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Memory and Asset Pricing Models with Heterogeneous Beliefs

  • Verbic, Miroslav

The paper discusses the role of memory in asset pricing models with heterogeneous beliefs. In particular, we were interested in how memory in the fitness measure affects stability of evolutionary adaptive systems and survival of technical trading. In order to obtain an insight into this matter two cases were analyzed; a two-type case of fundamentalists versus contrarians and a three-type case of fundamentalists versus opposite biases. It has been established that increasing memory strength has a stabilizing effect on dynamics, though it is not able to eliminate speculative traders’ short-run profit seeking behaviour from the market. Furthermore, opposite biases do not seem to lead to chaotic dynamics, even when there are no costs for fundamentalists. Apparently some (strong) trend extrapolator beliefs are needed in order to trigger chaotic asset price fluctuations.

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File URL: https://mpra.ub.uni-muenchen.de/1261/1/MPRA_paper_1261.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 1261.

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Date of creation: 15 Aug 2006
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Handle: RePEc:pra:mprapa:1261
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  1. Seppo Honkapohja & Kaushik Mitra, . "Learning with Bounded Memory in Stochastic Models," Discussion Papers 00/42, Department of Economics, University of York.
  2. De Grauwe, Paul & Grimaldi, Marianna, 2006. "Exchange rate puzzles: A tale of switching attractors," European Economic Review, Elsevier, vol. 50(1), pages 1-33, January.
  3. Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2002. "Evolutionary dynamics in markets with many trader types," CeNDEF Working Papers 02-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  4. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers 10368, Iowa State University, Department of Economics.
  5. Carl Chiarella & Xue-Zhong He & Peiyuan Zhu, 2003. "Fading Memory Learning in the Cobweb Model with Risk Averse Heterogeneous Producers," Research Paper Series 108, Quantitative Finance Research Centre, University of Technology, Sydney.
  6. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186 Elsevier.
  7. Cars Hommes & Carl Chiarella & Xue-Zhong He, 2004. "A Dynamical Analysis of Moving Average Rules," Computing in Economics and Finance 2004 238, Society for Computational Economics.
  8. William A. Brock, 1993. "Pathways to randomness in the economy: Emergent nonlinearity and chaos in economics and finance," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 8(1), pages 3-55.
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  10. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
  11. Xue-Zhong He & Carl Chiarella, 1999. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset-Pricing Model," Computing in Economics and Finance 1999 223, Society for Computational Economics.
  12. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
  13. Brock,W.A. & Hommes,C.H., 2002. "Heterogeneous beliefs and routes to complex dynamics in asset pricing models with price contingent contracts," Working papers 3, Wisconsin Madison - Social Systems.
  14. Hommes, Cars & Sorger, Gerhard, 1998. "Consistent Expectations Equilibria," Macroeconomic Dynamics, Cambridge University Press, vol. 2(03), pages 287-321, September.
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  16. Gaunersdorfer, A. & Hommes, C.H. & Wagener, F.O.O., 2000. "Bifurcation Routes to Volatility Clustering," CeNDEF Working Papers 00-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  17. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233 Elsevier.
  18. repec:cup:macdyn:v:2:y:1998:i:3:p:287-321 is not listed on IDEAS
  19. Lucas, Robert E, Jr, 1978. "Asset Prices in an Exchange Economy," Econometrica, Econometric Society, vol. 46(6), pages 1429-45, November.
  20. Gaunersdorfer, A. & Hommes, C.H. & Wagener, F.O.O., 2003. "Bifurcation Routes to Volatility Clustering under Evolutionary Learning," CeNDEF Working Papers 03-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  21. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
  22. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
  23. Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan & van de Velden, Henk, 2008. "Expectations and bubbles in asset pricing experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 116-133, July.
  24. Gaunersdorfer, Andrea, 2000. "Endogenous fluctuations in a simple asset pricing model with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 799-831, June.
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