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Long Memory in the Ukrainian Stock Market

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  • Guglielmo Maria Caporale
  • Luis A. Gil-Alana

Abstract

This paper examines the dynamics of stock prices in Ukraine by estimating the degree of persistence of the PFTS stock market index. Using long memory techniques we show that the log prices series is I(d) with d slightly above 1, implying that returns are characterised by a small degree of long memory and thus are predictable using historical data. Moreover, their volatility, measured as the absolute and squared returns, also displays long memory. Finally, we examine if the time dependence is affected by the day of the week; the results indicate that Mondays and Fridays are characterised by higher dependency, consistently with the literature on anomalies in stock market prices.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.417292.de/dp1279.pdf
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Bibliographic Info

Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 1279.

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Length: 20 p.
Date of creation: 2013
Date of revision:
Handle: RePEc:diw:diwwpp:dp1279

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Keywords: Stock market prices; Efficient market hypothesis; Long memory; Fractional integration;

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  1. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  2. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data: Reply," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 16(3), pages 280-83, July.
  3. Gibbons, Michael R & Hess, Patrick, 1981. "Day of the Week Effects and Asset Returns," The Journal of Business, University of Chicago Press, vol. 54(4), pages 579-96, October.
  4. Chris Brooks & Gita Persand, 2001. "Seasonality in Southeast Asian stock markets: some new evidence on day-of-the-week effects," Applied Economics Letters, Taylor & Francis Journals, vol. 8(3), pages 155-158.
  5. I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics, EconWPA 9605004, EconWPA, revised 26 Sep 1996.
  6. Jeffrey Jaffe & R. Westerfield, . "The Week-End Effect in Common Stock Returns: The International Evidence," Rodney L. White Center for Financial Research Working Papers, Wharton School Rodney L. White Center for Financial Research 3-85, Wharton School Rodney L. White Center for Financial Research.
  7. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
  8. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  9. Ignacio N Lobato & Carlos Velasco, 2007. "Efficient Wald Tests for Fractional Unit Roots," Econometrica, Econometric Society, Econometric Society, vol. 75(2), pages 575-589, 03.
  10. Peter M. Robinson & M. Henry, 1999. "Long and short memory conditional heteroskedasticity in estimating the memory parameter of levels," LSE Research Online Documents on Economics 304, London School of Economics and Political Science, LSE Library.
  11. Solnik, Bruno & Bousquet, Laurence, 1990. "Day-of-the-week effect on the Paris Bourse," Journal of Banking & Finance, Elsevier, vol. 14(2-3), pages 461-468, August.
  12. French, Kenneth R., 1980. "Stock returns and the weekend effect," Journal of Financial Economics, Elsevier, vol. 8(1), pages 55-69, March.
  13. Abadir, Karim M. & Distaso, Walter & Giraitis, Liudas, 2007. "Nonstationarity-extended local Whittle estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 1353-1384, December.
  14. Jeffrey Jaffe & R. Westerfield, . "The Week-End Effect in Common Stock Returns: The International Evidence," Rodney L. White Center for Financial Research Working Papers, Wharton School Rodney L. White Center for Financial Research 03-85, Wharton School Rodney L. White Center for Financial Research.
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