Realized kernels in practice: trades and quotes

Research output: Research - peer-reviewJournal article

  • Department of Mathematical Sciences
  • School of Economics and Management
  • Department of Marketing and Statistics
  • Econometric Modelling
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.
Original languageEnglish
JournalEconometrics Journal
Volume12
Issue number3
Pages (from-to)C1-C32
Number of pages32
ISSN1368-4221
DOIs
StatePublished - 2009

    Research areas

  • HAC estimator, Long run variance estimator, Market frictions, Quadratic variation, Realized variance

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