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Common intraday periodicity

  • Hecq Alain
  • Laurent Sébastien
  • Palm Franz

    (METEOR)

Using a reduced rank regression framework as well as information criteria we investigate the presence of commonalities in the intraday periodicity, a dominant feature in the return volatility of most intraday financial time series. We find that the test has little size distortion and reasonable power even in the presence of jumps. We also find that only three factors are needed to describe the intraday periodicity of thirty US asset returns sampled at the 5-minute frequency. Interestingly, we find that for most series the models imposing these commonalities deliver better forecasts of the conditional intraday variance than those where the intraday periodicity is estimated for each asset separately.

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File URL: http://digitalarchive.maastrichtuniversity.nl/fedora/objects/guid:0fe69702-30ac-4e90-9d1e-45ce6aeb6774/datastreams/ASSET1/content
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Paper provided by Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR) in its series Research Memorandum with number 010.

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Date of creation: 2011
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Handle: RePEc:unm:umamet:2011010
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  1. George Athanasopoulos & Osmani Teixeira de Carvalho Guillén & João Victor Issler & Farshid Vahid, 2010. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," Working Papers Series 205, Central Bank of Brazil, Research Department.
  2. Hecq Alain & Laurent Sébastien & Palm Franz, 2011. "On the Univariate Representation of Multivariate Volatility Models with Common Factors," Research Memorandum 011, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  3. Georges Dionne & Pierre Duchesne & Maria Pacurar, 2005. "Intraday Value at Risk (IVaR) Using Tick-by-Tick Data with Application to the Toronto Stock Exchange," Cahiers de recherche 0533, CIRPEE.
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  10. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
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  18. Engle, Robert F. & Marcucci, Juri, 2006. "A long-run Pure Variance Common Features model for the common volatilities of the Dow Jones," Journal of Econometrics, Elsevier, vol. 132(1), pages 7-42, May.
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  21. Neil Shephard & Ole E. Barndorff-Nielsen, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Series Working Papers 2003-W18, University of Oxford, Department of Economics.
  22. Engle, Robert F & Susmel, Raul, 1993. "Common Volatility in International Equity Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 167-76, April.
  23. Engle, Robert F & Hylleberg, Svend, 1996. "Common Seasonal Features: Global Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 615-30, November.
  24. 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.
  25. Pierre Giot, 2005. "Market risk models for intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 11(4), pages 309-324.
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