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The econometrics of ultra-high-frequency data

Robert F. Engle
- 01 Jan 2000 - 
- Vol. 68, Iss: 1, pp 1-22
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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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Time and the Process of Security Price Adjustment

David Easley, +1 more
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TL;DR: In this paper, a necessary and sufficient condition for the consistency if the pseudo maximum likelihood estimation of the first and second moments is given is given, and the existence of a lower bound for the asymptotic covariance matrix is shown.
Journal ArticleDOI

Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects

TL;DR: In this paper, the authors provide empirical support for the notion that autoregressive conditional heterogeneousness (ARCH) in daily stock return data reflects time dependence in the process generating information flow to the market.
Journal ArticleDOI

A transaction data study of weekly and intradaily patterns in stock returns

TL;DR: In this paper, the authors examined weekly and intradaily patterns in common stock prices using transaction data and found that negative Monday close-to-close returns accrue between the Friday close and the Monday open; for smaller firms they accrue primarily during the Monday trading day.
Journal ArticleDOI

Pseudo Maximum Likelihood Methods: Applications to Poisson Models

TL;DR: In this paper, pseudo maximum likelihood techniques are applied to basic Poisson models and to poisson models with specification errors without specifying the p.d.f. of the disturbances.
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