A nonparametric ACD model

We carry out a nonparametric analysis of financial durations. We make use of an existing algorithm to describe nonparametrically the dynamics of the process in terms of its lagged realizations and of a latent variable, its conditional mean. The devices needed to effectively apply the algorithm to our dataset are presented. On simulated data, the nonparametric procedure yields better estimates than the ones delivered by an incorrectly specified parametric method. On a real dataset, the nonparametric analysis can convey information on the nature of the data generating process that may not be captured by the parametric specification. In this view, the nonparametric method proposed can be a valuable preliminary analysis able to suggest the choice of a 'good' parametric specification, or a complement of a parametric estimation."

• Publication year

  2006

• Venue

  Financial Mathematics, Volatility and Covariance Modelling

• Publication date

  2006-08-01

• Fields of study

  Mathematics, Business, Economics, Computer Science

• Identifiers
  DOI 10.2139/SSRN.944419
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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