Parametric and nonparametric models and methods in financial econometrics

Research output: Contribution to journalReview article

1 Citation (Scopus)

Abstract

Financial 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.

Original languageEnglish (US)
Pages (from-to)1-42
Number of pages42
JournalStatistics Surveys
Volume1
DOIs
StatePublished - Dec 1 2007

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Nonparametric Methods
Nonparametric Model
Parametric Model
Econometrics
Model Validation
Simultaneous Confidence Bands
Financial Modeling
Generalized Likelihood Ratio Test
Parametric Estimation
Pseudo-likelihood
Model Misspecification
Discrete-time Model
Dependence Structure
Nonparametric Estimation
Likelihood Ratio Test
Continuous Time
Regression
Curve
Nonparametric methods
Nonparametric model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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abstract = "Financial 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.",
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Parametric and nonparametric models and methods in financial econometrics. / Zhao, Zhibiao.

In: Statistics Surveys, Vol. 1, 01.12.2007, p. 1-42.

Research output: Contribution to journalReview article

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