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Modeling Tick-by-Tick Realized Correlations

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Author Info
Fulvio Corsi ()
Francesco Audrino ()

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Abstract

We propose a tree-structured heterogeneous autoregressive (tree-HAR) process as a simple and parsimonious model for the estimation and prediction of tick-by-tick realized correlations. The model can account for different time and other relevant predictors' dependent regime shifts in the conditional mean dynamics of the realized correlation series. Testing the model on S&P 500 and 30-year treasury bond futures realized correlations, we provide empirical evidence that the tree-HAR model reaches a good compromise between simplicity and flexibility, and yields accurate single- and multi-step out-of-sample forecasts. Such forecasts are also better then those obtained from other standard approaches.

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File URL: http://www.vwa.unisg.ch/RePEc/usg/dp2008/DP-05-Co.pdf
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Publisher Info
Paper provided by Department of Economics, University of St. Gallen in its series University of St. Gallen Department of Economics working paper series 2008 with number 2008-05.

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Length: 29 pages
Date of creation: Jan 2008
Date of revision:
Handle: RePEc:usg:dp2008:2008-05

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Related research
Keywords: High frequency data; Realized correlation; Stock-bond correlation; Tree-structured models; HAR; Regimes;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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  1. Connolly, Robert & Stivers, Chris & Sun, Licheng, 2005. "Stock Market Uncertainty and the Stock-Bond Return Relation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(01), pages 161-194, March. [Downloadable!]
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    Other versions:
  3. Massimo Guidolin & Allan Timmerman, 2005. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Working Papers 2005-003, Federal Reserve Bank of St. Louis. [Downloadable!]
    Other versions:
  4. Fabio Trojani & Francesco Audrino, 2006. "Estimating and predicting multivariate volatility thresholds in global stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 345-369. [Downloadable!]
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  6. Michael McAller & Marcelo C. Medeiros, 2007. "A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries," Textos para discussão 544, Department of Economics PUC-Rio (Brazil). [Downloadable!]
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  7. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572. [Downloadable!] (restricted)
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  8. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June. [Downloadable!] (restricted)
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  9. Marcelo Cunha Medeiros & Alvaro Veiga, 2004. "Modelling multiple regimes in financial volatility with a flexible coefficient GARCH model," Textos para discussão 486, Department of Economics PUC-Rio (Brazil). [Downloadable!]
  10. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December. [Downloadable!] (restricted)
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  11. Ole E. Barndorff-Nielsen & Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280. [Downloadable!] (restricted)
    Other versions:
  12. Valeri Voev & Asger Lunde, 2007. "Integrated Covariance Estimation using High-frequency Data in the Presence of Noise," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 68-104. [Downloadable!] (restricted)
  13. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March. [Downloadable!] (restricted)
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  14. Christiansen, Charlotte & Ranaldo, Angelo, 2006. "Realized Bond-Stock Correlation: Macroeconomic Announcement Effects," Working Papers 2006-2, Swiss National Bank. [Downloadable!]
    Other versions:
  15. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, School of Economics and Management, University of Aarhus. [Downloadable!]
  16. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October. [Downloadable!] (restricted)
  17. Fulvio Corsi & Francesco Audrino, 2008. "Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects," University of St. Gallen Department of Economics working paper series 2008 2008-04, Department of Economics, University of St. Gallen. [Downloadable!]
  18. Francesco Audrino & Fabio Trojani, 2007. "A general multivariate threshold GARCH model with dynamic conditional correlations," University of St. Gallen Department of Economics working paper series 2007 2007-25, Department of Economics, University of St. Gallen. [Downloadable!]
    Other versions:
  19. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July. [Downloadable!] (restricted)
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