English, Article edition: Modeling long-term memory effect in stock prices: A comparative analysis with GPH test and Daubechies wavelets Alper Ozun; Atilla Cifter

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Bookmark: http://trove.nla.gov.au/version/8623
Physical Description
  • article
Language
  • English

Edition details

Title
  • Modeling long-term memory effect in stock prices: A comparative analysis with GPH test and Daubechies wavelets
Author
  • Alper Ozun
  • Atilla Cifter
Physical Description
  • article
Notes
  • 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.
  • Economic cycles, Emerging markets, Stock prices, Turkey
  • RePEc:eme:sefpps:v:25:y:2008:i:1:p:38-48
Language
  • English
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