Advanced Search
MyIDEAS: Login to save this article or follow this journal

Common Intraday Periodicity

Contents:

Author Info

  • Alain Hecq
  • Sébastien Laurent
  • Franz C. Palm

Abstract

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 30 U.S. 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. Copyright The Author 2011. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://hdl.handle.net/10.1093/jjfinec/nbr012
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.

Volume (Year): 10 (2011)
Issue (Month): 2 (2012 20 12)
Pages: 325-353

as in new window
Handle: RePEc:oup:jfinec:v:10:y:2011:i:2:p:325-353

Contact details of provider:
Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK
Fax: 01865 267 985
Email:
Web page: http://jfec.oxfordjournals.org/
More information through EDIRC

Order Information:
Web: http://www.oup.co.uk/journals

Related research

Keywords:

Other versions of this item:

References

References listed on IDEAS
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.:
as in new window
  1. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Papers, Economics Group, Nuffield College, University of Oxford 2003-W17, Economics Group, Nuffield College, University of Oxford.
  2. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, Society for Financial Econometrics, vol. 7(2), pages 174-196, Spring.
  3. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 13(3), pages 253-63, July.
  4. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Jump-Robust Volatility Estimation using Nearest Neighbor Truncation," NBER Working Papers 15533, National Bureau of Economic Research, Inc.
  5. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, Elsevier, vol. 131(1-2), pages 97-121.
  6. 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, Elsevier, vol. 132(1), pages 7-42, May.
  7. Athanasopoulos, George & Guillén, Osmani Teixeira de Carvalho & Issler, João Victor & Vahid, Farshid, 2010. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," Economics Working Papers (Ensaios Economicos da EPGE) 704, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  8. Werker, B.J.M. & Drost, F.C., 1996. "Closing the GARCH gap: Continuous time GARCH modeling," Open Access publications from Tilburg University, Tilburg University urn:nbn:nl:ui:12-72561, Tilburg University.
  9. 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, CIRPEE 0533, CIRPEE.
  10. LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  11. Andrew Patton, 2006. "Volatility Forecast Comparison using Imperfect Volatility Proxies," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney 175, Quantitative Finance Research Centre, University of Technology, Sydney.
  12. Taylor, Stephen J. & Xu, Xinzhong, 1997. "The incremental volatility information in one million foreign exchange quotations," Journal of Empirical Finance, Elsevier, Elsevier, vol. 4(4), pages 317-340, December.
  13. Raffaella Giacomini & Halbert White, 2003. "Tests of Conditional Predictive Ability," Econometrics, EconWPA 0308001, EconWPA.
  14. Suzanne S. Lee & Per A. Mykland, 2008. "Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 21(6), pages 2535-2563, November.
  15. Pierre Giot, 2005. "Market risk models for intraday data," The European Journal of Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 11(4), pages 309-324.
  16. Marcel P. Visser, 2011. "GARCH Parameter Estimation Using High-Frequency Data," Journal of Financial Econometrics, Society for Financial Econometrics, Society for Financial Econometrics, vol. 9(1), pages 162-197, Winter.
  17. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, MIT Press, vol. 89(4), pages 701-720, November.
  18. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, Elsevier, vol. 45(1-2), pages 7-38.
  19. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 23, pages 365-380, October.
  20. Engle, Robert F & Hylleberg, Svend, 1996. "Common Seasonal Features: Global Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, Department of Economics, University of Oxford, vol. 58(4), pages 615-30, November.
  21. Engle, Robert F & Susmel, Raul, 1993. "Common Volatility in International Equity Markets," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 11(2), pages 167-76, April.
  22. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, Elsevier, vol. 4(2-3), pages 115-158, June.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers, Federal Reserve Bank of St. Louis 2012-008, Federal Reserve Bank of St. Louis.
  2. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2013. "Which continuous-time model is most appropriate for exchange rates?," Working Papers, Federal Reserve Bank of St. Louis 2013-024, Federal Reserve Bank of St. Louis.
  3. Dewachter, Hans & Erdemlioglu, Deniz & Gnabo, Jean-Yves & Lecourt, Christelle, 2014. "The intra-day impact of communication on euro-dollar volatility and jumps," Journal of International Money and Finance, Elsevier, Elsevier, vol. 43(C), pages 131-154.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:oup:jfinec:v:10:y:2011:i:2:p:325-353. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press) or (Christopher F. Baum).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.