The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Realized kernels in practice: trades and quotes
Abstract
Realized kernels use high‐frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock and find a remarkable level of agreement. We identify some features of the high‐frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated with high volumes. One explanation for this is that they are due to non‐trivial liquidity effects.
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Cites
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Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
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A Theory of Intraday Patterns: Volume and Price Variability
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Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
Barndorff-Nielsen, O. E., & Shephard, N. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00336 · Cited by 2,215
Self-citationThe Distribution of Realized Exchange Rate Volatility
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501750332965 · Cited by 2,104
A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data
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A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data
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Cited by
Exploiting the errors: A simple approach for improved volatility forecasting
Bollerslev, T., Patton, A. J., & Quaedvlieg, R. (2016) · Journal of Econometrics · doi:10.1016/j.jeconom.2015.10.007 · Cited by 444
Bollerslev, T., Li, S. Z., & Todorov, V. (2016) · Journal of Financial Economics · doi:10.1016/j.jfineco.2016.02.001 · Cited by 180
Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?
Feng, Y., Zhang, Y., & Wang, Y. (2024) · Journal of Forecasting · doi:10.1002/for.3046 · Cited by 22
Metadata
- Authors
- Barndorff‐Nielsen, O. E., Hansen, P. R., Lunde, A., & Shephard, N.
- Venue
- The Econometrics Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-11-01
- Volume
- 12
- Issue
- 3
- Pages
- C1-C32
- ISSN
- 1368-4221 (ISSN-L)
- 1368-423X
- OpenAlex
- W3121532596
- Cited by
- 640
- References
- 16
- FWCI
- 44.26
- Type
- journal article
- Language
- en
- Open access
- closed
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