Covariance measurement in the presence of non-synchronous trading and market microstructure noise

Journal of Econometrics

Volumn 160, Issue 1, 2011, Pages 58-68

  Griffin, Jim E ^a   Oomen, Roel C A ^b,c  

^a UNIVERSITY OF KENT   (United Kingdom)

^b DEUTSCHE BANK AG   (Germany)

^c UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

BIAS AND VARIANCE; CLOSED-FORM EXPRESSION; COVARIANCE ESTIMATION; MARKET MICROSTRUCTURES; RELATIVE EFFICIENCY; SPARSE SAMPLING; STOCHASTIC VOLATILITY;

COMMERCE; MICROSTRUCTURE;

ESTIMATION;

EID: 78649730581     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jeconom.2010.03.015     Document Type: Conference Paper

References (41)

1. T.G. Andersen, and T. Bollerslev Answering the skeptics: yes, standard volatility models do provide accurate forecasts International Economic Review 39 4 1998 885 905
2. T.G. Andersen, T. Bollerslev, F.X. Diebold, and P. Labys Modeling and forecasting realized volatility Econometrica 71 2 2003 579 625
3. Bandi, F.M., Russell, J.R., 2005. Realized covariation, realized beta, and microstructure noise. Manuscript, University of Chicago.
4. F.M. Bandi, and J.R. Russell Separating microstructure noise from volatility Journal of Financial Economics 79 2006 655 692
5. O.E. Barndorff-Nielsen, P.R. Hansen, A. Lunde, and N. Shephard Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise Econometrica 76 6 2008 1481 1536
6. Barndorff-Nielsen, O.E., Hansen, P.R., Lunde, A., Shephard, N., 2008b. Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. Manuscript, Oxford-Man Institute.
7. O.E. Barndorff-Nielsen, and N. Shephard Econometric analysis of realised volatility and its use in estimating stochastic volatility models Journal of the Royal Statistical Society, Series B 64 2002 253 280
8. O.E. Barndorff-Nielsen, and N. Shephard Econometric analysis of realised covariation: high frequency based covariance, regression and correlation in financial economics Econometrica 72 3 2004 885 925
9. T. Bollerslev, and B.Y. Zhang Measuring and modeling systematic risk in factor pricing model using high-frequency data Journal of Empirical Finance 10 2003 533 558
10. K.J. Cohen, G.A. Hawawini, S.F. Maier, R.A. Schwartz, and D.K. Whitcomb Friction in the trading process and the estimation of systematic risk Journal of Financial Economics 12 1983 263 278
11. Corsi, F., Audrino, F., 2007. Realized correlation tick-by-tick. University of St. Gallen, Department of Economics, Discussion Paper No. 2007-02.
12. M.M. Dacorogna, R. Genay, U. Mller, R.B. Olsen, and O.V. Pictet An Introduction to High-Frequency Finance 2001 Academic Press London, UK
13. F. de Jong, and T. Nijman High frequency analysis of leadlag relationships between financial markets Journal of Empirical Finance 4 1997 257 277
14. E. Dimson Risk measurement when shares are subject to infrequent trading Journal of Financial Economics 7 1979 197 226
15. T.W. Epps Comovements in stock prices in the very short run Journal of the American Statistical Association 74 366 1979 291 298
16. L. Fisher Some new stock-market indexes Journal of Business 39 12 1966 191 225
17. J. Gatheral, and R.C.A. Oomen Zero-intelligence realized variance estimation Finance and Stochastics 14 2 2010 249 283
18. J.E. Griffin, and R.C. Oomen Sampling returns for realized variance calculations: tick time or transaction time? Econometric Reviews 27 13 2008 230 253
19. Griffin, J.E., Oomen, R.C., 2009. Appendix to covariance measurement in the presence of non-synchronous trading and market microstructure noise. Available at: http://ssrn.com/abstract=1438825.
20. Hansen, P.R., Lunde, A., 2004. An unbiased measure of realized variance. Manuscript, Stanford University, Economics Department.
21. P.R. Hansen, and A. Lunde Realized variance and market microstructure noise Journal of Business & Economic Statistics 24 2 2006 127 161
22. F.H.D. Harris, T.H. McInish, G.L. Shoesmith, and R.A. Wood Cointegration, error correction, and price discovery on informationally linked security markets Journal of Financial & Quantitative Analysis 30 4 1995 563 579
23. J. Hasbrouck Empirical Market Microstructure 2007 Oxford University Press
24. Hautsch, N., Kyj, L., Oomen, R.C., 2009. A blocking and regularization approach to high dimensional realized covariance estimation. Manuscript, Quantitative Products Laboratory, Berlin.
25. T. Hayashi, and S. Kusuoka Consistent estimation of covariation under nonsynchronicity Statistical Inference for Stochastic Processes 11 1 2008 93 106
26. T. Hayashi, and N. Yoshida On covariance estimation of non-synchronously observed diffusion processes Bernoulli 11 2 2005 359 379
27. T. Hayashi, and N. Yoshida Asymptotic normality of a covariance estimator for nonsynchronously observed diffusion processes Annals of the Institute of Statistical Mathematics 60 2 2008 357 396
28. J. Jacod, Y. Li, P.A. Mykland, M. Podolskij, and M. Vetter Microstructure noise in the continuous case: the pre-averaging approach Stochastic Processes and their Applications 119 7 2009 2249 2276
29. Q. Liu On portfolio optimization: how and when do we benefit from high-frequency data? Journal of Applied Econometrics 24 4 2009 560 582
30. Martens, M., 2006. Estimating unbiased and precise realized covariances. Manuscript, Erasmus University Rotterdam.
31. R.C. Oomen Properties of realized variance under alternative sampling schemes Journal of Business & Economic Statistics 24 2 2006 219 237
32. Oomen, R.C., 2009. High dimensional covariance forecasting for short intra-day horizons. Quantitative Finance (forthcoming).
33. Podolskij, M., Vetter, M., 2007. Estimation of volatility functionals in the simultaneous presence of microstructure noise and jumps. Bernoulli (forthcoming).
34. M. Scholes, and J. Williams Estimating betas from nonsynchronous data Journal of Financial Economics 5 1977 309 327
35. Sheppard, K., 2005. Realized covariance and scrambling. Manuscript, University of Oxford.
36. V. Voev, and A. Lunde Integrated covariance estimation using high-frequency data in the presence of noise Journal of Financial Econometrics 5 1 2007 68 104
37. L. Zhang Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach Bernoulli 12 6 2006 1019 1043
38. Zhang, L., 2006b. Estimating covariation: epps effect, microstructure noise. Manuscript, Carnegie Mellon University, Department of Statistics.
39. 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 100 472 2005 1394 1411
40. 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
41. B. Zhou High frequency data and volatility in foreign-exchange rates Journal of Business & Economic Statistics 14 1 1996 45 52