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Long memory and non-linearity in Stock Markets

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Author Info
Bond, Derek
Dyson, Kenneth

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Abstract

In this paper the long memory and non-linear properties of share prices in the UK’s Stock Exchange and AIM are explored. The results suggest that the most commonly traded shares exhibit long memory thus raising interesting issues about the validity of normal assumptions of market efficiencies.

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File URL: http://mpra.ub.uni-muenchen.de/252/
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Publisher Info
Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 252.

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Date of creation: Sep 2006
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Handle: RePEc:pra:mprapa:252

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Related research
Keywords: Efficient Markets Long Memory Nonlinear Models

Find related papers by JEL classification:
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November. [Downloadable!] (restricted)
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  2. Katsumi Shimotsu, 2006. "Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend," Working Papers 1061, Queen's University, Department of Economics. [Downloadable!]
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  3. Hamilton, James D, 2001. "A Parametric Approach to Flexible Nonlinear Inference," Econometrica, Econometric Society, vol. 69(3), pages 537-73, May.
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  4. Gil-Alana, L.A., 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, Elsevier, vol. 15(1), pages 28-48. [Downloadable!] (restricted)
  5. Dahl, Christian M. & Gonzalez-Rivera, Gloria, 2003. "Testing for neglected nonlinearity in regression models based on the theory of random fields," Journal of Econometrics, Elsevier, vol. 114(1), pages 141-164, May. [Downloadable!] (restricted)
  6. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22. [Downloadable!]
    Other versions:
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