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The Exact Discretisation of CARMA Models with Applications in Finance

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Publication details

JournalJournal of empirical finance
DateAccepted/In press - 18 Mar 2016
DateE-pub ahead of print - 31 Mar 2016
DatePublished (current) - Sep 2016
Issue numberB
Number of pages41
Pages (from-to)739 - 761
Early online date31/03/16
Original languageEnglish


The problem of estimating a continuous time model using discretely observed data is common in empirical finance.
This paper uses recently developed methods of deriving the exact discrete representation for a continuous time ARMA (autoregressive moving
average) system of order p, q to consider three popular models in finance.
Our results for two benchmark term structure models show that higher order ARMA processes provide a significantly better fit than standard
Ornstein-Uhlenbeck processes.
We then explore present value models linking stock prices and dividends in the presence of cointegration.
Our methods enable us to take account of the fact that the two variables are observed in fundamentally different ways by explicitly
modelling the data as mixed stock-flow type, which we then compare with the (more common, but incorrect) treatment of dividends as a
stock variable.

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© 2016 Elsevier B.V. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. Embargo period: 18 months

    Research areas

  • Continuous time ARMA process; discrete time representation; present value; term structure.

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