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Rational Routes to Randomness

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Author Info
William A. Brock
Cars H. Hommes

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Abstract

We introduce the concept of Adaptively Rational Equilibrium (A.R.E.) where agents base decisions upon predictions of future values of endogenous variables whose actual values are determined by equilibration. Predictors are chosen from a finite set. Each predictor is a function of past observations and has a performance measure attached to it which is publically available. Agents use a discrete choice model and make a rational choice concerning the predictor based upon the performance measure. This results in a dynamics across predictor choice which is coupled to the dynamics of the endogenous variables. When there is at least one `stabilizing' predictor (e.g. rational or long memory expectations) driving the endogenous variable toward its steady state value and at least one `destabilizing' predictor (e.g. adaptive or short memory expectations) driving the endogenous variable away from its steady state value, then the adaptive rational equilibrium dynamics can be very complicated and cycles and chaos can arise. The irregularity of the equilibrium time paths is explained by the existence of a homoclinic orbit and its associated complicated dynamical phenomena, when the intensity of choice between predictors is high. Thus local instability and global complicated dynamics may be a feature of a fully rational notion of equilibrium.

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Publisher Info
Paper provided by Santa Fe Institute in its series Working Papers with number 95-03-029.

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Date of creation: Mar 1995
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Handle: RePEc:wop:safiwp:95-03-029

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  2. Thorsten Hens & Klaus Reiner Schenk-Hoppé, . "Markets Do Not Select For a Liquidity Preference as Behavior Towards Risk," IEW - Working Papers iewwp139, Institute for Empirical Research in Economics - IEW. [Downloadable!]
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  3. Laurence Lasselle & Serge Svizzero & Clem Tisdell, 2007. " Stability and Cycles in a Cobweb Model with Heterogeneous Expectations," CDMA Working Paper Series 0706, Centre for Dynamic Macroeconomic Analysis. [Downloadable!]
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  4. Diks, C.G.H. & Dindo, P.D.E., 2006. "Informational differences and learning in an asset market with boundedly rational agents," CeNDEF Working Papers 06-11, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
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  5. Paul De Grauwe & Pablo Rovira Kaltwasser, 2006. "A Behavioral Finance Model of the Exchange Rate with Many Forecasting Rules," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
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  9. U. Horst, . "Ergodic Fluctuations in a Stock Market Model with Interacting Agents - The Mean Field Case," Sonderforschungsbereich 373 1999-106, Humboldt Universitaet Berlin.
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  13. Droste, E. & Tuinstra, J., 1998. "Evolutionary selection of behavioral rules in a Cournot model : a local bifurcation analysis," Discussion Paper 86, Tilburg University, Center for Economic Research. [Downloadable!]
  14. Steven N. Durlauf, 1996. "Statistical Mechanics Approaches to Socioeconomic Behavior," NBER Technical Working Papers 0203, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  15. Demary, Markus, 2006. "Transaction taxes, traders' behavior and exchange rate risks," Economics Working Papers 2006,14, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
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  16. Hommes, C.H., 2007. "Bounded Rationality and Learning in Complex Markets," CeNDEF Working Papers 07-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
  17. SaangJoon Baak, 1999. "Heterogeneous Expectations, Market Dynamics, and Social Welfare," Computing in Economics and Finance 1999 222, Society for Computational Economics. [Downloadable!]
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