, Agent-based models of nancial markets. comparision with experimental markets, p.35, 1999.

C. Shelton, An electronic market maker, working Paper AI Memo 2001-005, Massachusetts Institute of Technology, p.61, 2001.

A. Chen and M. T. Leung, Regression neural network for error correction in foreign exchange forecasting and trading Application of neural networks to an emerging nancial market: forecasting and trading the taiwan stock index, 1049 1068. 229 , and Daouk, pp.923-229, 2003.

S. Chen and Y. Huang, Risk preference and survival dynamics Risk preference, forecasting accuracy and survival dynamics: Simulations based on a multi-asset agent-based articial stock market Computational intelligence in economics and nance: Shifting the research frontier, Proceedings of the 3rd International Workshop on Agent-based Approaches in Economic and Social Comples Systems Computational Intelligence in Economics and Finance, pp.916-172, 2004.

C. Yeh, Evolving traders and the business school with genetic programming: A new architecture of the agent-based articial stock market Evolving traders and the business school with genetic programming: A new architecture of the agent-based articial stock market, Journal of Economic Dynamics and Control Journal of Economic Dynamics & Control, vol.25, issue.59, pp.31-61, 2001.

Y. , C. Liao, and C. , On the emergent properties of articial stock markets On aie-asm: a software to simulate articial stock markets with genetic programming, Evolutionary Computation in Economics and Finance, pp.107122-81, 2002.

C. Chiarella and X. He, Asset price and wealth dynamics under heterogeneous expectations, Quantitative Finance, vol.1, issue.5, pp.509526-60, 2001.
DOI : 10.1088/1469-7688/1/5/303

S. Cincotti, L. Ponta, and M. Raberto, A multi-assets articial stock market with zero-intelligence traders, p.70, 2005.

P. Cizeau, Y. Liu, M. Meyer, C. Peng, and H. Stanley, Volatility distribution in the S&P500 stock index, Physica A: Statistical Mechanics and its Applications, vol.245, issue.3-4, p.19, 1997.
DOI : 10.1016/S0378-4371(97)00417-2

D. Cliff and J. Bruten, Minimal-intelligence agents for bargaining behaviors in market-based environments, pp.97-91, 1997.

K. Cohen, S. Maier, R. Schwartz, and D. Whitcomb, A simulation model of stock exchange trading, SIMULATION, vol.41, issue.5, pp.41-181191, 1983.
DOI : 10.1177/003754978304100502

R. Cont, Empirical properties of asset returns: stylized facs and statistical issues Volatility clustering in nancial markets: empirical facts and agent-based models, Quantitative Finance Journal of Financial Economics, vol.1, issue.29, pp.223236-151, 2001.

J. Bouchaud, M. Potters, and J. Bouchaud, Herd behavior and aggregate uctuations in nancial markets, Scaling in stock market data: Stable laws and beyond. Lecture given at Les Houches Workchop on Scale Invariance, 1997.

K. Cuthbertson and D. Nitzsche, Quantitative Financial Economics. Stocks,Bonds and Foreign Exchange, p.40, 2004.

D. Cutler, J. Poterba, and L. Summers, What moves stock prices, Journal of Portfolio Management, vol.15, issue.12, pp.170196-170219, 1989.
DOI : 10.3886/icpsr01021.v1

URL : http://doi.org/10.3886/icpsr01021.v1

J. Cvitanic, E. Jouini, S. Malamud, and C. Napp, Financial markets equilibrium with heterogeneous agents. Review of Finance, Fothcoming, p.39, 2011.
URL : https://hal.archives-ouvertes.fr/halshs-00488537

M. Daniels, J. Farmer, G. Iori, and E. Smith, A quantitative model of trading and price formation in nacial markets. arXiv:cond-mat Quantitative model of price diusion and market friction based on trading as mechanistic random process, Physical Review Letter, vol.56, issue.50, pp.10-108102, 2002.

G. Dantzig, All shortest routes in a graph, Theory of Graphs, International Symposium, pp.9192-218, 1966.

V. Darley and A. Outkin, A NASDAQ market simulation. Insights on a major market from the science of complex adaptive systems, Complex Systems and Interdisciplinary Science, vol.1, issue.76, p.77, 2007.

D. Cliff and J. B. , Zero is not enough: On the lower limit of agent intelligence for continuous double auction markets, p.105, 1997.

J. Delong, A. Shleifer, L. Summers, and R. Waldmann, Positive feedback investment strategies and destabilizing rational speculation, Journal of Finance, vol.45, pp.379395-265, 1990.

V. Demiguel, L. Garlappi, and R. Uppal, Optimal versus naive diversication: How inecient is the 1/n portfolio strategy? Review of Financial Studies, pp.159-164, 2009.

E. Dijkstra, A note on two problems in connection iwth graphs, Numerische Mathematik, vol.1, pp.269271-218, 1959.

C. Donohue and K. Yip, Optimal Portfolio Rebalancing with Transaction Costs, The Journal of Portfolio Management, vol.29, issue.4, p.185, 2003.
DOI : 10.3905/jpm.2003.319894

V. Dorofeenko and J. Shorish, Dynamical modeling of the demographic prisoner's dilemma: Institute for Advanced Studies, Economic Series, p.14, 2002.

B. Edmonds, Computational Techniques for Modelling Learning in Economics , Kluwer, chap. Modelling bounded rationality in agent-based simulations using the evolution of mental models, p.61, 1999.

N. Ehrentreich, A corrected version of the santa fe institute articial stock market model Technical trading in the santa fe institute articial stock market revisited, Social Science Computer Review Journal of Economic Behavior & Organization, vol.2, issue.20, pp.174196-67, 2002.

D. Ellsberg, Risk, ambiguity and the savage axioms, Quarterly Journal of Economics, vol.76, pp.643669-643702, 1961.

E. J. Elton, M. J. Gruber, and C. R. Blake, The persistence of riskadjusted mutual fund performance, Journal of Business, vol.69, issue.2, pp.13357-199, 1996.

R. Engle, Autoregressive conditional heteroscedasticity with estimates of the variance of u.k. ination, Econometrica, pp.50-9871008, 1982.

T. Bollerslev, Modelling the persistence of conditional variances, Econometric Reviews, vol.5, issue.8187, p.22, 1986.

J. Epstein, Agent-based computational models and generative social science Generative Social Science: Studies in Agent-Based Computational Modeling Remarks on the foundations of agent-based generative social science, Handbook of Computational Economics, pp.15821602-15821616, 1999.

R. Axtell, Growing Articial Societies: Social Science from the Bottom Up, p.19, 1996.

P. Érdi, Complexity Explained, 2008.

E. Fama, The Behavior of Stock-Market Prices, The Journal of Business, vol.38, issue.1, pp.34105-34127, 1965.
DOI : 10.1086/294743

M. Blume, Filter rules and stock-market trading, Journal of Business, p.31, 0198.

J. Farmer, Market force, ecology and evolution, Industrial and Corporate Change, vol.11, issue.5, pp.50-58, 2002.
DOI : 10.1093/icc/11.5.895

S. Joshi, The price dynamic of common trading strategies. SFI Working Paper 00-12-069, p.136, 2000.

P. Patelli and I. Zovko, The predictive power of zero intelligence in nancial markets, Proceedings of the National Academy of Scence, p.127, 1951.

J. Ferber and J. Muller, Inuence and reaction: a model of situated multiagent systems, Second International Conference on Multiagent Systems ICMAS-96, pp.7279-64, 1996.

M. Fligner and G. Policello, Robust rank procedures for the benrenssher problem, Journal of the American Statistical Association, pp.76-162168, 1981.

R. Floyd, Algorithm 97, shortest path algorithms, Operations Research, vol.17, issue.216, pp.395412-218, 1969.
DOI : 10.1145/367766.368168

T. Foucault, Order ow composition and trading costs in a dynamic limit order market, Journal of Financial Markets, issue.2, pp.99134-108, 1999.

R. Franke and F. Westerhoff, Estimation of a structular stochastic volatility model of asset pricing, Computational Economics, pp.38-5383, 2009.

J. Frankel and K. Froot, Understanding the us dollar in the eighties: the expectations of chartists and fundamentalists, Economic Record, vol.1, issue.2, pp.2438-2450, 1986.

M. Friedman, The case of exible exchange rates Essays in Positive Economics The Methodology of Positive Economics, Essay in Positive Economics, 1953.

B. Frijns, T. Lehnert, and R. Zwinkles, Modeling structural changes in the volatility process, Journal of Empirical Finance, vol.18, issue.3, pp.11871222-11871245, 2008.
DOI : 10.1016/j.jempfin.2011.01.005

D. Fudenberg and J. Tirole, Game Theory, p.173, 1991.

M. Garder, Mathematical games: The fantastic combinations of john conway's new solitaire game 'life'. Scientic American, 1970.

M. R. Garey and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, p.211, 1979.

L. Glosten and P. Milgrom, Bid, ask and transactions prices in a specialist model with heterogeneously informed traders, Journal of Financial Economics, vol.14, p.57, 1985.

D. Gode and S. Sunder, Allocative eciency of markets with zerointelligence traders: Market as a partial substitute for individual rationality, Journal of Political Economy, vol.101, issue.90, pp.119137-119152, 1993.

N. Goel, S. Maitra, and E. Montroll, On the Volterra and Other Nonlinear Models of Interacting Populations, Reviews of Modern Physics, vol.43, issue.2, pp.231-277, 1971.
DOI : 10.1103/RevModPhys.43.231

J. L. Gordillo, J. Pardo-guerra, and C. Stephens, Adaptation in the presence of exogeneous information in an articial nancial market. MI- CAI 2004: Advances in Articial Intelligence, Lecture Notes in Compute Science, vol.49, pp.2972-342351, 2004.

M. Gordon, G. Oaradis, and C. Rorke, Experimental evidence on alternative portfolio rules, American Economic Review, vol.62, p.143, 1972.

A. Gouachin, F. Michel, and Y. Guiraud, Mic: A deployment environment for autonomous agents, E4MAS 2004, pp.109126-64, 2004.

R. Grothmann, Multi-agent market modeling based on neural networks, p.58, 2002.

D. Guillaume, M. Dacorogna, R. Davé, U. Muller, R. Olsen et al., From the birds eye view to the microscope: A survey of new stylized facts of the intraday foreigh exchange markets, Finance and Stochastics, vol.1, pp.95131-95155, 1997.

P. Handa and R. A. Schwartz, The limit order eect, Journal of Finance, vol.125, issue.5, pp.94302-108, 2006.

L. Hansen and K. Singleton, Genaralized instrumental variables estimation of nonlinear rational expectation models, Econometrica, pp.50-12691286, 1982.

P. Henaff and C. Martini, Model validation: theory, practice and perspectives . The Journal of Risk Model Validation, pp.315-238, 2011.
DOI : 10.2139/ssrn.1613023

I. Herstein and J. Milhor, An Axiomatic Approach to Measurable Utility, Econometrica, vol.21, issue.2, pp.291297-291329, 1953.
DOI : 10.2307/1905540

J. Holland, Adaptation in Natural and Articial Systems, p.61, 1975.

C. Hommes, Financial markets as nonlinear adaptive evolutionary systems Heterogeneous agent models in economics and nance, Handbook of Computational Economics, pp.59-69, 2001.

W. Huang, Y. Nakamori, and S. Wang, Forecasting stock market movement direction with support vector machine, Computers & Operations Research, vol.32, issue.10, pp.2513-2522, 2005.
DOI : 10.1016/j.cor.2004.03.016

J. Iglesias, S. Goncalves, G. Abramson, and J. L. Vega, Correlation between risk aversion and wealth distribution, Physica A, vol.342, pp.186192-83, 2004.

B. Jacobs, K. Levy, and H. Markowitz, Simulating Security Markets in Dynamic and Equilibrium Modes, Financial Analysts Journal, vol.66, issue.5, pp.4253-142, 2010.
DOI : 10.2469/faj.v66.n5.7

B. I. Jacobs, K. N. Levy, and H. M. Markowitz, Financial market simulation. The Journal of Portfolio Management, 30th Anniversary Issue, 142151, pp.49-52, 2004.

K. Jamal and S. Sunder, Why do biased heuristics approximate bayes rule in double action, Journal of Economic Behavior & Organisation, vol.46, issue.4, pp.431435-55, 2001.

W. Jevons, The Theory of Political Economy, 1871.
DOI : 10.1057/9781137374158

N. Johnson, Systems of frequency curves genrated by methods of translation, Biometrika, pp.1-2, 1949.

P. Johnson, What i learned from the articial stock market, Social Science Computer Review, vol.2, issue.20, pp.174196-69, 2002.

S. Joshi and M. Bedau, Technical trading creates a prisoner's dilemma: Results from an agent-based model, Proceedings of the 6th International Conference Computational Finance, pp.465479-465510, 2000.

E. Jouini and C. Napp, Behavioral biases and the representative agent, Theory and Decision, vol.55, issue.4, p.12, 2012.
DOI : 10.1007/s11238-011-9274-3

D. Kahneman, P. Solvic, and A. Tversky, Judgment under uncertainty: Heuristics and biases, p.42, 1982.
DOI : 10.1017/CBO9780511809477

A. Tversky, On the psychology of prediction Choices, values, and frames, Psychological Review, vol.80, issue.10, p.42, 1973.

T. Kaizoji, Speculative bubbles and crashes in stock marketsl an interacting-agent model of speculative acrivity. Physica A, Statistical Mechanics and its Applications, Special issue, pp.3-4, 2000.

J. Kallberg and W. Ziemba, Comparison of alternative utility functions in portfolio selection problems, Management Science, vol.29, issue.174, pp.12571276-143, 1983.

S. Kandel and R. Stambaugh, Asset returns and intertemporal preferences, Journal of Monetary Economics, vol.27, pp.3971-143, 1991.

E. Karni, Decision Making under Uncertainty: the Case of State-Dependent Preferences, p.33, 1985.
DOI : 10.4159/harvard.9780674494008

G. Kim and H. Markowitz, Investment rules, margin, and market volatility, The Journal of Portfolio Management, vol.16, issue.1, pp.4552-67, 1989.
DOI : 10.3905/jpm.1989.409233

R. King, V. Smith, A. Williams, and M. Bening, Nonlinear Dynamics and Evolutionary Economics, The Robustens of Bubbles and Crashes in Experimental Stock Markets, pp.183200-106, 1993.

M. Kirchler and H. J. , Fat tails and volatility clustering in experimental asset markets, Journal of Economic Dynamics and Control, vol.31, issue.6, pp.31-18441874, 2007.
DOI : 10.1016/j.jedc.2007.01.009

A. Kirman, Ants, Rationality, and Recruitment, The Quarterly Journal of Economics, vol.108, issue.1, pp.137156-65, 1993.
DOI : 10.2307/2118498

G. Teyssiere, Microeconomic models for long memory in the volatility of nancial time series, Studies in Nonlinear Dynamics & Economics, vol.5, pp.675702-675726, 2002.

R. Klein and V. Bawa, The eect of estimation risk on optimal portfolio choice, Journal of Financial Economics, vol.3, pp.215231-162, 1976.

M. Kritzman, S. Page, and D. Turkington, In defese of optimization: The fallacy of 1/n, Financial Analysts Journal, vol.66, pp.3140-158, 2010.

S. Kullback and R. Leibler, On information and suciency, Annuals of Mathematical Statistics, vol.22, pp.7986-257, 1951.

K. Ladley and K. R. Schenk-hoppe, Do stylised facts of order book markets need strategic behaviour, Journal of Economic Dynamics and Control, vol.33, issue.24, pp.817831-105, 2009.

C. Lamoureux and W. Lastrapes, Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects, The Journal of Finance, vol.12, issue.1, pp.221229-221252, 1990.
DOI : 10.1111/j.1540-6261.1990.tb05088.x

B. Lebaron, A builder's guide to agent based nancial markets, Quantitative Finance, vol.1, issue.57, pp.254261-254309, 2001.

B. V. Agent-based-computational-nance, W. Arthur, and R. Parlmer, Time series properties of an articial stock market, Handbook of Computational Economics, pp.14871516-14871539, 0198.

O. Ledoit and M. Wolf, A well-conditioned estimator for largedimensional covariance matrices, Journal of Multivariate Analysis, vol.88, pp.365411-365446, 2004.

H. Levy, Equilibrium in an imperfect market: A constraint on the number of securities in the portfolio, American Economic Review, pp.68-111, 1978.

M. Levy, H. Levy, and S. Solomon, Is risk-aversion hereditary? Microscopic simulation of the stock market: the eect of microscopic diversity Microscopic Simulation of Financial Markets: From Investor Behaviour to Market Phenomena, Journal of Mathematical Economics Journal de Physique I (France), vol.5, issue.51, pp.33-38, 1995.

Y. Ritov, Mean-variance ecient portfolios with many assets: 50% short, Quantitative Finance, vol.11, issue.183, pp.14611471-165, 2011.

J. Lintner, Security prices, risk and maximal gains from diversication, Journal of Finance, vol.33, issue.4, pp.587615-587658, 1965.

H. Liu, Optimal Consumption and Investment with Transaction Costs and Multiple Risky Assets, The Journal of Finance, vol.56, issue.1, pp.289338-185, 2004.
DOI : 10.1111/j.1540-6261.2004.00634.x

X. Liu, S. Gregor, and J. Yang, The eects of behavioral and structural assumptions in articial stock market. Pysica A Statistical Mechanisms and its Applications, pp.25352546-107, 2008.

B. Llacay and G. Peffer, Realistic agent-based simulation of nancial crises: the 1998 turmoil, Computational Intelligence in Business and Economics. Proceeding of the MS'10 Internation Conference, pp.189197-271, 2010.

O. Loistl, B. Schossmann, and O. Vetter, Xetra ecient evaluation and nasdaq modeling by kapsyn, European Journal of Operational Research, vol.135, pp.270295-53, 2001.

O. Vetter, KapSyn Computer Modeled Stock Exchanges, 2000.

A. Veverka, An integration of current markets microstructure results into a consistent picture catallactic modeling of capital market's micro structure, Tech. rep, p.53, 2004.

J. Long, Stock prices, ination, and hte term structure of interest rates, Journal of Financial Economics, pp.41-131170, 1974.

G. Loomes and R. Sugden, Regret Theory: An Alternative Theory of Rational Choice Under Uncertainty, The Economic Journal, vol.92, issue.368, pp.92-125, 1982.
DOI : 10.2307/2232669

A. Lotka, Contribution to the Theory of Periodic Reactions, The Journal of Physical Chemistry, vol.14, issue.3, p.271274, 1910.
DOI : 10.1021/j150111a004

T. Lux, Volatility clustering in nancial markets: a microsimulation of interacting agents Handbook of Financial Markets: Dynamics and Evolution, Stochastic behavioral asset pricing models and the stylized facts, pp.50-161215, 2000.

M. Marchsi, Scaling and criticality in a stochastich multi-agent model of a nancial market, Nature, vol.397, issue.68, pp.498500-64, 1999.

M. Machina, "Expected Utility" Analysis without the Independence Axiom, Econometrica, vol.50, issue.2, pp.227232-227265, 1982.
DOI : 10.2307/1912631

B. Malkiel, Can Predictable Patterns in Market Returns be Exploited Using Real Money?, The Journal of Portfolio Management, vol.30, issue.5, pp.131141-199, 2004.
DOI : 10.3905/jpm.2004.442638

B. Mandelbrot, The variation of certain speculative prices Biologically Inspired Algorithms for Financial Modelling, Journal of Business, XXXVI, vol.21, issue.22, p.14, 1963.

G. Mankiw, J. Rotemberg, and L. Summers, Intertemporal Substitution in Macroeconomics, The Quarterly Journal of Economics, vol.100, issue.1, pp.225251-143, 1985.
DOI : 10.2307/1885743

K. Mannaro, M. Marchesi, and A. Setzu, Using an articial nancial market for assessing the impact of tobin-like transaction taxes, Journal of Economic Behavior & Organization, vol.67, pp.445462-72, 2008.

R. Mantegna, Lévy walks and enhanced diusion in milan stock exchange. Physica A: Statistical Mechanism nad its Applications, pp.232242-232261, 1991.

H. Stanley, An Introduction to Econophysics: Correlations and Complexity in Finance, p.237, 1999.

M. Marchesi, S. Cincotti, S. Focardi, and M. Roberto, Development and testing of an articial stock market. Model Dynamic in Economic Finance, p.70, 2000.

S. Markose, E. Tsang, and S. Martinez-jaramillo, The red queen principle and the emergence of ecient nancial markets: an agent based approach, Workshop on economics and heterogeneous interacting agents (WEHIA), 2003.

H. Markowitz, Portfolio selection Portfolio Selection: Ecient Diversication of Investment Stock market simulator sms1. program description Risk adjustment Accounting and Auditing, Baruch College Working Paper Series 88-24. v, pp.7791-7823, 1952.

J. Marschak, Rational behaviour, uncertain prospects and measurable utility, Econometrica, vol.18, pp.111141-111173, 1950.
DOI : 10.2307/1907264

S. Martinez-jaramillo, Articial Financial Markets: An Agent Based Approach to Reproduce Stylized Facts and to study the Red Queen Eect, pp.61-80, 2007.

S. Maslov, Simple model of a limit order-driven market, Physica A, vol.278, issue.105, pp.571578-571627, 2000.

S. Masters, Rebalancing. The Journal of Portfolio Management, pp.510-235, 2003.

P. Mathieu and O. Brandouy, Ecient monitoring of nancial orders with agent-based technologies, 9th International conference on Practical Applications of Agents and Multi-Agents Systems (PAAMS'2011), pp.277286-238, 2011.

J. Mccauley, Dynamics of Markets: Econophysics and Finance, 2004.
DOI : 10.1017/CBO9780511606588

R. Mehra and E. Prescott, The equity premium: A puzzle, Journal of Monetary Economics, vol.15, issue.2, pp.145161-171, 1985.
DOI : 10.1016/0304-3932(85)90061-3

C. Menger, Principles of Economics. reprinted by Ludwig von Mises Institute, 1871.

R. Merton, Optimum consumption and portfolio management with xed transaction costs An analytical derivation of the ecient portfolio frontier, Journal of Economic Theory Journal of Financial and Quantitative Analysis, vol.3, issue.373413, pp.185-18511872, 1971.

F. Michel, The IRM4S model, Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems , AAMAS '07, pp.908910-64, 2007.
DOI : 10.1145/1329125.1329289

URL : https://hal.archives-ouvertes.fr/lirmm-00394198

P. Milgrom and N. Stokey, Information, trade and common knowledge, Journal of Economic Theory, vol.26, issue.1, pp.1727-173, 1982.
DOI : 10.1016/0022-0531(82)90046-1

URL : http://www.kellogg.northwestern.edu/research/math/papers/377.pdf

L. Motiwalla and M. Wahab, Predictable variation and protable trading of us equities: a trading simulation using neural networks, Computers & Operations Research, vol.27, pp.11-12, 2000.

L. Muchnik and S. Solomon, Markov nets and the natlab platform; application to continuous double auction. New Economic Windows, p.84, 2006.

C. Neely, P. Weller, and R. Dittmar, Technical analysis in the foreign exchange market: A laymans guide Is technical analysis in the foreign exchange market protable? a genetic programming approach. Financial and Quantitative Analysis, Review, vol.32, pp.405426-56, 1997.

D. Nelson, Commentary: price volatility, international markets links, and their implications for regulatory policies, Journal of Financial Services Research, vol.3, pp.247254-247276, 1989.

M. Obstfeld, Risk taking, global diversication, and growth, American Economic Review, vol.84, pp.13101329-143, 1994.

M. Osborne, Brownian Motion in the Stock Market, Operations Research, vol.7, issue.2, p.145173, 1959.
DOI : 10.1287/opre.7.2.145

C. Overway and B. John, Rebalancing multi-asset portfolios. Natixis Global Associates Whitepaper, p.186, 2006.

R. Palmer, W. Arthur, J. Holland, and B. Lebaron, An articial stock market Articial economic life: A simple model of stock market, Articial Life and Robotics Physica D, vol.3, issue.75, pp.2731-57, 1994.

C. Papadimitriou and K. Steigleitz, Combinatorial Optimization: Algorithms and Complexity, p.216, 1998.

P. Pellizzari, Complexities and simplicity: a review of agent-based articial markets, Giornata di studi in onore di Giovanni Castellani, 2005.

C. Plott and S. Sunder, Eciency of epxerimental sycirity markets with insider information: an application of rational expectation models, Journal of Political Economy, pp.90-663698, 1982.

M. Pompian, Behavioral Finance and Wealth Management. How to Build Optimal Portfolios That Account for Investor Biases, 2006.

L. Ponta, M. Raberto, and S. Cincotti, A multi-assets articial stock market with zero-intelligence traders, A Letter Journal Exploring the Frontiers of Physics, vol.93, issue.81, pp.28002-128002, 2011.

M. Prietula, K. Carley, and L. Gasser, Simulating Organizations, 1998.

J. Quiggin, A theory of anticipated utility, Journal of Economic Behavior & Organization, vol.3, issue.4, pp.323343-323376, 1982.
DOI : 10.1016/0167-2681(82)90008-7

M. Raberto, S. Cincotti, S. Focardi, and M. Marchesi, Modeling and simulation of a double auction articail nancial market. Physica A: Statistical Mechanics and its Applications Agent-based simulation of a nancial market, Physica D. Nonlinear phenomena, vol.355, issue.50, pp.3445-319327, 2001.

R. Roll, A critique of the asset pricing theory's tests, Journal of Financial Economics, vol.4, p.38, 1977.

S. Ross, The arbitrage pricing theory, Journal of Economic Theory, vol.1, issue.32, pp.341360-341400, 1976.

J. Rosser, Complexity in Economics: The International Library of Critical Writings in Economics, 2004.

P. Samuelson, Probability and attempts to measure utility Proof that properly anticipated prices uctuate randomly, Economic Review Industrial Management Review, vol.1, issue.6 5, pp.32-4149, 1950.

T. Schelling, Micromotives and Macrobehavior, p.12, 1978.

D. Schmeidler, Subjective probability and expected utility without additivity, Econometrica, vol.57, pp.571587-571620, 1989.
DOI : 10.4324/9780203358061_chapter_5

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.4096

S. Schulenburg and P. Ross, Explorations in LCS Models of Stock Trading, 2002.
DOI : 10.1007/3-540-48104-4_10

R. Sedgewick and K. Wayne, Algorithms, p.220, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00074300

W. Sharpe, A simplied model for portfolio analysis Capital asset prices -a theory of market equilibrium under conditions of risk Mutual fund performance Capital asset pricing with and without negative holdings, 425442. 32, pp.277293-277326, 1943.

M. Shatner, L. Mushnik, and S. Solomon, A continuous time asynchronous model of the stock market. arXiv:cond-mat, pp.56-57, 2000.

D. Shier, Iterative methods for determining the k shortest paths in a network, Networks, vol.78, issue.3, 0218.
DOI : 10.1002/net.3230060303

A. Shleifer, Inecient markets, p.276, 2000.

H. Simon, Models of Man The architecture of complexity, Proceedings of the American Phylosophical Society, 1957.

V. Smith, G. Suchanek, and A. Williams, An experimental study of competitive market behavior Bubbles, crashes, and endogeneous expectations in experimental spot asset markets, Journal of Political Economy Econometrica, vol.70, issue.56, pp.11191151-106, 1962.

J. Stewart, Rebalancing Equity Allocations, The Journal of Investing, vol.14, issue.2, p.188, 2005.
DOI : 10.3905/joi.2005.517174

G. Stigler, The Theory of Price., Economica, vol.21, issue.81, 1966.
DOI : 10.2307/2601511

R. J. Sweeney, Beating the foreign exchange market Some new lter rule tests: Methods and results, Journal of Finance Journal of Financial and Quantitative Analysis, vol.41, issue.23, pp.30-285300, 1986.

H. Takahashi and T. Terano, Analysis of micro-macro structure of nancial markets via agent-based model: Risk management and dynamics of asset pricing, Electronics and Communications in Japan, vol.87, pp.618628-618670, 2004.

L. Tefatsion and K. Judd, Handbook of Computational Economics, 2006.

L. Tesfatsion, A Trade Network Game with Endogenous Partner Selection, 1995.
DOI : 10.1007/978-1-4757-2644-2_17

I. Tkatch and Z. S. Alam, Strategic Order Splitting in Automated Markets, SSRN Electronic Journal, 2009.
DOI : 10.2139/ssrn.1400307

J. Tobin, Liquidity Preference as Behavior Towards Risk, The Review of Economic Studies, vol.25, issue.2, pp.6586-6619, 1958.
DOI : 10.2307/2296205

J. Treynor, Toward a theory of market value of risky assets, fall 1962. A nal version was published in 1999 in Asset Pricing and Pertfolio Performance, Risk Books, pp.15-22, 1962.

J. Tu and G. Zhou, Markowitz meets talmud: A combination of sophisticated and naive diversication strategies, Journal of Financial Economics, vol.99, issue.168, pp.164-166, 2011.

A. Tversky and D. Kahneman, Judgment under uncertainty: heuristics and biases Advances in prospect theory: cumulative representation of uncertainty, Science Journal of Risk and Uncertainty, vol.185, issue.5, pp.10-297323, 1974.

I. Veryzhenko, O. Brandouy, and P. Mathieu, Agent's minimal intelligence calibration for realistic market dynamics. Progress in Articial Economics Computational and Agent-Based Models. AE 2010, Lecture Notes in Economics and Mathematical Systems, vol.645, issue.94, pp.314-96, 2010.

A. Vissing-jorgensen, NBER Macroeconomics Annual Perspective on behavioral nance: does "irrationality" disappear with wealth? Evidence from expectations and actions, p.12, 2003.

V. Volterra, Animal Ecology Variations and uctuations of the number of individuals of animal species living together, p.163, 1926.

J. Von-neuman and O. Morgenstern, Theory of Games and Economic Behavior, p.32, 1947.

L. Walras, Éléments d'économie politique pure, ou théorie de la richesse sociale, 1874.

S. Walter, F. Ayres, L. Chen, T. Schouwennars, and M. Albota, Optimal rebalancing for institutional portfolios, The Journal of Portfolio Management, p.185, 2006.

W. Weaver, Science and Complexity, American Scentist, vol.36, issue.4, p.536, 1948.
DOI : 10.1007/978-1-4899-0718-9_30

H. White, A Reality Check for Data Snooping, Econometrica, vol.68, issue.5, p.10971126, 0198.
DOI : 10.1111/1468-0262.00152

P. Windrum, G. Fagiolo, and A. Modeta, Empirical validation of agent-based models: Alternatives and prospects, Journal of Articial Societies and Social Simulation, vol.10, pp.137156-65, 2007.

M. Wooldridge, An Introduction to MultiAgent Systems, p.15, 2002.

S. Wu and S. Bhattacharyya, Minimal Intelligence Agents in Double Auction Markets with Speculators, Proceedings of 7th Joint Conference on Information Sciences, pp.10921095-56, 2003.
DOI : 10.4018/978-1-59140-649-5.ch004

J. Yang, Heterogeneous beliefs, intelligent agents, and allocative eciency in an articial stock market. Society for Computation Economics Seies of Computating in Economics and Finance The eciency of an articial double auction stock market with neural learning agents, Evolutionary Computation in Economics and Finance, vol.612, issue.59, pp.60-85, 1999.

H. Zimmermann, R. Neuneier, and R. Grothmann, IEEE Transaction on Neural Networks, Multi-Agent Modeling of Multiple FX-Markets by Neural Networks, pp.735743-61, 2001.