Publication: The econometrics of randomly spaced financial data: a survey
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2009-12
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Abstract
This paper provides an introduction to the problem of modeling randomly spaced
longitudinal data. Although Point Process theory was developed mostly in the sixties
and early seventies, only in the nineties did this field of Probability theory attract the
attention of researchers working in Financial Econometrics. The large increase,
observed since, in the number of different classes of Econometric models for dealing
with financial duration data, has been mostly due to the increased availability of both
trade-by-trade data from equity markets and daily default and rating migration data from
credit markets. This paper provides an overview of the main Econometric models
available in the literature for dealing with what is sometimes called tick data.
Additionally, a synthesis of the basic theory underlying these models is also presented.
Finally, a new theorem dealing with the identifiability of latent intensity factors from
point process data, jointly with a heuristic proof, is introduced.
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Tick data, Financial duration models, Point processes, Migration models