Skip to main content Accessibility help
×
Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T04:11:26.905Z Has data issue: false hasContentIssue false

Bibliography

Published online by Cambridge University Press:  05 February 2013

Cars Hommes
Affiliation:
Universiteit van Amsterdam
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adam, K. (2007), Experimental evidence on the persistence of output and inflation. The Economic Journal 117 (520), 603–636.CrossRefGoogle Scholar
Akerlof, G.A. and Shiller, R.J. (2009), Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism. Princeton University Press, Princeton, NY.Google Scholar
Alfarano, S., Lux, T. and Wagner, F. (2005), Estimation of agent-based models: the case of an asymmetric herding model. Computational Economics 26, 19–49.CrossRefGoogle Scholar
Allen, H. and Taylor, M.P. (1990), Charts, noise and fundamentals in the London foreign exchange market. Economic Journal 100 (400), Conference Papers, 49–59.CrossRefGoogle Scholar
Amilon, H. (2008), Estimation of an adaptive stock market model with heterogeneous agents. Journal of Empirical Finance 15, 342–362.CrossRefGoogle Scholar
Anderson, P.W, Arrow, K.J. and Pines, D. (eds.) (1988), The Economy as an Evolving Complex System. Addison-Wesley, Reading, MA.
Anderson, S., de Palma, A. and Thisse, J. (1993), Discrete choice theory of product differentiation. MIT Press, Cambridge, MA.Google Scholar
Anufriev, M. and Hommes, C.H. (2012a), Evolution of market heuristics, Knowledge Engineering Review, The Knowledge Engineering Review 27, 255–271.CrossRefGoogle Scholar
Anufriev, M. and Hommes, C.H. (2012b), Evolutionary selection of individual expectations and aggregate outcomes in asset pricing experiments. American Economic Journal: Microeconomics 2012, 4 (4).Google Scholar
Anufriev, M., Assenza, T., Hommes, C.H. and Massaro, D. (2012), Interest rate rules and macroeco-nomic stability under heterogeneous expectations. Macroeconomic Dynamics, in press.
Aoki, M. (2002), Modeling Aggregate Behavior and Fluctuations in Economics. Stochastic Views of Interacting Agents. Cambridge University Press, Cambridge.Google Scholar
Arifovic, J. (1994), Genetic algorithm learning and the cobweb model. Journal of Economic Dynamics and Control 18, 3–28.CrossRefGoogle Scholar
Arthur, W.B. (1994), Increasing returns and path dependence in the economy. University of Michigan Press, Ann Arbor, MI.CrossRefGoogle Scholar
Arthur, W.B. (1995) Complexity in economic and financial markets. Complexity 1, 20–25.CrossRefGoogle Scholar
Arthur, W.B. (2006), Out-of-equilibrium economics and agent-based modeling. In Tesfatsion, L. and Judd, K.L. (eds.), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics, chapter 23. North-Holland, Amsterdam, pp. 1551–1564.Google Scholar
Arthur, W.B., Durlauf, S.N and Lane, D.A. (eds.) (1997a), The Economy as an Evolving Complex System II. Addison-Wesley, Reading, MA.
Arthur, W.B., Holland, J.H., LeBaron, B., Palmer, R. and Tayler, P. (1997b), Asset pricing under endogenous expectations in an artificial stock market. In Arthur, W., Lane, D. and Durlauf, S. (eds.), The Economy as an Evolving Complex System II. Addison-Wesley, Reading, MA, pp. 15–44.Google Scholar
Artstein, Z. (1983) Irregular cobweb dynamics. Economics Letters 11, 15–17.CrossRefGoogle Scholar
Assenza, T., Heemeijer, P., Hommes, C.H. and Massaro, D. (2011), Individual expectations and aggregate macro behavior. CeNDEF Working Paper. University of Amsterdam, July 2011.Google Scholar
Baak, S.J. (1999), Tests for bounded rationality with a linear dynamic model distorted by heterogeneous expectations. Journal of Economic Dynamics and Control 23, 1517–1543.CrossRefGoogle Scholar
Bao, T., Duffy, J. and Hommes, C.H. (2011), Learning, forecasting and optimizing: an experimental study. CeNDEF Working Paper. University of Amsterdam, October 2011.Google Scholar
Bao, T., Hommes, C.H., Sonnemans, J. and Tuinstra, J. (2012), Individual expectation, limited rationality and aggregate outcome. Journal of Economic Dynamics and Control, 36, 1101–1120.CrossRefGoogle Scholar
Barberis, N. and Thaler, R. (2003), A survey of behavioral finance. In Constantinidis, G.M.Harris, M. and Stulza, R. (eds.) Handbook of the Economics of Finance. Elsevier, Amsterdam, pp. 1051–1121.Google Scholar
Barberis, N., Shleifer, A. and Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics 49, 307–343.CrossRefGoogle Scholar
Benartzi, S. and Thaler, R.H. (2007), Heuristics and biases in retirement savings behavior. Journal of Economic Perspectives 21, 81–104.CrossRefGoogle Scholar
Benhabib, J. and Day, R.H. (1982), A characterization of erratic dynamics in the overlapping generations model. Journal of Economic Dynamics and Control 4, 37–55.CrossRefGoogle Scholar
Blume, L. and Easley, D. (1992), Evolution and market behavior. Journal of Economic Theory, 58, 9–40.CrossRefGoogle Scholar
Blume, L. and Easley, D. (2006), If you're so smart, why aren't you rich? Belief selection in complete and incomplete markets. Econometrica 74, 929–966.CrossRefGoogle Scholar
Bollerslev, T., Engle, R. and Nelson, D. (1994), Arch models. In Engle, R. and McFadden, D. (eds.), Handbook of Econometrics, Volume IV. North Holland, Amsterdam, pp. 2961–3038.Google Scholar
Boswijk, H.P., Hommes, C.H. and Manzan, S. (2007), Behavioral heterogeneity in stock prices. Journal of Economic Dynamics and Control 31, 1938–1970.CrossRefGoogle Scholar
Bottazzi, G., Devetag, G. and Pancotto, F. (2011). Does volatility matter? Expectations of price return and variability in an asset pricing experiment, Journal of Economic Behavior and Organization 77, 124–146.CrossRefGoogle Scholar
Bouchaud, J.-P. (2009), Economics needs a scientific revolution. Nature 457, 147.Google Scholar
Bouchaud, J.-P., Farmer, J.D. and Lillo, F. (2009), How markets slowly digest changes in supply and demand. In Hens, T. and Schenk-Hoppé, K.R. (eds.), Handbook of Financial Markets: Dynamics and Evolution. Elsevier, Amsterdam, pp. 57–160.Google Scholar
Branch, W.A. (2004), The theory of rationally heterogeneous expectations: evidence from survey data on inflation expectations. Economic Journal 114, 592–621.CrossRefGoogle Scholar
Branch, W.A. (2006), Restricted perceptions equilibria and learning in macroeconomics. In Colander, D. (ed.), Post Walrasian Macroeconomics: Beyond the Dynamic Stochastic General Equilibrium Model. Cambridge University Press, New York, pp. 135–160.Google Scholar
Branch, W.A. (2007), Sticky information and model uncertainty in survey data on inflation expectations. Journal of Economic Dynamics and Control 31, 245–276.CrossRefGoogle Scholar
Branch, W.A. and Evans, G.W. (2006), Intrinsic heterogeneity in expectation formation. Journal of Economic Theory 127, 264–295.CrossRefGoogle Scholar
Branch, W.A. and McGough, B. (2005), Consistent expectations and misspecification in stochastic non-linear economies. Journal of Economic Dynamics and Control 29, 659–676.CrossRefGoogle Scholar
Bray, M.M. and Savin, N.E. (1986), Rational expectations equilibria, learning, and model specification. Econometrica 54, 1129–1160.CrossRefGoogle Scholar
Brock, W.A. (1993) Pathways to randomness in the economy: emergent nonlinearity and chaos in economics and finance. Estudios Económicos 8, 3–55.Google Scholar
Brock, W.A. (1997), Asset price behavior in complex environments. In Arthur, W.B., Durlauf, S.N., and Lane, D.A. (eds.), The Economy as an Evolving Complex System II. Addison-Wesley, Reading, MA, 385–423.Google Scholar
Brock, W.A. and Hommes, C.H. (1995), Rational routes to randomness. SSRI Working Paper 9506. Department of Economics, University of Wisconsin.Google Scholar
Brock, W.A. and Hommes, C.H. (1997a), A rational route to randomness. Econometrica 65, 1059–1095.CrossRefGoogle Scholar
Brock, W.A. and Hommes, C.H. (1997b), Models of complexity in economics and finance. In Hey, C. et al. (eds.), System Dynamics in Economic and Financial Models, Chapter 1, Wiley, New York, pp. 3–41.Google Scholar
Brock, W.A. and Hommes, C.H. (1998), Heterogeneous beliefs and routes to chaos in a simple asset pricing model. Journal of Economic Dynamics and Control 22, 1235–1274.CrossRefGoogle Scholar
Brock, W.A. and Hommes, C.H. (1999), Rational animal spirits. In Herings, P.J.J., Laan, van der G. and Talman, A.J.J. (eds.), The Theory of Markets. North-Holland, Amsterdam, pp. 109–137.Google Scholar
Brock, W.A. and LeBaron, B. (1996), Astructural model for stock return volatility and trading volume. Review of Economics and Statistics 78, 94–110.CrossRefGoogle Scholar
Brock, W.A. and Sayers, C.L. (1988), Is the business cycle characterized by deterministic chaos?Journal of Monetary Economics 22, 71–90.CrossRefGoogle Scholar
Brock, W.A., Hsieh, D. and LeBaron, B. (1991), Nonlinear Dynamics, Chaos and Instability: Statistical Theory and Economic Evidence. MIT Press, Cambridge, London.Google Scholar
Brock, W.A., Lakonishok, J. and LeBaron, B. (1992), Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance 47, 1731–1764.CrossRefGoogle Scholar
Brock, W.A., Dechert, W.D., Scheinkman, J.A. and LeBaron, B. (1996), Atest for independence based on the correlation dimension. Econometric Reviews 15, 197–235.CrossRefGoogle Scholar
Brock, W.A., Hommes, C.H. and Wagener, F.O.O. (2005), Evolutionary dynamics in markets with many trader types. Journal of Mathematical Economics, 41, 7–42.CrossRefGoogle Scholar
Brock, W.A., Hommes, C.H. and Wagener, F.O.O. (2009), More hedging instruments may destabilize markets. Journal of Economic Dynamics and Control 33, 1912–1928.CrossRefGoogle Scholar
Bullard, J. (1994), Learning equilibria. Journal of Economic Theory 64, 468–485.CrossRefGoogle Scholar
Bullard, J., Evans, G.W. and Honkapohja, S. (2008), Monetary policy, judgment and near-rational exuberance. American Economic Review 98, 1163–1177.CrossRefGoogle Scholar
Bullard, J., Evans, G.W. and Honkapohja, S. (2010), A model of near-rational exuberance. Macroeconomic Dynamics 14, 166–188.CrossRefGoogle Scholar
Camerer, C.F. (2003), Behavioral Game Theory. Princeton University Press, Princeton, NJ.Google Scholar
Campbell, J.Y. and Shiller, R.J. (2005), Valuation ratios and the long-run stock market outlook: an update. In Thaler, R.H. (ed.), Advances in Behavioral Finance, volume 2. Princeton University Press, Princeton, NJ, pp. 173–201.Google Scholar
Campbell, J.Y., Lo, A.W. and MacKinlay, A.C. (1997), The Econometrics of Financial Markets. Princeton University Press, Princeton, NJ.Google Scholar
Capistrán, C. and Timmermann, A. (2009), Disagreement and biases in inflation expectations. Journal of Money, Credit and Banking 41, 365–396.CrossRefGoogle Scholar
Carlson, J. (1967), The stability of an experimental market with a supply response lag. Southern Economic Journal 33, 305–321.CrossRefGoogle Scholar
Chavas, J.P. (1996) On the economic rationality of market participants: the case of expectations in the U.S. pork market. Department of Economics, University of Wisconsin.Google Scholar
Chavas, J.P. (2000) On information and market dynamics: the case of the U.S. beef market. Journal of Economic Dynamics and Control 24, 833–853.CrossRef
Chevalier, J. and Ellison, G. (1997), Risk taking by mutual funds as a response to incentives. Journal of Political Economy 105, 1167–1200.CrossRefGoogle Scholar
Cheysson, Ê. (1887), La statistique géometriqueméthode pour la solution des problèmes commerciaux et industrièles. Legenie Civil, Paris.Google Scholar
Chiarella, C. (1988) The cobweb model. Its instability and the onset of chaos. Economic Modelling 5, 377–384.CrossRefGoogle Scholar
Chiarella, C. (1992), The dynamics of speculative behaviour. Annals of Operations Research 37, 101–123.CrossRefGoogle Scholar
Chiarella, C. and He, X. (2001), Asset price and wealth dynamics under heterogeneous expectations, Quantitative Finance 1, 509–526.CrossRefGoogle Scholar
Chiarella, C. and He, X. (2002), Heterogeneous beliefs, risk and learning in a simple asset pricing model. Computational Economics 19, 95–132.CrossRefGoogle Scholar
Chiarella, C. and He, X. (2003), Heterogeneous beliefs, risk and learning in a simple asset pricing model with a market maker. Macroeconomic Dynamics 7, 503–536.CrossRefGoogle Scholar
Chiarella, C., Dieci, R. and Gardini, L. (2002), Speculative behaviour and complex asset price dynamics: a global analysis. Journal of Economic Behavior and Organization 49, 173–197.CrossRefGoogle Scholar
Chiarella, C., Dieci, R. and Gardini, L. (2006), Asset price and wealth dynamics in a financial market with heterogeneous agents. Journal of Economic Dynamics and Control, 30, 1755–1786.CrossRefGoogle Scholar
Chiarella, C., Dieci, R. and He, X. (2009), Heterogeneity, market mechanisms, and asset price dynamics. In Hens, T. and Schenk-Hoppé, K. R. (eds.), Handbook of Financial Markets: Dynamics and Evolution. Elsevier, Amsterdam, pp. 277–344.Google Scholar
Clarida, R.G., Gali, J. and Gertler, M. (1999), The science of monetary policy: a New Keynesian perspective. Journal of Economic Literature 37, 1661–1707.CrossRefGoogle Scholar
Clark, C.W. (1985), Bioeconomic Modelling and Fisheries Management. Wiley-Interscience, New York.Google Scholar
Clark, C.W. (1990), Mathematical Bioeconomics: The Optimal Management of Renewable Resources, 2nd ed. Wiley-Interscience, New York.Google Scholar
Colander, D., Goldberg, M., Haas, A., Juselius, K., Kirman, A.Lux, T. and Sloth, B. (2009), The financial crisis and the systemic failure of economics profession, Critical Review: A Journal of Politics and Society 21, 249–267.CrossRefGoogle Scholar
Collet, P. and Eckman, J.-P. (1980), Iterated Maps on the Interval as Dynamical Systems. Birkhäuser, Basel.Google Scholar
Conlisk, J. (1980), Costly optimizers versus cheap imitators. Journal of Economic Behavior and Organization 1, 275–293.CrossRefGoogle Scholar
Conlisk, J. (1996), Why bounded rationality?Journal of Economic Literature 34, 669–700.Google Scholar
Cont, R. (2001), Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance 1, 223–236.CrossRefGoogle Scholar
Cont, R. and Bouchaud, J.-P. (2000), Herd behavior and aggregate fluctuations in financial markets. Macroeconomic Dynamics 4, 170–196.CrossRefGoogle Scholar
Cornea, A., Hommes, C.H. and Massaro, D. (2012), Behavioral heterogeneity in U.S. inflation dynamics. CeNDEF Working Paper. University of Amsterdam.Google Scholar
Cutler, D.M., Poterba, J.M. and Summers, L.H. (1989), What moves stock prices?Journal of Portfolio Management 15, 4–12.CrossRefGoogle Scholar
Dacorogna, M.M., Müller, U.A., Jost, C., Pictet, O.V., Olsen, R.B. and Ward, J.R. (1995), Heterogeneous real-time trading strategies in the foreign exchange market. European Journal of Finance 1, 383–403.CrossRefGoogle Scholar
Day, R.H. (1994), Complex Economic Dynamics Vol. I. An Introduction to Dynamical Systems and Market Mechanisms. MIT Press, Cambridge, MA.Google Scholar
Day, R.H. and Hanson, K.A. (1991), Cobweb chaos. In Kaul, T.K. and Sengupta, J.K. (eds.), Economic Models, Estimation and Social Systems, Essays in Honor of Karl A. Fox. North-Holland, Amsterdam.Google Scholar
Day, R.H. and Huang, W. (1990), Bulls, bears and market sheep. Journal of Economic Behavior and Organization 14, 299–329.CrossRefGoogle Scholar
DeGrauwe, P. (2010a), Top-down versus bottom-up macroeconomics. CESifo Economic Studies 56(4), 465–497.CrossRefGoogle Scholar
DeGrauwe, P. (2010b), Behavioral macroeconomics. Manuscript, University of Leuven, September 2010.Google Scholar
DeGrauwe, P. (2010c), Animal spirits and monetary policy, Economic Theory 47, 423–457.CrossRefGoogle Scholar
DeGrauwe, P. and Grimaldi, M. (2006), The Exchange Rate in a Behavioral Finance Framework. Princeton University Press, Princeton, NJ.Google Scholar
DeGrauwe, P. and Markiewicz, A. (2012), Learning to forecast the exchange rate: two competing approaches. Journal of International Money and Finance 2012, in press.Google Scholar
DeGrauwe, P., Dewachter, H. and Embrechts, M. (1993) Exchange Rate Theory. Chaotic Models of Foreign Exchange Markets. Blackwell, Oxford.Google Scholar
Del Guerico, D. and Tkac, P.A. (2002), The determinants of the flow of funds of managed portfolios: mutual funds versus pension funds. Journal of Financial and Quantitative Analysis 37, 523–557.Google Scholar
Delli Gatti, D., Gallegati, M. and Kirman, A. (eds.) (2000), Interaction and market structure. Essays on heterogeneity in economics. Lecture Notes in Economics and Mathematical Systems 484. Springer Verlag, Berlin.
Delli-Gatti, D., Gaffeo, E., Gallegati, M., Giulioni, G. and Pallestrini, A. (2008), Emergent Macroeconomics. An Agent-based Approach to Business Fluctuations. Springer Verlag, Milan.Google Scholar
DeLong, J.B., Shleifer, A., Summers, L.H. and Waldmann, R.J. (1990a), Noise trader risk in financial markets. Journal of Political Economy 98, 703–738.CrossRefGoogle Scholar
DeLong, J.B., Shleifer, A., Summers, L.H. and Waldmann, R.J. (1990b), Positive feedback investment strategies and destabilizing rational speculation. Journal of Finance 45, 379–395.CrossRefGoogle Scholar
Devaney, R.L. (2003), An Introduction to Chaotic Dynamical Systems, 2nd edn. Westview Press.Google Scholar
Dieci, R. and Westerhoff, F. (2010), Heterogeneous speculators, endogenous fluctuations and interacting markets: a model of stock prices and exchange rates. Journal of Economic Dynamics and Control 34, 743–764.CrossRefGoogle Scholar
Diks, C.G.H. and Weide, R. van der (2005), Herding, a-synchronous updating and heterogeneity in memory in a CBS. Journal of Economic Dynamics and Control 29, 741–763.CrossRefGoogle Scholar
Diks, C.G.H., Hommes, C.H., Panchenko, V. and Weide, R. van der (2008), E&F Chaos:a user friendly software package for nonlinear economic dynamics. Computational Economics, 32, 221–244.CrossRefGoogle Scholar
Droste, E., Hommes, C.H. and Tuinstra, J. (2002), Endogenous fluctuations under evolutionary pressure in Cournot competition. Games and Economic Behavior 40, 232–269.CrossRefGoogle Scholar
Dudek, M.K. (2010), A consistent route to randomness. Journal of Economic Theory 145, 354–381.CrossRefGoogle Scholar
Duffy, J. (2006), Agent-based models and human-subject experiments. In Tesfatsion, L. and Judd, K.L. (eds.), Handbook of Computational Economics, volume 2. North Holland, Amsterdam, 949–1011.Google Scholar
Duffy, J. (2008a), Experimental macroeconomics. In Durlauf, S. and Blume, L. (eds.), The New Palgrave Dictionary of Economics, 2nd ed. Palgrave Macmillan, New York.Google Scholar
Duffy, J. (2008b), Macroeconomics: a survey of laboratory research. In Kagel, J. and Roth, A.E. (eds.), Handbook of Experimental Economics, volume 2, Working Paper 334. University of Pittsburgh.Google Scholar
Ellen, ter, S. and Zwinkels, R.C.J. (2010), Oil price dynamics: a behavioral, finance approach with heterogeneous agents. Energy Economics 32(6), 1427–1434.CrossRefGoogle Scholar
Erev, I. and Roth, A.E. (1998), Prediction how people play games: reinforcement learning in games with unique strategy equilibrium. American Economic Review 88, 848–881.Google Scholar
Evans, G.W. and Honkapohja, S. (2001), Learning and Expectations in Macroeconomics. Princeton University Press, Princeton, NJ.CrossRefGoogle Scholar
Evans, G.W. and Ramey, G. (1992), Expectation calculation and macroeconomic dynamics. American Economic Review 82, 207–224.Google Scholar
Ezekiel, M. (1938) The cobweb theorem. Quarterly Journal of Economics 52, 255–280.CrossRef
Falconer, K. (1990), Fractal Geometry. Mathematical Foundations and Applications. Wiley, Chichester.Google Scholar
Fama, E.F. (1965), The behavior of stock market prices. Journal of Business 38, 34–105.CrossRefGoogle Scholar
Fama, E.F. (1970), Efficient capital markets: a review of theory and empirical work. Journal of Finance 25, 383–423.CrossRefGoogle Scholar
Fama, E.F. and French, K.R. (2002), The equity premium. Journal of Finance 57, 637–659.CrossRefGoogle Scholar
Farmer, J.D. (2002), Market force, ecology, and evolution. Industrial and Corporate Change 11, 895–953.CrossRefGoogle Scholar
Farmer, J.D. and Foley, D. (2009), The economy needs agent-based modelling. Nature 460, 685–686.CrossRefGoogle ScholarPubMed
Farmer, J.D. and Geanakoplos, J. (2009), The virtures and vices of equilibrium and the future of financial economics. Complexity 14, 11–38.CrossRefGoogle Scholar
Farmer, J.D. and Joshi, S. (2002), The price dynamics of common trading strategies. Journal of Economic Behavior and Organization 49, 149–171.CrossRefGoogle Scholar
Fehr, E. and Tyran, J.-R. (2001), Does money illusion matter?American Economic Review 91, 1239–1262.CrossRefGoogle Scholar
Fehr, E. and Tyran, J.-R. (2005), Individual irrationality and aggregate outcomes. Journal of Economic Perspectives 19, 43–66.CrossRefGoogle Scholar
Fehr, E. and Tyran, J.-R. (2008), Limited rationality and strategic interaction: the impact ofthe strategic environment on nominal inertia. Econometrica 76, 353–394.CrossRefGoogle Scholar
Finkenstädt, B. and Kuhbier, P. (1992), Chaotic dynamics inagricultural markets. Annals of Operations Research 37, 73–96.CrossRefGoogle Scholar
Fisher, K.L. and Statman, M. (2002), Blowing bubbles. Journal of Psychology and Financial Markets 3, 53–65.CrossRefGoogle Scholar
Franke, R. and Westerhoff, F. (2011), Estimation of a structural stochastic volatility model of asset pricing. Computational Economics, 38, 53–83.CrossRefGoogle Scholar
Frankel, J.A. and Froot, K.A. (1986), Understanding the US dollar in the eighties: The expectations of chartists and fundamentalists. Economic Record, special issue, pp. 24–38. (Also published as NBER working paper No. 0957, December 1987.)
Frankel, J.A. and Froot, K.A. (1987), Using survey data to test standard propositions regarding exchange rate expectations. American Economic Review 77, 133–153.Google Scholar
Frankel, J.A. and Froot, K.A. (1990a) Chartists, fundamentalists and the demand for dollars. In Courakis, A.S. and Taylor, M.P. (eds.), Private Behaviour and Government Policy in Interdependent Economies. Oxford University Press, New York, pp. 73–126. (Also published as NBER Working Paper No. r1655, October 1991.)Google Scholar
Frankel, J.A. and Froot, K.A. (1990b), The rationality of the foreign exchange rate. Chartists, fundamentalists and trading in the foreign exchange market. American Economic Review 80(2), AEA Papers and Proceedings, 181–185.Google Scholar
Friedman, M. (1953), The case of flexible exchange rates. In Friedman, M. (ed.) Essays in Positive Economics. University of Chicago Press, Chicago, IL.Google Scholar
Frijns, B., Lehnert, B and Zwinkels, R. (2010), Behavioral heterogeneity in option prices. Journal of Economic Dynamics and Control 34, 2273–2287.CrossRefGoogle Scholar
Froot, K.A. and Frankel, J.A. (1989), Forward discount bias: is itanexchange rate premium?Quarterly Journal of Economics 104, 139–161.CrossRefGoogle Scholar
Gallegati, M. and Kirman, A. (eds.) (1999), Beyond the Representative Agent. Edward Elgar, Northampton.
Gaunersdorfer, A. (2000), Endogenous fluctuations in a simple asset pricing model with heterogeneous beliefs. Journal of Economic Dynamics and Control 24, 799–831.CrossRefGoogle Scholar
Gaunersdorfer, A. (2001), Adaptive belief systems and the volatility of asset prices. Central European Journal of Operations Research 9, 5–30.Google Scholar
Gaunersdorfer, A. and Hommes, C.H. (2007), A nonlinear structural model for volatility clustering. In Teyssière, G. and Kirman, A.P. (eds.), Long Memory in Economics. Springer Verlag, Berlin, pp. 265–288.Google Scholar
Gaunersdorfer, A., Hommes, C.H. and Wagener, F.O.O. (2005), Nonlocal onset of instability in an asset pricing model with heterogeneous agents. In Dumortier, F., Broer, H., Mawhin, J., Vanderbauwhede, A. and Lunel, S.V. (eds.), EQUADIFF 2003: Proceedings of the International Conference on Differential Equations. Hasselt, Belgium, July 22–26, 2003. World Scientific, Hackensack, NJ, pp. 613–618.Google Scholar
Gaunersdorfer, A., Hommes, C.H. and Wagener, F.O.J. (2008), Bifurcation routes to volatility clustering under evolutionary learning. Journal of Economic Behavior and Organization 67, 27–47.CrossRefGoogle Scholar
Gigerenzer, G. and Selten, R. (eds.) (2001), Bounded Rationality. The Adaptive Toolbox. MIT Press, Cambridge, MA.
Gigerenzer, G., Todd, P.M. and the ABC Research Group (1999), Simple Heuristics That Make Us Smart. Oxford University Press, Oxford.Google Scholar
Gilli, M. and Winker, P. (2003), A global optimization heuristic for estimating agent based models. Computational Statistics and Data Analysis 42, 299–312.CrossRefGoogle Scholar
Gleick, J. (1987), Chaos. Making a New Science. Viking, Harrisonburg, VA.Google Scholar
Goeree, J.K. and Hommes, C.H. (2000), Heterogeneous beliefs and the non-linear cobweb model. Journal of Economic Dynamics and Control 24, 761–798.CrossRefGoogle Scholar
Goldbaum, D. (2005), Market efficiency and learning in an endogenously unstable environment. Journal of Economic Dynamics and Control 29, 953–978.CrossRefGoogle Scholar
Goodwin, R.M. (1947), Dynamical couplic with especial reference to markets having production lags. Econometrica 15, 181–204.CrossRefGoogle Scholar
Gordon, M. (1962), The Investment Financing and Valuation of the Corporation. Irwin, Homewood, IL.Google Scholar
Grandmont, J.-M. (1985), On endogenous competitive business cycles. Econometrica 53, 995–1045.CrossRefGoogle Scholar
Grandmont, J.-M. (1998), Expectation formation and stability in large socio-economic systems. Econometrica 66, 741–781.CrossRefGoogle Scholar
Grassberger, P. and Procaccia, I. (1983), Characterization ofstrange attractors. Physical Review Letters 50, 346–349.CrossRefGoogle Scholar
Guckenheimer, J. and Holmes, P. (1983), Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields. Springer Verlag, New York.CrossRefGoogle Scholar
Haltiwanger, J. and Waldman, M. (1985), Rational expectations and the limits of rationality: an analysis of heterogeneity. American Economic Review, 75(3), 326–340.Google Scholar
Heemeijer, P., Hommes, C.H., Sonnemans, J. and Tuinstra, J. (2009), Price stability and volatility in markets with positive and negative expectations feedback, Journal of Economic Dynamics and Control, 33, 1052–1072.CrossRefGoogle Scholar
Hénon, M. (1976), A two-dimensional mapping with a strange attractor. Communications in Mathematical Physics 50, 69–77.CrossRefGoogle Scholar
Hens, T. and Schenk-Hoppé, K.R. (eds.) (2009), Handbook of Financial Markets: Dynamics and Evolution. Elsevier, Amsterdam.
Hicks, J.R. (1950), A contribution to the theory of the trade cycle. Clarendon Press, Oxford.Google Scholar
Holmes, J.M. and Manning, R. (1988), Memory and market stability. The case of the cobweb. Economics Letters 28, 1–7.CrossRefGoogle Scholar
Holt, C.A. and Villamil, A.P. (1986), A laboratory experiment with a single person cobweb. Atlantic Economic Journal 14, 51–54.CrossRefGoogle Scholar
Hommes, C.H. (1991a), Adaptive learning and roads to chaos. The case of the cobweb. Economics Letters 36, 127–132.CrossRefGoogle Scholar
Hommes, C.H. (1991b), Chaotic dynamicsin economic models. Some simple case studies. Groningen Theses in Economics, Management & Organization. Wolters-Noordhoff, Groningen.Google Scholar
Hommes, C.H. (1994), Dynamics of the cobweb model with adaptive expectations and nonlinear supply and demand. Journal of Economic Behaviour and Organization 24, 315–335.CrossRefGoogle Scholar
Hommes, C.H. (1995), A reconsideration of Hicks’ nonlinear trade cylce model. Structural Change and Economic Dynamics 6, 435–459.CrossRefGoogle Scholar
Hommes, C.H. (1998), On the consistency of backward-looking expectations. The caseof the cobweb. Journal of Economic Behaviour and Organization 33, 333–362.CrossRefGoogle Scholar
Hommes, C.H. (2000), Cobweb dynamics under bounded rationality. In Dockner, E.J. et al. (eds.), Optimization, Dynamics and Economic Analysis – Essays in Honor of Gustav Feichtinger. Springer Verlag Berlin, pp. 134–150.Google Scholar
Hommes, C.H. (2001), Financial markets as nonlinear adaptive evolutionary systems. Quantitative Finance 1, 149–167.CrossRefGoogle Scholar
Hommes, C.H. (2002), Modeling the stylized facts in finance through simple nonlinear adaptive systems. Proceedings of the National Academy of Sciences 99, 7221–7228.CrossRefGoogle ScholarPubMed
Hommes, C.H. (2005), Heterogeneous agents models: two simple examples. In Lines, M. (ed.), Nonlinear Dynamical Systems in Economics. CISM Courses and Lectures No. 476. Springer, Berlin, pp. 131–164.Google Scholar
Hommes, C.H. (2006), Heterogeneous agent models in economics and finance. In Tesfatsion, L. and Judd, K.L. (eds), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics, chapter 23. North-Holland, Amsterdam, pp. 1109–1186.Google Scholar
Hommes, C.H. (2009), Bounded rationality and learning in complex markets. In Rosser, J.B. (ed.), Handbook of Research on Complexity, Edward Elgar, Cheltenham, pp. 87–123.Google Scholar
Hommes, C.H. (2011), The heterogeneous expectations hypothesis: Some evidence from the lab, Journal of Economic Dynamics and Control 35, 1–24.CrossRefGoogle Scholar
Hommes, C.H. and Lux, T. (2013), Individual expectations and aggregate behavior in learning to forecast experiments, Macroeconomic Dynamics, in press.
Hommes, C.H. and Manzan, S. (2006), Comments on “Testing for nonlinear structure and chaos in economic time series”. Journal of Macroeconomics 28, 169–174.CrossRefGoogle Scholar
Hommes, C.H., and Rosser, J. Barkley Jr., (2001) Consistent expectations equilibria and complex dynamics in renewable resource markets, Macroeconomic Dynamics 5, 180–203.CrossRefGoogle Scholar
Hommes, C.H. and Sorger, G. (1998), Consistent expectations equilibria. Macroeconomic Dynamics 2, 287–321.Google Scholar
Hommes, C.H. and Wagener, F.O.O. (2009), Complex evolutionary systems in behavioral finance. In Hens, T. and Schenk-Hoppé, K.R. (eds.), Handbook of Financial Markets: Dynamics and Evolution. Elsevier, Amsterdam, pp. 217–276.Google Scholar
Hommes, C.H. and Zhu, M. (2012), Behavioral learning equilibria. CeNDEF Working Paper. University of Amsterdam.Google Scholar
Hommes, C.H., Sonnemans, J. and van de Velden, H. (2000), Expectation formation in an experimental cobweb economy, In: Delli Gatti, D., Gallegati, M. and Kirman, A. (eds.). Interaction and Market Structure: Essays on Heterogeneity in Economics, Lecture Notes in Economics and Mathematical Systems, volume 484, Berlin: Springer-Verlag, pp. 253–266.Google Scholar
Hommes, C.H., Sorger, G., Wagener, F., (2013), Consistency of linear forecasts in a nonlinear stochastic economy, In: Bischi, G.I., Chiarella, C. and Sushko, I. (Eds.), Global Analysis of Dynamic Models in Economics and Finance, Springer-Verlag, Berlin, pp. 229–287.Google Scholar
Hommes, C.H., Huang, H. and Wang, D. (2005a), A robust rational route to randomness in a simple asset pricing model. Journal of Economic Dynamics and Control 29, 1043–1072.CrossRefGoogle Scholar
Hommes, C.H., Sonnemans, J., Tuinstra, J., and van de Velden, H., (2005b) Coordination of expectations in asset pricing experiments, Review of Financial Studies 18, 955–980.CrossRefGoogle Scholar
Hommes, C., Sonnemans, J., Tuinstra, J. and Velden, H. van de, (2007), Learning in cobweb experiments, Macroeconomic Dynamics 11 (S1), 8–33.CrossRefGoogle Scholar
Hommes, C.H., Sonnemans, J., Tuinstra, J. and Velden, H. van de, (2008), Expectations and bubbles in asset pricing experiments, Journal of Economic Behavior & Organization 67, 116–133.CrossRefGoogle Scholar
Hommes, C.H., Kiseleva, T., Kuznetsov, Y. and Verbic, M. (2012), Is more memory in evolutionary selection (de)stabilizing?, Macroeconomic Dynamics, 16, 335–357.CrossRefGoogle Scholar
Hong, H. and Stein, J. (1999), Aunified theory of underreaction, momentum trading and overreaction in asset markets. Journal of Finance 55, 265–295.CrossRefGoogle Scholar
Ingrao, B. and Israel, G., (1990), The Invisible Hand. Economic Equilibrium in the History of Science, Cambridge, MA,: MIT Press.Google Scholar
Iori, G. (2002), A microsimulation of traders activity in the stock market: the role of heterogeneity, agents’ interactions and trade frictions. Journal of Economic Behavior and Organization 49, 269–285.CrossRefGoogle Scholar
Ippolito, R.A. (1989), Efficiency with costly information: a study of mutual fund performance, 1965–1984. Quarterly Journal of Economics 104, 1–23.CrossRefGoogle Scholar
Ito, K. (1990), Foreign exchange rate expectations. American Economic Review 80, 434–449.Google Scholar
Jacobson, M.V. (1981), Absolutely continuous invariant measures for one-parameter families of one-dimensional maps. Communications in Mathematical Physics 81, 39–88.CrossRefGoogle Scholar
Jensen, R.V. and Urban, R. (1984), Chaotic price behaviour in a nonlinear cobweb model. Economics Letters 15, 235–240.CrossRefGoogle Scholar
de Jong, E., Verschoor, W.F.C. and Zwinkels, R.C.J. (2009), Behavioural heterogeneity and shift-contagion: evidence from the Asian crisis. Journal of Economic Dynamics and Control 33, 1929–1944.CrossRefGoogle Scholar
de Jong, E., Verschoor, W.F.C. and Zwinkels, R.C.J. (2010), Heterogeneity of agents and exchange rate dynamics: evidence from the EMS. Journal of International Money and Finance 29, 1652–1669.CrossRefGoogle Scholar
Jongen, R., Wolf, C.C.P., Zwinkels, R.C.J. and Verschoor, W.F.C. (2012), Explaining dispersion in the foreign exchange market: a heterogeneous agent approach, Journal of Economic Dynamics and Control, 36, 719–735.CrossRefGoogle Scholar
Kahneman, D. (2003), Maps of bounded rationality: Psychology for behavioral economics. American Economic Review 93, 1449–1475.CrossRefGoogle Scholar
Kahneman, D. and Tversky, A. (1973), On the psychology of prediction. Psychological Review 80, 237–251.CrossRefGoogle Scholar
Kaldor, N. (1934), A classificatory note on the determinateness of equilibrium. Review of Economic Studies 1, 122–136.CrossRefGoogle Scholar
Kantz, H. and Schreiber, T. (1997), Nonlinear Time Series Analysis. Cambridge University Press, Cambridge.Google Scholar
Karceski, J. (2002), Returns-chasing behavior, mutual funds, and beta's death. Journal of Financial and Quantitative Analysis 37, 559–594.CrossRefGoogle Scholar
Keynes, J.M. (1936), The General Theory of Unemployment, Interest and Money. Harcourt, Brace and World, New York.Google Scholar
Kindleberger, C.P. (1996), Manias, Panics, and Crashes. A History of Financial Crises 3rd edn. Wiley, New York.Google Scholar
Kirman, A. (1991), Epidemics of opinion and speculative bubbles in financial markets. In Taylor, M. (ed.), Money and Financial Markets, Macmillan, New York.Google Scholar
Kirman, A. (1992), Whom or what does the representative individual represent?Journal of Economic Perspectives 6, 117–136.CrossRefGoogle Scholar
Kirman, A. (1993), Ants, rationality and recruitment. Quarterly Journal of Economics 108, 137–156.CrossRefGoogle Scholar
Kirman, A. (1999), Aggregate activity and economic organisation. Revue Européene des Sciences Sociales XXXVII(113), 189–230.Google Scholar
Kirman, A. (2010), Complex Economics: Individual and Collective Rationality. Routledge, Oxford.Google Scholar
Kirman, A. and Teyssière, G. (2002), Microeconomic models for long memory in the volatility of financial time series. Studies in Nonlinear Dynamics and Econometrics 5(4), 281–302.CrossRefGoogle Scholar
Kurz, M. (ed.) (1997), Endogenous Economic Fluctuations. Springer Verlag, New York.
Kuznetsov, Y. (1995), Elements of Applied Bifurcation Theory. Springer Verlag, New York.CrossRefGoogle Scholar
Kydland, F.E. and Prescott, E.C. (1982), Time to build and aggregate fluctuations. Econometrica 50, 1345–70.CrossRefGoogle Scholar
Lansing, K.J. (2009), Time-varing U.S. inflation dynamics and the new Keynesian Phillips curve. Review of Economic Dynamics 12, 304–326.CrossRefGoogle Scholar
Lansing, K.J. (2010), Rational and near-rational bubbles without drift. Economic Journal 120, 1149–1174.CrossRefGoogle Scholar
Lasselle, L., Svizzero, S. and Tisdell, C. (2005), Stability and cycles in a cobweb model with heterogeneous expectations. Macroeconomic Dynamics 9, 630–650.CrossRefGoogle Scholar
LeBaron, B. (2000), Agent based computational finance: suggested readings and early research. Journal of Economic Dynamics and Control 24, 679–702.CrossRefGoogle Scholar
LeBaron, B. (2002), Short-memory traders and their impact on group learning in financial markets. Proceedings of the National Academy of Sciences (USA) 99(Suppl. 3), 7201–7206.CrossRefGoogle ScholarPubMed
LeBaron, B. (2006), Agent-based computational finance. In Tesfatsion, L., Judd, K.L. (eds.), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics, chapter 24. North-Holland, Amsterdam, pp. 1187–1233.Google Scholar
LeBaron, B., Arthur, W.B. and Palmer, R. (1999), Time series properties of an artificial stock market. Journal of Economic Dynamics and Control 23, 1487–1516.CrossRefGoogle Scholar
Leontief, W.W. (1934), Verzögerte Angebotsanpassung und partielles Gleichgewicht. Zeitschrift für Nationalökonomie, V(5), 670–676.CrossRefGoogle Scholar
Levy, M., Levy, H. and Solomon, S. (1994), A microscopic model of the stock market. Economics Letters 45, 103–111.CrossRefGoogle Scholar
Li, T.Y. and Yorke, J.A. (1975), Period three implies chaos. American Mathematical Monthly 82, 985–992.CrossRefGoogle Scholar
Lichtenberg, A.J. and Ujihara, A. (1989), Application of nonlinear mapping theory to commodity price fluctuations. Journal of Economic Dynamics and Control 13, 225–246.CrossRefGoogle Scholar
Lines, M. and Westerhoff, F. (2010), Inflation expetations and macroeconomic dynamics: the case of rational versus extrapolative expectations. Journal of Economic Dynamics and Control 34, 246–257.CrossRefGoogle Scholar
Lorentz, E.N. (1963), Deterministic nonperiodic flow. Journal of the Atmospheric Sciences 20, 130–141.2.0.CO;2>CrossRefGoogle Scholar
Lorenz, H.W. (1993), Nonlinear Dynamical Economics and Chaotic Motion, 2nd, revised and enlarged ed. Springer-Verlag, Berlin.CrossRefGoogle Scholar
Lucas, R.E. (1972a), Econometric testing of the natural rate hypothesis. In Eckstein, O. (ed.), The Econometrics of Price Determination. Conference, Board of Governors of the Federal Reserve System and Social Science Research Council, Washington DC, pp. 50–59.Google Scholar
Lucas, R.E. (1972b), Expectations and the neutrality of money. Journal of Economic Theory 4, 103–124.CrossRefGoogle Scholar
Lucas, R.E. (1986), Adaptive behavior and economic theory, Journal of Business 59(4), S401–S426.CrossRefGoogle Scholar
Lux, T. (1995), Herd behavior, bubbles and crashes. The Economic Journal 105, 881–896.CrossRefGoogle Scholar
Lux, T. (1997), Time variation of second moments from a noise trader/infection model. Journal of Economic Dynamics and Control 22, 1–38.CrossRefGoogle Scholar
Lux, T. (1998), The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distribution. Journal of Economic Behavior and Organization 33, 143–165.CrossRefGoogle Scholar
Lux, T. (2009), Stochastic behavioral asset pricing models and the stylized facts. In Hens, T. and Schenk-Hoppé, K.R. (eds.), Handbook of Financial Markets: Dynamics and Evolution. Elsevier, Amsterdam.Google Scholar
Lux, T. and Marchesi, M. (1999), Scaling and criticality in a stochastic multi-agent model of a financial market. Nature 397(February) 498–500.CrossRefGoogle Scholar
Lux, T. and Marchesi, M. (2000) Volatility clustering in financial markets: a micro-simulation of interacting agents. International Journal of Theoretical and Applied Finance 3, 675–702.CrossRefGoogle Scholar
Mankiw, N., Reis, R. and Wolfers, J. (2003), Disagreement about inflation expectations, NBER Macroecomics Annual 2003, volume 18, 209–248.Google Scholar
Mandelbrot, B.B. (1982), The Fractal Geometry of Nature. Freeman, San Francisco, CA.Google Scholar
Manski, C. and McFadden, D. (1981), Structural Analysis of Discrete Data with Econometric Applications. MIT Press, Cambridge, MA.Google Scholar
Mantegna, R.N. and Stanley, H.E. (2000), An Introduction to Econophysics. Correlations and Complexity in Finance. Cambridge University Press, Cambridge.Google Scholar
Manzan, S. (2003), Essays in nonlinear economic dynamics. PhD thesis, Tinbergen Institute Research Series 317. Thela Publishers, Amsterdam.Google Scholar
Marimon, R. and Sunder, S. (1994), Expectations and learning under alternative monetary regimes: an experimental approach. Economic Theory 4, 131–162.CrossRefGoogle Scholar
May, R.M. (1976), Simple mathematical models with very complicated dynamics. Nature 261, 459–467.CrossRefGoogle ScholarPubMed
Medio, A. (1992), Chaotic Dynamics. Theory and Applications to Economics. Cambdridge University Press, Cambridge.Google Scholar
Medio, A. and Lines, M. (2001), Non-linear Dynamics. A Primer. Cambridge University Press, Cambridge.CrossRefGoogle Scholar
de Melo, W. and van Strien, S. (1993), One-dimensional Dynamics. Springer Verlag, Berlin.CrossRefGoogle Scholar
Menkhoff, L. and Taylor, M.P. (2007), The obstinate passion of foreign exchange professionals: technical analysis. Journal of Economic Literature 45, 936–972.CrossRefGoogle Scholar
Merton, R.C. (1980), On estimating the expected return on the market. An exploratory investigation. Journal of Financial Economics 8, 323–361.CrossRefGoogle Scholar
Muth, J.F. (1961), Rational expectations and the theory of price movements. Econometrica 29, 315–335.CrossRefGoogle Scholar
Nerlove, M. (1958), Adaptive expectations and cobweb phenomena. Quarterly Journal of Economics 72, 227–240.CrossRefGoogle Scholar
Nicholson, W. (1995), Microeconomic Theory. Basic Principles and Extensions, 6th edn. Dryden Press, Fort Worth, TX.Google Scholar
Palis, J. and Takens, F. (1993), Hyperbolicity and Sensitive Chaotic Dynamics at Homoclinic Bifurcations. Cambridge University Press, Cambridge.Google Scholar
Pashigian, B.P. (1987), Cobweb theorem. In Eatwell, J., Milgate, M. and Newman, P. (eds.), The New Palgrave. A Dictionary of Economics, volume 1, MacMillan, Basingstoke.Google Scholar
Pesaran, H.M. and Weale, M. (2006), Survey expectations. In Elliott, G., Granger, C.W.J. and Timmermann, A. (eds), Handbook of Economic Forecasting. Amsterdam, North-Holland, pp. 715–776.Google Scholar
Pfajfar, D. and Santoro, E. (2010), Heterogeneity, learning and information stickiness in inflation expectations. Journal of Economic Behavior and Organization 75, 426–444.CrossRefGoogle Scholar
Pfajfar, D. and Zakelj, B. (2011), Inflation expectations and monetary policy design: evidence from the laboratory. CentER Discussion Paper. Tilburg University, July 2011.Google Scholar
Plott, C.R. and Sunder, S. (1982), Efficiencyofexperimental security markets with insider information: an application of rational expectations models. Journal of Political Economy 90, 663–698.CrossRefGoogle Scholar
Poincaré, H. (1890), Sur le problème des trois corps et les equations de la dynamique (Mémoire couronné du prise de S.M. le roi Oscar II de Suède). Acta Mathamatica 13, 1–270.Google Scholar
Ricci, U. (1930), Die “synthetisch Ökonomie” von Henry Ludwell Moore, Zeitschrift für Nation-alökonomie I(5), 649–668.CrossRefGoogle Scholar
Rockinger, M. (1996), Determinants of capital flows to mutual funds. Working paper, HEC School of Management, Paris.Google Scholar
Rosser, J.B., Jr. (2000), From Catastrophe to Chaos: A General Theory of Economic Discontinuities, 2nd ed. Kluwer Academic Publishers, Boston.CrossRefGoogle Scholar
Rosser, J.B., Jr. (2004), Complexity in Economics: The International Library of Critical Writings in Economics 174, (3 volumes). Edward Elgar, Aldergate.Google Scholar
Rosser, J.B., Jr. (2009), Handbook of Economic Complexity. Edward Elgar, Cheltenham.CrossRefGoogle Scholar
Ruelle, D. and Takens, F. (1971), On the nature of turbulence. Communications in Mathematical Physics 20, 167–192.CrossRefGoogle Scholar
Sakai, H. and Tokumaru, H. (1980), Autocorrelations of a certain chaos, IEEE Transactions on Acoustics, Speech and Signal Processing 28, 588–590.CrossRefGoogle Scholar
Sargent, T.J. (1993), Bounded Rationality in Macroeconomics. Clarendon Press, Oxford.Google Scholar
Sargent, T.J. (1999), The Conquest of American Inflation. Princeton University Press, Princeton, NJ.Google Scholar
Sargent, T.J. (2008), Evolution and intelligent design. American Economic Review 98, 5–37.CrossRefGoogle Scholar
Scheinkman, J.A. and LeBaron, B. (1989), Nonlinear dynamics and stock returns. Journal of Business 62, 311–337.CrossRefGoogle Scholar
Schönhofer, M. (1999), Chaotic learning equilibria. Journal of Economic Theory 89, 1–20.CrossRefGoogle Scholar
Schultz, H., (1930), Der Sinn der Statistischen Nachfragekurven. In Altschul, E. (ed.), Veröffentlichun-gen der Frankfurter Gesellschaft für Konjunkturforschung 10.
Schunk, D. (2009), Behavioral heterogeneity in dynamic search situations: theory and experimental evidence. Journal of Economic Dynamics and Control 33, 1719–1738.CrossRefGoogle Scholar
Schunk, D. (2011), Heterogeneous agnets in intertemporal choice: theory and experimental evidence. Working paper, University of Zürich, 2011.Google Scholar
Shefrin (2000), Beyond greed and fear. Understanding behavioral finance and the psychology of investing. Harvard Business School Press, Boston, MA.Google Scholar
Shiller, R.J. (1981), Do stock prices move too much to be justified bysubsequent changesin dividends?American Economic Review 71, 421–436.Google Scholar
Shiller, R.J. (1984), Stock prices and social dynamics. Brookings Papers in Economic Activity 2, 457–510.CrossRefGoogle Scholar
Shiller, R.J. (1987), Investor behavior in the October 1987 stock market crash: survey evidence. NBER working paper No. 2446, November 1987 (Published in Shiller, R.J., Market Volatility, MIT Press, Cambridge, MA 1989, chapter 23.)
Shiller, R.J. (1989), Market Volatility. MIT Press, Cambridge, MA.Google Scholar
Shiller, R.J. (2000), Measuring bubble expectations and investor confidence. Journal of Psychology and Financial Markets 1, 49–60.CrossRefGoogle Scholar
Simon, H.A. (1955), A behavioral model of rational choice. Quarterly Journal of Economics 69, 99–118.CrossRefGoogle Scholar
Simon, H.A. (1957), Models of Man. Wiley, New York.Google Scholar
Simon, H.A. (1984), On the behavioral and rational foundations of economic dynamics. Journal of Economic Behavior and Organization 5, 35–55.CrossRefGoogle Scholar
Sims, C.A. (1980), Macroeconomics and reality. Econometrica 48, 1–48.CrossRefGoogle Scholar
Sirri, E.R. and Tufano, P. (1998), Costly search and mutual fund flows. Journal of Finance 53, 1589–1621.CrossRefGoogle Scholar
Smale, S. (1963), Diffeomorhphisms with many periodic points. In Cairns, S.S. (ed.), Differential and combinatorial topology. Princeton University Press, Princeton, NJ, pp. 63–80.Google Scholar
Smith, V.L., (1962), A experimental study of competitive market behavior. Joural of Political Economy 70, 111–137.CrossRefGoogle Scholar
Smith, V.L., Suchanek, G.L. and Williams, A.W. (1988), Bubbles, crashes and endogenous expectations in experimental spot asset markets. Econometrica, 56, 1119–1151.CrossRefGoogle Scholar
Sögner, L. and Mitlöhner, H. (2002), Consistent expectations equilibria and learning in a stock market. Journal of Economic Dynamics and Control 26, 171–185.CrossRefGoogle Scholar
Sonnemans, J., Hommes, C.H., Tuinstra, J. and van de Velden, H. (2004), The instability of a heterogeneous cobweb economy: a strategy experiment in expectation formation. Journal of Economic Behavior and Organization 54, 453–481.CrossRefGoogle Scholar
Sorger, G. (1998), Imperfect foresight and chaos: an example of a self-fulfilling mistake. Journal of Economic Behavior and Organization 33, 363–383.CrossRefGoogle Scholar
Summers, L.H. (1986), Does the stock market rationally reflect fundamental values?, Journal of Finance 41, 591–601.CrossRefGoogle Scholar
Sunder, S. (1995) Experimental asset markets: a survey. In Kagel, J.H. and Roth, A.E. (eds.), Handbook of Experimental Economics. Princeton University Press, Princeton, NJ, pp. 445–500.Google Scholar
Sutan, A. and Willinger, M. (2009), Guessing with negative feedback: an experiment. Journal of Economic Dynamics and Control 33, 1123–1133.CrossRefGoogle Scholar
Takens, F. (1981), Detecting strange attractors in turbulence: In Rand, D.A. and Young, L.S. (eds.), Dynamical Systems and Turbulence. Lecture Notes in Mathematics 898. Springer Verlag, Berlin, pp. 366–381.Google Scholar
Taylor, M.P. and Allen, H. (1992), The use of technical analysis in the foreign exchange market. Journal of International Money and Finance 11, 304–314.CrossRefGoogle Scholar
Tesfatsion, L., (2006), Agent-based computational economics: a constructive approach to economic theory. In Tesfatsion, L. and Judd, K.L. (eds), Handbook of Computational Economics Volume 2: Agent-Based Computational Economics. North-Holland, Amsterdam, pp. 831–880.Google Scholar
Tesfatsion, L. and Judd, K.L. (eds), 2006, Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics. North-Holland, Amsterdam.
Teräsvirta, T. (1994), Specification, estimation, and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89, 208–218.Google Scholar
Thaler, R., (1994) Quasi Rational Economics. Russel Sage Foundation.Google Scholar
Tinbergen, J. (1930), Bestimmung und Deutung von Angebotskurven. Ein Beispiel, Zeitschrift für Nationalökonomie, (5), 669–679.CrossRef
Tong, H., (1990), Non-linear Time Series. A Dynamical System Approach. Clarendon Press, Oxford.Google Scholar
Tuinstra, J. (2003), Beliefs equilibria in an overlapping generations model, Journal of Economic Behavior and Organization 50, 145–164.CrossRefGoogle Scholar
Tuinstra, J., and Wagener, F.O.O. (2007), On learning equilibria. Economic Theory 30, 493–513.CrossRefGoogle Scholar
Tversky, A. and Kahneman, D. (1974), Judgment under uncertainty: heuristics and biases. Science 185, 1124–1131.CrossRefGoogle ScholarPubMed
Vilder, de, R. (1996), Complicated endogenous business cycles under gross substitutability. Journal of Economic Theory 71, 416–442.CrossRefGoogle Scholar
Vissing-Jorgensen, A. (2003), Perspective on behavioral finance: does ‘irrationality’ disappear with wealth? Evidence from expectations and actions. In: Gertler, M. and Rogoff, K. (eds.), NBER Macroeconomics Annual. MIT Press, Cambridge, MA.Google Scholar
Waugh, F.V. (1964), Cobweb models, Journal of Farm Economics 46, 732–750.CrossRefGoogle Scholar
Wellford, C.P. (1989), Alaboratory analysis of price dynamics and expectations in the cobweb model. Discussion Paper No. 89–15. Department of Economics, University of ArizonaGoogle Scholar
Westerhoff, F.H. (2004), Multi-asset market dynamics. Macroeconomic Dynamics 8, 596–616.Google Scholar
Westerhoff, F.H. and Dieci, R. (2006), The effectiveness of Keynes–Tobin transaction taxes when heterogeneous agents can trade in different markets: a behavioral finance approach. Journal of Economic Dynamics and Control 30, 293–322.CrossRefGoogle Scholar
Westerhoff, F.H. and Reitz, S. (2003), Nonlinearities and cyclical behavior: the role of chartists and fundamentalists. Studies in Nonlinear Dynamics and Econometrics 7(4), article 3.Google Scholar
Williams, A.W. (1987) The formation of price forecasts in experimental markets. Journal of Money, Credit and Banking, 19, 1–18.CrossRefGoogle Scholar
Winker, P. and Gilli, M. (2001), Indirect estimation of the parameters of agent based models of financial markets. FAME Research Paper No. 38. University of Geneva, November 2001.Google Scholar
Woodford, M. (2003), Interest and Prices: Foundations of a Theory of Monetary Policy, Princeton University Press, Princeton, NJ.Google Scholar
Youssefmir, M. and Huberman, B.A. (1997), Clustered volatility in multi agent dynamics. Journal of Economic Behavior and Organization 32, 101–118.CrossRefGoogle Scholar
Zeeman, E.C. (1974), The unstable behavior of stock exchange. Journal of Mathematical Economics 1, 39–49.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Bibliography
  • Cars Hommes, Universiteit van Amsterdam
  • Book: Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems
  • Online publication: 05 February 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139094276.010
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Bibliography
  • Cars Hommes, Universiteit van Amsterdam
  • Book: Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems
  • Online publication: 05 February 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139094276.010
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Bibliography
  • Cars Hommes, Universiteit van Amsterdam
  • Book: Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems
  • Online publication: 05 February 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139094276.010
Available formats
×