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The Econometrics of Ultra-High Frequency Data

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Robert F. Engle

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Abstract

Ultra-high frequency data are complete transactions data which inherently arrive at random times. Marked point processes provide a theoretical framework for analysis of such data sets. The ACD model developed by Engle and Russell (1995) is then applied to IBM transactions data to develop semi-parametric hazard estimates and measures of instantaneous conditional variances. The variances are negatively influenced by surprisingly long durations as suggested by some of the market micro-structure literature

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 5816.

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Date of creation: Nov 1996
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Handle: RePEc:nbr:nberwo:5816

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  1. Shephard, Neil, 1993. "Fitting Nonlinear Time-Series Models with Applications to Stochastic Variance Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S135-52, Suppl. De. [Downloadable!] (restricted)
  2. Eric Ghysels & Christian Gouriéroux & Joanna Jasiak, 1995. "Trading Patterns, Time Deformation and Stochastic Volatility in Foreign Exchange Markets," CIRANO Working Papers 95s-42, CIRANO. [Downloadable!]
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