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Open AccessJournal ArticleDOI

The econometrics of ultra-high-frequency data

Robert F. Engle
- 01 Jan 2000 - 
- Vol. 68, Iss: 1, pp 1-22
TLDR
In this article, the ACD point process was applied to IBM transaction arrival times to develop semiparametric hazard estimates and conditional intensities, and combined with a GARCH model of prices produces ultra-high-frequency measures of volatility.
Abstract
Ultra-high-frequency data is defined to be a full record of transactions and their associated characteristics. The transaction arrival times and accompanying measures can be analyzed as marked point processes. The ACD point process developed by Engle and Russell (1998) is applied to IBM transactions arrival times to develop semiparametric hazard estimates and conditional intensities. Combining these intensities with a GARCH model of prices produces ultra-high-frequency measures of volatility. Both returns and variances are found to be negatively influenced by long durations as suggested by asymmetric information models of market micro-structure.

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MIDAS regressions: Further results and new directions

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Microstructure Noise in the Continuous Case: The Pre-Averaging Approach ∗

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Risk and Volatility: Econometric Models and Financial Practice

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References
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