Parametric and nonparametric models and methods in financial econometrics

dc.creatorZhao, Zhibiao
dc.date2008-01-10
dc.date2008-03-20
dc.date.accessioned2026-07-07T12:05:36Z
dc.date.available2026-07-07T12:05:36Z
dc.descriptionFinancial econometrics has become an increasingly popular research field. In this paper we review a few parametric and nonparametric models and methods used in this area. After introducing several widely used continuous-time and discrete-time models, we study in detail dependence structures of discrete samples, including Markovian property, hidden Markovian structure, contaminated observations, and random samples. We then discuss several popular parametric and nonparametric estimation methods. To avoid model mis-specification, model validation plays a key role in financial modeling. We discuss several model validation techniques, including pseudo-likelihood ratio test, nonparametric curve regression based test, residuals based test, generalized likelihood ratio test, simultaneous confidence band construction, and density based test. Finally, we briefly touch on tools for studying large sample properties.
dc.descriptionPublished in at http://dx.doi.org/10.1214/08-SS034 the Statistics Surveys (http://www.i-journals.org/ss/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0801.1599
dc.identifierhttp://arxiv.org/abs/0801.1599
dc.identifierStatistics Surveys 2008, Vol. 2, 1-42
dc.identifierdoi:10.1214/08-SS034
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/208419
dc.subjectStatistical Finance
dc.subjectMethodology
dc.titleParametric and nonparametric models and methods in financial econometrics
dc.typetext

Files

Collections