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Long Memory on the German Stock Exchange

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Author Info
Henryk GURGUL () (Faculty of Management, University of Science and Technology, Krakow – corresponding author)
Tomasz WÓJTOWICZ (Faculty of Management, University of Science and Technology, Krakow)

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Abstract

In this study, the contributors present the results of their investigations into the long-memory properties of trading volume and the volatility of stock returns (given by absolute returns and alternatively by square returns). Their database is daily stock data of German companies in the DAX segment of the German Stock Exchange. The purpose of these investigations is the calculation of memory parameters and to determine whether there exists the same degree of long memory for trading-volume and return-volatility data. Calculations are performed on daily results from January 1994 to November 2005 and in three sub-periods: January 1994 to December 1997, January 1998 to December 2001, and January 2002 to November 2005.

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Publisher Info
Article provided by Charles University Prague, Faculty of Social Sciences in its journal Finance a uver - Czech Journal of Economics and Finance.

Volume (Year): 56 (2006)
Issue (Month): 09-10 (September)
Pages: 447-468
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:fau:fauart:v:56:y:2006:i:9-10:p:447-468

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Related research
Keywords: DAX 30; trading volume; univariate and bivariate long memory;

Find related papers by JEL classification:
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
G35 - Financial Economics - - Corporate Finance and Governance - - - Payout Policy

References listed on IDEAS
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  1. Lamoureux, Christopher G & Lastrapes, William D, 1994. "Endogenous Trading Volume and Momentum in Stock-Return Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 253-60, April.
  2. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188. [Downloadable!] (restricted)
  3. Velasco, Carlos, 1999. "Non-stationary log-periodogram regression," Journal of Econometrics, Elsevier, vol. 91(2), pages 325-371, August. [Downloadable!] (restricted)
  4. I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics 9605004, EconWPA, revised 26 Sep 1996. [Downloadable!]
    Other versions:
  5. Katsumi Shimotsu & Peter C.B. Phillips, 2002. "Exact Local Whittle Estimation of Fractional Integration," Economics Discussion Papers 535, University of Essex, Department of Economics. [Downloadable!]
    Other versions:
  6. Lobato, Ignacio N., 1999. "A semiparametric two-step estimator in a multivariate long memory model," Journal of Econometrics, Elsevier, vol. 90(1), pages 129-153, May. [Downloadable!] (restricted)
  7. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 5(2), pages 199-242. [Downloadable!] (restricted)
  8. Crato, Nuno, 1994. "Some International Evidence Regarding the Stochastic Memory of Stock Returns," Applied Financial Economics, Taylor and Francis Journals, vol. 4(1), pages 33-39, February. [Downloadable!] (restricted)
  9. Katsumi Shimotsu & Peter C.B. Phillips, 2000. "Pooled Log Periodogram Regression," Cowles Foundation Discussion Papers 1267, Cowles Foundation, Yale University. [Downloadable!]
  10. Giampiero M. Gallo, Barbara Pacini, 2000. "The effects of trading activity on market volatility," European Journal of Finance, Taylor and Francis Journals, vol. 6(2), pages 163-175, June. [Downloadable!] (restricted)
  11. Lobato, Ignacio N & Velasco, Carlos, 2000. "Long Memory in Stock-Market Trading Volume," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 410-27, October.
  12. Katsumi Shimotsu & Peter C.B. Phillips, 2000. "Local Whittle Estimation in Nonstationary and Unit Root Cases," Cowles Foundation Discussion Papers 1266, Cowles Foundation, Yale University, revised Sep 2003. [Downloadable!]
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