Skip to main content

High Frequency Correlation Modelling

  • Chapter

Part of the book series: New Economic Windows ((NEW))

Abstract

Many statistical arbitrage strategies, such as pair trading or basket trading, are based on several assets. Optimal execution routines should also take into account correlation between stocks when proceeding clients orders. However, not so much effort has been devoted to correlation modelling and only few empirical results are known about high frequency correlation. Depending on the time scale under consideration, a plausible candidate for modelling correlation should:

  • at high frequency: reproduce the Epps effect [1], take into account lead-lag relationships between assets [2]

  • at the daily scale: avoid purely Gaussian correlations [3].

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   79.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Epps T. W. (1979) Comovements in Stock Prices in the Very Short-Run. Journal of the American Statistical Association 74, 291–298

    Google Scholar 

  2. Toth B., Kertesz J. (2009) The Epps Effect Revisited, Quantitative Finance 9(7), 793–802

    Article  Google Scholar 

  3. Bouchaud J.-P., Potters M. (2004) Theory of Financial Risk and Derivative Pricing, From Statistical Physics to Risk Management. Cambridge University Press

    Google Scholar 

  4. Reno R. (2003) A Closer Look at the Epps Effect. International Journal of Theoretical and Applied Finance 6: 87–102

    Article  Google Scholar 

  5. Toth B., Kertesz J. (2006) Increasing Market Efficiency: Evolution of Cross-Correlations of Stock Returns, Physica A 360, 505–515

    Article  Google Scholar 

  6. Iori G., Precup O.V. (2006) Cross-correlation Measures in the High Frequency Domain, Working Paper

    Google Scholar 

  7. Toth B., Kertesz J. (2007) On the origin of the Epps Effect, Physica A 383(1), 54–58

    Article  Google Scholar 

  8. Bacry E. (2010) Modeling microstructure noise using point processes, Econophys-Kolkata V Conference, submitted to Quantitative finance papers

    Google Scholar 

  9. Robert C. Y., Rosenbaum M. (2009) On the limiting spectral distribution of the covariance matrices of time-lagged processes, to appear in Journal of Multivariate Analysis

    Google Scholar 

  10. Robert C. Y., Rosenbaum M., Hoffman M., Yoshida N. (2010) Estimation of the lead-lag parameter from non-synchronous data, Working Paper

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Italia

About this chapter

Cite this chapter

Huth, N., Abergel, F. (2011). High Frequency Correlation Modelling. In: Abergel, F., Chakrabarti, B.K., Chakraborti, A., Mitra, M. (eds) Econophysics of Order-driven Markets. New Economic Windows. Springer, Milano. https://doi.org/10.1007/978-88-470-1766-5_13

Download citation

Publish with us

Policies and ethics