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Chaos and Nonlinear Forecastability in Economics and Finance

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  • Blake LeBaron

    (University of Wisconsin)

Abstract

Both academic and applied researchers studying financial markets and other economic series have become interested in the topic of chaotic dynamics. The possibility of chaos in financial markets opens important questions for both economic theorists as well as financial market participants. This paper will clarify the empirical evidence for chaos in financial markets and macroeconomic series. It will also compare these two concepts from a financial market perspective contrasting the objectives of the practitioner with those of economic researchers. Finally, the paper will speculate on the impact of chaos and nonlinear modeling on future economic research.

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Bibliographic Info

Paper provided by EconWPA in its series Finance with number 9411001.

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Date of creation: 14 Nov 1994
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Handle: RePEc:wpa:wuwpfi:9411001

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References

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  1. Blake LeBaron, . "The Joint Dynamics and Stability of Stock Prices and Volume," Working papers _004, University of Wisconsin - Madison.
  2. Ramsey, J.B. & Sayers, C.L. & Rothman, P., 1988. "The Statistical Properties Of Dimension Calculations Using Small Data Sets: Some Economic Applications," Papers 15, Houston - Department of Economics.
  3. William Barnett, 2005. "Monetary Aggregation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 200510, University of Kansas, Department of Economics, revised Mar 2005.
  4. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
  5. Clive W. Granger & Timo Terasvirta & Heather M. Anderson, 1993. "Modeling Nonlinearity over the Business Cycle," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 311-326 National Bureau of Economic Research, Inc.
  6. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
  7. Blake LeBaron, . "Technical Trading Rules and Regime Shifts in Foreign Exchange," Working papers _007, University of Wisconsin - Madison.
  8. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-64, December.
  9. Frank, Murray & Gencay, Ramazan & Stengos, Thanasis, 1988. "International chaos?," European Economic Review, Elsevier, vol. 32(8), pages 1569-1584, October.
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Cited by:
  1. Risso, Wiston Adrián, 2008. "The informational efficiency and the financial crashes," Research in International Business and Finance, Elsevier, vol. 22(3), pages 396-408, September.
  2. Sergio Da Silva, 2004. "The Dornbusch Model with Chaos and Foreign Exchange Intervention," International Finance 0405017, EconWPA.
  3. Lubos Briatka, 2006. "How Big is Big Enough? Justifying Results of the iid Test Based on the Correlation Integral in the Non-Normal World," CERGE-EI Working Papers wp308, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
  4. Mahajan, Arvind & Wagner, Andrew J., 1999. "Nonlinear dynamics in foreign exchange rates," Global Finance Journal, Elsevier, vol. 10(1), pages 1-23.
  5. Carolina Castaldi & Giovanni Dosi, 2003. "The Grip of History and the Scope for Novelty: Some Results and Open Questions on Path Dependence in Economic Processes," LEM Papers Series 2003/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  6. Faggini, Marisa, 2010. "Chaos detection in economics. Metric versus topological tools," MPRA Paper 30928, University Library of Munich, Germany.
  7. Vitaliy Vandrovych, 2005. "Study of Nonlinearities in the Dynamics of Exchange Rates: Is There Any Evidence of Chaos?," Computing in Economics and Finance 2005 234, Society for Computational Economics.

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