Realized kernels in practice: Trades and quotes

Econometrics Journal

Volumn 12, Issue 3, 2009, Pages

  Barndorff Nielsen, O E ^a   Hansen, P Reinhard ^b   Lunde, A ^c   Shephard, N ^d  

^a AARHUS UNIVERSITY   (Denmark)

^b STANFORD UNIVERSITY   (United States)

^c AARHUS SCHOOL OF BUSINESS   (Denmark)

^d UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

HAC estimator; Long run variance estimator; Market frictions; Quadratic variation; Realized variance

Indexed keywords

EID: 75849145690     PISSN: 13684221     EISSN: 1368423X     Source Type: Journal    
DOI: 10.1111/j.1368-423X.2008.00275.x     Document Type: Article

References (32)

1. Admati, A. R. and P. Pfleiderer (1988a). Selling and trading on information in financial markets. American Economic Review 78, 96-103.
2. Admati, A. R. and P. Pfleiderer (1988b). A theory of intra day patterns: volume and price variability. Review of Financial Studies 1, 3-40.
3. Admati, A. R. and P. Pfleiderer (1989). Divide and conquer: a theory of intraday and day-of-the-week mean effects. Review of Financial Studies 2, 189-223.
4. Andersen, T. G., T. Bollerslev and F. X. Diebold (2008). Parametric and nonparametric measurement of volatility. Forthcoming in Y. Aït-Sahalia and L. P. Hansen (Eds.), Handbook of Financial Econometrics, Amsterdam: North Holland.
5. Andersen, T. G., T. Bollerslev, F. X. Diebold and P. Labys (2000). Great realizations. Risk 13, 105-8.
6. Andersen, T. G., T. Bollerslev, F. X. Diebold and P. Labys (2001). The distribution of exchange rate volatility. Journal of the American Statistical Association 96, 42-55. (Correction (2003) Journal of the American Statistical Association 98, 501).
7. Andrews, D. W. K. (1991). Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59, 817-58.
8. Bandi, F. M. and J. R. Russell (2006a). Comment of Hansen and Lunde (2006). Journal of Business & Economic Statistics 24, 167-73.
9. Bandi, F. M. and J. R. Russell (2006b). Market microstructure noise, integrated variance estimators, and the limitations of asymptotic approximations: a solution. Working paper, Graduate School of Business, University of Chicago.
10. Bandi, F.M. and J. R. Russell (2008).Microstructure noise, realized variance, and optimal sampling. Review of Economic Studies 75, 339-69.
11. Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde and N. Shephard (2006). Subsampling realized kernels. Working paper, Nuffield College, University of Oxford.
12. Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde and N. Shephard (2008a). Designing realized kernels to measure the ex-post variation of equity prices in the presence of noise. Econometrica 76, 1481-536.
13. Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde and N. Shephard (2008b). Multivariate realized kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and nonsynchronous trading. Working paper, Oxford-Man Institute, University of Oxford.
14. Barndorff-Nielsen, O. E. and N. Shephard (2002). Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society, Series B, 64, 253-80.
15. Barndorff-Nielsen, O. E. and N. Shephard (2007). Variation, jumps and high frequency data in financial econometrics. In R. Blundell, T. Persson and W. K. Newey (Eds.), Advances in Economics and Econometrics. Theory and Applications, Ninth World Congress. Econometric Society Monographs, 328-372. Cambridge: Cambridge University Press.
16. Brownless, C. T. and G. M. Gallo (2006). Financial econometric analysis at ultra-high frequency: Data handling concerns. Computational Statistics & Data Analysis 51, 2232-45.
17. Dacorogna, M. M., R. Gencay, U. A. Müller, R. B. Olsen and O. V. Pictet (2001). An Introduction to High-Frequency Finance. San Diego: Academic Press.
18. Diebold, F. and G. Strasser (2007). On the correlation structure of microstructure noise in theory and practice. Working paper, Department of Economics, University of Pennsylvania.
19. Falkenberry, T. N. (2001). High frequency data filtering. Technical report, Tick Data.
20. Fan, J. and Y. Wang (2007). Multi-scale jump and volatility analysis for high-frequency financial data. Journal of the American Statistical Association 102, 1349-62.
21. Hansen, P. R. and A. Lunde (2006). Realized variance and market microstructure noise (with discussion). Journal of Business and Economic Statistics 24, 127-218.
22. Hasbrouck, J. (2007). Empirical Market Microstructure: Economic and Statistical Perspectives on the Dynamics of Trade in Securities Markets. New York: Oxford University Press.
23. Jacod, J., Y. Li, P. A. Mykland, M. Podolskij and M. Vetter (2007). Microstructure noise in the continuous case: the pre-averaging approach. Working paper, Department of Statistics, University of Chicago.
24. Kalnina, I. and O. Linton (2008). Estimating quadratic variation consistently in the presence of correlated measurement error. Forthcoming in Journal of Econometrics.
25. Kyle, A. S. (1985, November). Continuous auctions and insider trading. Econometrica 53, 1315-35.
26. Li, Y. and P. Mykland (2007). Are volatility estimators robust to modelling assumptions? Bernoulli 13, 601-22.
27. Newey, W. K. and K. D. West (1987). A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55, 703-8.
28. O'Hara, M. (1995). Market Microstructure Theory. Cambridge: Blackwell.
29. Shephard, N. (2005). Stochastic Volatility: Selected Readings. Oxford: Oxford University Press.
30. Zhang, L. (2006). Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach. Bernoulli 12, 1019-43.
31. Zhang, L., P. A. Mykland and Y. Aït-Sahalia (2005). A tale of two time scales: determining integrated volatility with noisy high-frequency data. Journal of the American Statistical Association 100, 1394-1411.
32. Zhou, B. (1996). High-frequency data and volatility in foreign-exchange rates. Journal of Business and Economic Statistics 14, 45-52.