Modeling tick-by-tick realized correlations

Computational Statistics and Data Analysis

Volumn 54, Issue 11, 2010, Pages 2372-2382

  Audrino, Francesco ^a   Corsi, Fulvio ^b  

^a UNIVERSITY OF ST GALLEN   (Switzerland)

^b UNIVERSITY OF LUGANO   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

AUTO-REGRESSIVE; CONDITIONAL MEANS; EMPIRICAL EVIDENCE; MODEL YIELDS; MULTI-PERIOD; MULTI-STEP; OUT-OF-SAMPLE FORECAST; REGIME SHIFT; TREASURY BONDS;

FORECASTING;

EID: 77955277030     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2009.09.033     Document Type: Article

References (47)

1. T. Andersen, T. Bollerslev, F. Diebold, and H. Ebens The distribution of realized stock return volatility Journal of Financial Economics 61 1 2001 43 76 (Pubitemid 33376366)
2. T.G. Andersen, T. Bollerslev, F.X. Diebold, and P. Labys The distribution of exchange rate volatility Journal of the American Statistical Association 96 2001 42 55
3. T.G. Andersen, T. Bollerslev, F.X. Diebold, and P. Labys Modeling and forecasting realized volatility Econometrica 71 2 2003 579 625
4. Andersen, T.G., Bollerslev, T., Huang, X., 2007. A reduced form framework for modeling volatility of speculative prices based on realized variation measures. CREATES Research Paper Series 14
5. F. Audrino, and P. Bhlmann Tree-structured GARCH models Journal of the Royal Statistical Society, Series B 63 2001 727 744
6. F. Audrino, and F. Trojani Estimating and predicting multivariate volatility regimes in global stock markets Journal of Applied Econometrics 21 3 2006 345 369
7. Audrino, F., Trojani, F., 2007. A general multivariate GARCH model with dynamic conditional correlations. VWA Discussion Paper Series 25, University of St. Gallen
8. O.E. Barndorff-Nielsen, and N. Shephard Non-Gaussian OrnsteinUhlenbeck- based models and some of their uses in financial economics Journal of the Royal Statistical Society, Series B 63 2001 167 241
9. O.E. Barndorff-Nielsen, and N. Shephard Econometric analysis of realized volatility and its use in estimating stochastic volatility models Journal of the Royal Statistical Society, Series B 64 2002 253 280
10. O.E. Barndorff-Nielsen, and N. Shephard Estimating quadratic variation using realized variance Journal of Applied Econometrics 17 5 2002 457 477
11. O.E. Barndorff-Nielsen, and N. Shephard Econometric analysis of realised covariation: High frequency covariance, regression and correlation in financial economics Econometrica 72 3 2004 885 925
12. O.E. Barndorff-Nielsen, and N. Shephard How accurate is the asymptotic approximation to the distribution of realized volatility? D.W.F. Andrews, J.H. Stock, Identification and Inference for Econometric Models. A Festschrift in Honour of T.J. Rothenberg 2005 Cambridge University Press 306 331
13. Barndorff-Nielsen, O.E., Hansen, P.R., Lunde, A., Shephard, N., 2008. Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. Working Paper
14. G. Barone-Adesi, F. Bourgoin, and K. Giannopoulos Don't Look Back Risk 11 August 1998 100 104
15. G. Barone-Adesi, K. Giannopoulos, and L. Vosper VaR without correlations for portfolio of derivative securities Journal of Futures Markets 19 April 1999 583 602
16. L. Breiman, J.H. Friedman, R.A. Olshen, and C.J. Stone Classification and Regression Trees 1984 Wadsworth Belmont, CA
17. L. Cappiello, R.F. Engle, and K. Sheppard Asymmetric dynamics in the correlations of global equity and bond returns Journal of Financial Econometrics 4 2006 537 572
18. C. Christiansen, and A. Ranaldo Realized bond-stock correlation: Macroeconomic announcement effects Journal of Futures Markets 27 5 2007 439 469
19. F. Comte, and E. Renault Long memory in continuous time stochastic volatility models Mathematical Finance 8 1998 291 323 (Pubitemid 128342547)
20. R. Connolly, C. Stivers, and L. Sun Stock market uncertainty and the stockbond return relation Journal of Financial and Quantitative Analysis 40 2005 161 194
21. F. Corsi Simple approximate long memory models of realized volatility Journal of Financial Econometrics 7 2009 174 196
22. Corsi, F., Audrino, F., 2008. Realized covariance tick-by-tick in presence of rounded time stamps and general microstructure effects. University of St. Gallen (unpublished manuscript)
23. F. Corsi, S. Mittnik, C. Pigorsch, and U. Pigorsch The volatility of realized volatility Econometric Reviews 27 1 2008 46 78 (special issue)
24. Curci, G., Corsi, F., 2003. A discrete sine transform approach for realized volatility measurement. NCCR FINRISK Working Paper No. 44
25. F.X. Diebold, and A. Inoue Long memory and regime switching Journal of Econometrics 105 2001 131 159
26. B. Efron, and R.J. Tibshirani An Introduction to the Bootstrap 1993 Chapman & Hall London
27. R. Ferland, and S. Lalancette Dynamics of realized volatilities and correlations: An empirical study Journal of Banking and Finance 30 7 2006 2109 2130
28. Griffin, J.E., Oomen, R.C.A., 2006. Covariance measurement in the presence of non-synchronous trading and market microstructure noise (unpublished manuscript)
29. M. Guidolin, and A. Timmermann An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns Journal of Applied Econometrics 21 1 2006 1 22
30. B.E. Hansen Inference when a nuisance parameter is not identified under the null hypothesis Econometrica 64 2006 413 430
31. P.R. Hansen A test for superior predictive ability Journal of Business & Economic Statistics 23 2005 365 380
32. T. Hayashi, and N. Yoshida On covariance estimation of non-synchronously observed diffusion processes Bernoulli 11 2 2005 359 379
33. Hillebrand, E., Medeiros, M.C., 2008. The benefits of bagging for forecast models of realized volatility. Econometric Reviews (in press)
34. A. Ilmanen Stockbond correlations Journal of Fixed Income 13 2003 55 66
35. H.R. Knsch The jackknife and the bootstrap for general stationary observations Annals of Statistics 17 1989 1217 1241
36. Li, L., 2002. Macroeconomic factors and the correlation of stock and bond returns. Working Paper, Yale International Center for Finance
37. Martens, M., 2004. Estimating unbiased and precise realized covariances. Social Science Research Network Electronic Library
38. M. McAleer, and M.C. Medeiros A multiple regime smooth transition heterogenous autoregressive model for long memory and asymmetries Journal of Econometrics 147 2008 104 119
39. M.C. Medeiros, and A. Veiga Modeling multiple regimes in financial volatility with a flexible coefficient GARCH(1, 1) model Econometric Theory 25 1 2009 117 161
40. U. Mller, M. Dacorogna, R. Dave, R. Olsen, O. Pictet, and J. Weizsacker Volatilities of different time resolutions Analyzing the dynamics of market components Journal of Empirical Finance 4 1997 213 239
41. Palandri, A., 2006. Consistent realized covariance for asynchronous observations contaminated by market microstructure noise (unpublished manuscript)
42. L. Pastor, and R.F. Stambaugh Liquidity risk and expected stock returns The Journal of Political Economy 111 2003 642 685
43. D.N. Politis, and J.P. Romano The stationary bootstrap Journal of the American Statistical Association 89 1994 1303 1313
44. Ranaldo, A., Reynard, S., 2008. Monetary Policy Effects on Long-Term Rates and Stock Prices (unpublished manuscript)
45. Sheppard, K., 2006. Realized covariance and scrambling (unpublished manuscript)
46. V. Voev, and A. Lunde Integrated covariance estimation using high-frequency data in the presence of noise Journal of Financial Econometrics 5 2007 68 104
47. L. Zhang, P.A. Mykland, and Y. At-Sahalia A tale of two time scales: Determining integrated volatility with noisy high frequency data Journal of the American Statistical Association 100 2005 1394 1411