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On the long memory properties of emerging capital markets: evidence from Istanbul stock exchange

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Author Info
Rehim Kili&art1;
Abstract

This paper analyses long memory properties of Istanbul Stock Exchange Market (ISE) National 100 daily dollar index returns, absolute and squared returns. Both parametric FIGARCH models and nonparametric methods are employed. Results indicate that, contrary to empirical evidence on some other emerging capital markets, daily returns do not possess long memory characteristics, however, similar to developed equity markets, evidence is provided of long memory dynamics in the conditional variance which can be modelled adequately by a FIGARCH model.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Applied Financial Economics.

Volume (Year): 14 (2004)
Issue (Month): 13 (September)
Pages: 915-922
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Handle: RePEc:taf:apfiec:v:14:y:2004:i:13:p:915-922

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Andersen, Torben G & Bollerslev, Tim, 1997. " Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July. [Downloadable!] (restricted)
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  2. John T. Barkoulas & Christopher F. Baum & Nickolaos Travlos, 1996. "Long Memory in the Greek Stock Market," Boston College Working Papers in Economics 356., Boston College Department of Economics. [Downloadable!]
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  3. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-68, July.
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  4. Cheung, Yin-Wong & Lai, Kon S., 1995. "A search for long memory in international stock market returns," Journal of International Money and Finance, Elsevier, vol. 14(4), pages 597-615, August. [Downloadable!] (restricted)
  5. Zhuanxin Ding & Clive Granger & Robert Engle, 1992. "A Long Memory Property of Stock Market Returns and a New Model," University of California at San Diego, Economics Working Paper Series 92-21, Department of Economics, UC San Diego.
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  6. 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. [Downloadable!] (restricted)
  7. Tim Bollerslev & Jeffrey M. Wooldridge, 1988. "Quasi-Maximum Likelihood Estimation of Dynamic Models with Time-Varying Covariances," Working papers 505, Massachusetts Institute of Technology (MIT), Department of Economics.
  8. 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, vol. 16(3), pages 280-83, July.
  9. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July. [Downloadable!] (restricted)
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  1. Rehim Kiliç, 2007. "Conditional Volatility and Distribution of Exchange Rates: GARCH and FIGARCH Models with NIG Distribution," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(3), pages 1430-1430. [Downloadable!] (restricted)
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