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Long memory in stock market volatility and the volatility-in-mean effect: the FIEGARCH-M model

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  • Bent Jesper Christensen

    ()
    (University of Aarhus and CREATES)

  • Jie Zhu

    ()
    (University of Aarhus and CREATES)

  • Morten Ørregaard Nielsen

    ()
    (Queen's University and CREATES)

Abstract

We extend the fractionally integrated exponential GARCH (FIEGARCH) model for daily stock return data with long memory in return volatility of Bollerslev and Mikkelsen (1996) by introducing a possible volatility-in-mean effect. To avoid that the long memory property of volatility carries over to returns, we consider a filtered FIEGARCH-in-mean (FIEGARCH-M) effect in the return equation. The filtering of the volatility-in-mean component thus allows the co-existence of long memory in volatility and short memory in returns. We present an application to the daily CRSP value-weighted cum-dividend stock index return series from 1926 through 2006 which documents the empirical relevance of our model. The volatility-in-mean effect is significant, and the FIEGARCH-M model outperforms the original FIEGARCH model and alternative GARCH-type specifications according to standard criteria.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1207.pdf
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 1207.

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Length: 22 pages
Date of creation: Jun 2009
Date of revision:
Handle: RePEc:qed:wpaper:1207

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Keywords: FIEGARCH; financial leverage; GARCH; long memory; risk-return tradeoff; stock returns; volatility feedback;

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References

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Citations

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Cited by:
  1. Massimiliano Caporin & Angelo Ranaldo, 2011. "On the Predictability of Stock Prices: a Case for High and Low Prices," Working Papers 2011-11, Swiss National Bank.
  2. Dahl, Christian M. & Iglesias, Emma M., 2009. "Volatility spill-overs in commodity spot prices: New empirical results," Economic Modelling, Elsevier, vol. 26(3), pages 601-607, May.
  3. Bent Jesper Christensen & Christian M. Dahl & Emma M. Iglesias, 2008. "Semiparametric Inference in a GARCH-in-Mean Model," CREATES Research Papers 2008-46, School of Economics and Management, University of Aarhus.
  4. Walid Chkili & Chaker Aloui & Duc Khuong Nguyen, 2014. "Instabilities in the relationships and hedging strategies between crude oil and US stock markets: do long memory and asymmetry matter?," Working Papers 2014-549, Department of Research, Ipag Business School.
  5. Christian Conrad & Menelaos Karanasos & Ning Zeng, 2008. "Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A multi-country study," Working Papers 0472, University of Heidelberg, Department of Economics, revised Jul 2008.
  6. Charfeddine Lanouar, 2014. "True or Spurious Long Memory in Volatility : Further Evidence on the Energy Futures Markets," Working Papers 2014-503, Department of Research, Ipag Business School.
  7. Bent Jesper Christensen & Morten Ørregaard Nielsen & Jie Zhu, 2012. "The impact of financial crises on the risk-return tradeoff and the leverage effect," CREATES Research Papers 2012-19, School of Economics and Management, University of Aarhus.
  8. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.

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