Separating microstructure noise from volatility

Journal of Financial Economics

Volumn 79, Issue 3, 2006, Pages 655-692

  Bandi, Federico M ^a   Russell, Jeffrey R ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

High frequency data; Microstructure noise; Volatility; Volatility timing

Indexed keywords

EID: 32544460708     PISSN: 0304405X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfineco.2005.01.005     Document Type: Article

References (49)

1. Y. Aït-Sahalia P. Mykland L. Zhang How often to sample a continuous-time process in the presence of market microstructure noise Review of Financial Studies 18 2005 351-416
2. S. Alizadeh M.W. Brandt F.X. Diebold Range-based estimation of stochastic volatility models Journal of Finance 57 2002 1047-1092
3. T.G. Andersen T. Bollerslev Heterogeneous information arrivals and return volatility dynamics: Uncovering the long-run in high frequency returns Journal of Finance 52 1997 975-1005
4. T.G. Andersen T. Bollerslev Intraday periodicity and volatility persistence in financial markets Journal of Empirical Finance 4 1997 115-158
5. T.G. Andersen T. Bollerslev Deutsche market volatility: Intraday activity patterns, macroeconomic announcements, and longer run dependencies Journal of Finance 53 1998 219-265
6. T.G. Andersen T. Bollerslev F.X. Diebold P. Labys Great realizations Risk Magazine 71 2000 105-108
7. T.G. Andersen T. Bollerslev F.X. Diebold H. Ebens The distribution of realized stock return volatility Journal of Financial Economics 61 2001 43-76
8. Andersen, T.G., Bollerslev, T., Diebold, F.X., 2002. Parametric and nonparametric measurements of volatility. In: Aït-Sahalia, Y., Hansen, L.P. (Eds.), Handbook of Financial Econometrics. North Holland, Amsterdam. Forthcoming.
9. T.G. Andersen T. Bollerslev F.X. Diebold P. Labys Modeling and forecasting realized volatility Econometrica 71 2003 579-625
10. Bai, X., Russell, J.R., Tiao, G., 2004. Effects of non-normality and dependence on the precision of variance estimates using high-frequency data. Unpublished working paper, University of Chicago.
11. R. Baillie T. Bollerslev H.O. Mikkelsen Fractionally integrated generalized autoregressive conditional heteroskedasticity Journal of Econometrics 74 1996 3-30
12. Bandi, F.M., Perron, B., 2004. Long memory and the relation between realized and implied volatility. Unpublished working paper, University of Chicago and University of Montreal.
13. Bandi, F.M., Russell, J.R., 2004. Microstructure noise, realized variance, and optimal sampling. Unpublished working paper, University of Chicago.
14. O.E. Barndorff-Nielsen 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
15. O.E. Barndorff-Nielsen N. Shephard Econometric analysis of realized covariation: High-frequency based covariance, regression and correlation in financial economics Econometrica 72 2004 885-925
16. D.S. Bates Post-'87 crash fears in the S&P 500 futures option market Journal of Econometrics 94 2000 181-238
17. S. Beckers Variance of security price returns based on high, low, and closing prices Journal of Business 56 1983 97-112
18. T. Bollerslev H.O. Mikkelsen Modeling and pricing long-memory in stock market volatility Journal of Econometrics 73 1996 75-99
19. T. Bollerslev H.O. Mikkelsen Long-term equity anticipation securities and stock market volatility dynamics Journal of Econometrics 92 1999 75-99
20. Brandt, M.W., Diebold, F.X., 2004. A no-arbitrage approach to range-based estimation of return covariances and correlations. Journal of Business, forthcoming.
21. M. Chernov A.R. Gallant E. Ghysels G. Tauchen Alternative models for stock price dynamics Journal of Econometrics 116 2003 225-257
22. F. Comte R. Renault Long-memory in continuous-time stochastic volatility models Mathematical Finance 8 1998 291-323
23. Z. Ding C.W.J. Granger R.F. Engle A long memory property of stock returns and a new model Journal of Empirical Finance 1 1993 83-106
24. D. Duffie J. Pan K. Singleton Transform analysis and asset pricing for affine jump-diffusions Econometrica 68 2000 1343-1376
25. D. Easley M. O'Hara Time and the process of security price adjustment Journal of Finance 47 1992 577-606
26. R.F. Engle G.J. Lee A permanent and transitory component model of stock return volatility R.F. Engle H. White Cointegration, Causality, and Forecasting: A Festschriftin Honor of Clive W.J. Granger 1999 Oxford University Press Oxford 475-497
27. B. Eraker M. Johannes N. Polson The impact of jumps in volatility and returns Journal of Finance 58 2003 1269-1300
28. J. Fleming C. Kirby B. Ostdiek The economic value of volatility timing Journal of Finance 56 2001 329-352
29. J. Fleming C. Kirby B. Ostdiek The economic value of volatility timing using "realized volatility" Journal of Financial Economics 67 2003 473-509
30. K.R. French G.W. Schwert R.F. Stambaugh Expected stock returns and volatility Journal of Financial Economics 19 1987 3-29
31. M.B. Garman M.J. Klass On the estimation of price volatility from historical data Journal of Business 53 1980 67-78
32. J. Geweke S. Porter-Hudak The estimation and application of long memory time series models Journal of Time Series Analysis 4 1983 221-238
33. Hansen, P.R., Lunde A., 2004a. An unbiased measure of realized variance. Unpublished working paper, Stanford University and University of Aarhus.
34. Hansen, P.R., Lunde A., 2004b. Realized variance and market microstructure noise. Unpublished working paper, Stanford University and University of Aarhus.
35. C.S. Jones The dynamics of stochastic volatility: Evidence from underlying and options markets Journal of Econometrics 116 2003 181-224
36. A. Madhavan Market microstructure a survey Journal of Financial Markets 3 2000 205-258
37. Meddahi, N., 2001. An eigenfunction approach for volatility modelling, Unpublished working paper. University of Montreal.
38. Ohanissian, A., Russell, J.R., Tsay R., 2004. Using temporal aggregation to distinguish between true and spurious long memory. Unpublished working paper, University of Chicago.
39. Oomen, R., 2004a. Properties of realized variance for pure-jump processes: Calendar time sampling versus business time sampling. Unpublished working paper, Warwick Business School.
40. Oomen, R., 2004b. Properties of bias-corrected realized variance in calendar time and in business time. Unpublished working paper, Warwick Business School.
41. J. Pan The jump-risk premia implicit in options evidence from an integrated time-series study Journal of Financial Economics 63 2002 3-50
42. M. Parkinson The extreme value method for estimating the variance of the rate of return Journal of Business 53 1980 61-65
43. G.W. Schwert Why does stock market volatility change over time? Journal of Finance 44 1989 1115-1153
44. G.W. Schwert Stock market volatility Financial Analysts Journal 46 1990 23-24
45. G.W. Schwert Stock volatility and the crash of '87 Review of Financial Studies 3 1990 77-102
46. G.W. Schwert P.J. Seguin Heteroskedasticity in stock returns Journal of Finance 45 1991 1129-1155
47. H.R. Stoll Friction Journal of Finance 55 2000 1479-1514
48. Zhang, L., Mykland, P., Aït-Sahalia, Y., 2004. A tale of two time scales: Determining integrated volatility with noisy high-frequency data. Journal of the American Statistical Association, forthcoming.
49. B. Zhou High-frequency data and volatility in foreign exchange rates Journal of Business and Economic Statistics 14 1996 45-52