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Robust estimation of intraweek periodicity in volatility and jump detection

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Author Info

  • Boudt, Kris
  • Croux, Christophe
  • Laurent, S.

Abstract

Opening, lunch and closing of financial markets induce a periodic component in the volatility of high-frequency returns. We show that price jumps cause a large bias in the classical periodicity estimators and propose robust alternatives. We find that accounting for periodicity greatly improves the accuracy of intraday jump detection methods. It increases the power to detect the relatively small jumps occurring at times for which volatility is periodically low and reduces the number of spurious jump detections at times of periodically high volatility. We use the series of detected jumps to estimate robustly the long memory parameter of the squared EUR/USD, GBP/USD and YEN/USD returns

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Bibliographic Info

Paper provided by Katholieke Universiteit Leuven in its series Open Access publications from Katholieke Universiteit Leuven with number urn:hdl:123456789/277137.

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Date of creation: Mar 2011
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Publication status: Published in Journal of Empirical Finance (2011-03) v.18, p.353-367
Handle: RePEc:ner:leuven:urn:hdl:123456789/277137

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Web page: http://www.kuleuven.be

Related research

Keywords: High-frequency foreign exchange data; Jump detection; Long memory; Periodicity;

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References

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  1. Takatosh Ito & Richard K. Lyons & Michael T. Melvin, 1997. "Is there private information in the FX market? the Tokyo experiment," Pacific Basin Working Paper Series 97-04, Federal Reserve Bank of San Francisco.
  2. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Papers 2003-W17, Economics Group, Nuffield College, University of Oxford.
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  7. Goncalves, Silvia & Meddahi, Nour, 2009. "Bootstrapping Realized Volatility," Open Access publications from University of Toulouse 1 Capitole http://neeo.univ-tlse1.fr, University of Toulouse 1 Capitole.
  8. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
  9. Taylor, Stephen J. & Xu, Xinzhong, 1997. "The incremental volatility information in one million foreign exchange quotations," Journal of Empirical Finance, Elsevier, vol. 4(4), pages 317-340, December.
  10. Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely, 2011. "Jumps, cojumps and macro announcements," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 893-921, 09.
  11. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
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  15. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
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Cited by:
  1. Eichler Michael & Tuerk Dennis, 2012. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Research Memoranda 036, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
  2. Jean-Yves Gnabo & Jér�me Lahaye & Sébastien Laurent & Christelle Lecourt, 2012. "Do jumps mislead the FX market?," Quantitative Finance, Taylor and Francis Journals, vol. 12(10), pages 1521-1532, October.
  3. Barbara Bedowska-Sojka, 2011. "The Impact of Macro News on Volatility of Stock Exchanges," Dynamic Econometric Models, Wydawnictwo Naukowe Uniwersytetu Mikolaja Kopernika, vol. 11, pages 99-110.

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