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Modeling long-term memory effect in stock prices: A comparative analysis with GPH test and Daubechies wavelets

  • Alper Ozun
  • Atilla Cifter

Purpose – This paper, using Turkish stock index data, set outs to present long-term memory effect using chaotic and conventional unit root tests and investigate if chaotic technique as wavelets captures long-memory better than conventional techniques. Design/methodology/approach – Haar and Daubechies as wavelet-based OLS estimator and GPH and other classical models are applied in order to investigate the performance of long memory in the time series. Findings – The results indicate that Daubechies wavelet analysis provide the accurate determination for long memory where conventional techniques does not. Originality/value – The research results have both methodological and practical originality. On the theoretical side, the wavelet-based OLS estimator is superior in modeling the behaviours of the stock returns in emerging markets where non-linearities 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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Article provided by Emerald Group Publishing in its journal Studies in Economics and Finance.

Volume (Year): 25 (2008)
Issue (Month): 1 (March)
Pages: 38-48

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Handle: RePEc:eme:sefpps:v:25:y:2008:i:1:p:38-48
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  1. Tkacz Greg, 2001. "Estimating the Fractional Order of Integration of Interest Rates Using a Wavelet OLS Estimator," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(1), pages 1-15, April.
  2. Patrick M. Crowley, 2005. "An intuitive guide to wavelets for economists," GE, Growth, Math methods 0508009, EconWPA.
  3. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
  4. 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.
  5. Nason, G.P. & von Sachs, R., 1999. "Wavelets in Time Series Analysis," Papers 9901, Catholique de Louvain - Institut de statistique.
  6. Sowell, Fallaw, 1990. "The Fractional Unit Root Distribution," Econometrica, Econometric Society, vol. 58(2), pages 495-505, March.
  7. Mark J. Jensen, 1997. "An Alternative Maximum Likelihood Estimator of Long-Memeory Processes Using Compactly Supported Wavelets," Econometrics 9709002, EconWPA.
  8. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Working Papers 02-3, Bank of Canada.
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