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Modeling Long-Term Memory Effect in Stock Prices: A Comparative Analysis with GPH Test and Daubechies Wavelets

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  • Ozun, Alper
  • Cifter, Atilla

Abstract

Long-term memory effect in stock prices might be captured, if any, with alternative models. Though Geweke and Porter-Hudak (1983) test model the long memory with the OLS estimator, a new approach based on wavelets analysis provide WOLS estimator for the memory effect. This article examines the long-term memory of the Istanbul Stock Index with the Daubechies-20, Daubechies-12, the Daubechies-4 and the Haar wavelets and compares the results of the WOLS estimators with that of OLS estimator based on the Geweke and Porter-Hudak test. While the results of the GPH test imply that the stock returns are memoryless, fractional integration parameters based on the Daubechies wavelets display that there is an explicit long-memory effect in the stock returns. The research results have both methodological and practical crucial conclusions. On the theoretical side, the wavelet based OLS estimator is superior in modeling the behaviours of the stock returns in emerging markets where nonlinearities and high volatility exist due to their chaotic natures. For practical aims, on the other hand, the results show that the Istanbul Stock Exchange is not in the weak-form efficient because the prices have memories that are not reflected in the prices, yet.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 2481.

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Date of creation: 01 Feb 2007
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Handle: RePEc:pra:mprapa:2481

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Keywords: Long-term memory; Wavelets; Stock prices; GPH test;

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  1. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Working Papers, Bank of Canada 02-3, Bank of Canada.
  2. Jensen, Mark J., 2000. "An alternative maximum likelihood estimator of long-memory processes using compactly supported wavelets," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 24(3), pages 361-387, March.
  3. Nason, G.P. & von Sachs, R., 1999. "Wavelets in Time Series Analysis," Papers, Catholique de Louvain - Institut de statistique 9901, Catholique de Louvain - Institut de statistique.
  4. Sowell, Fallaw, 1990. "The Fractional Unit Root Distribution," Econometrica, Econometric Society, Econometric Society, vol. 58(2), pages 495-505, March.
  5. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, Elsevier, vol. 53(3), pages 253-259, December.
  6. Tkacz Greg, 2001. "Estimating the Fractional Order of Integration of Interest Rates Using a Wavelet OLS Estimator," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, De Gruyter, vol. 5(1), pages 1-15, April.
  7. Patrick M. Crowley, 2005. "An intuitive guide to wavelets for economists," GE, Growth, Math methods, EconWPA 0508009, EconWPA.
  8. Erhan Bayraktar & H. Vincent Poor & Ronnie Sircar, 2007. "Estimating the Fractal Dimension of the S&P 500 Index using Wavelet Analysis," Papers math/0703834, arXiv.org.
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