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Discrete-valued Levy processes and low latency financial econometrics

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  • Ole E. Barndorff-Nielsen

    () (The T.N. Thiele Centre for Mathematics in Natural Science, Department of Mathematical Sciences, University of Aarhus, Ny Munkegade, DK-8000 Aarhus C, Denmark & CREATES, University of Aarhus)

  • David G. Pollard

    () (AHL Research, Man Research Laboratory, Eagle House, Walton Well Road, Oxford OX2 6ED, UK)

  • Neil Shephard

    () (Oxford-Man Institute, University of Oxford, Eagle House, Walton Well Road, Oxford OX2 6ED, UK, & Department of Economics, University of Oxford)

Abstract

Motivated by features of low latency data in finance we study in detail discrete-valued Levy processes as the basis of price processes for high frequency econometrics. An important case of this is a Skellam process, which is the difference of two independent Poisson processes. We propose a natural generalisation which is the difference of two negative binomial processes. We apply these models in practice to low latency data for a variety of different types of futures contracts.

Suggested Citation

  • Ole E. Barndorff-Nielsen & David G. Pollard & Neil Shephard, 2010. "Discrete-valued Levy processes and low latency financial econometrics," Economics Papers 2010-W04, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:1004
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    File URL: http://www.nuffield.ox.ac.uk/economics/papers/2010/w4/skellam180610.pdf
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    Keywords

    futures markets; high frequency econometrics; low latency data; negative binomial; Skellam distribution.;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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