Expansion and estimation of Lévy process functionals in nonlinear and nonstationary time series regression

Chaohua Dong, Jiti Gao

Research output: Contribution to journalArticleResearchpeer-review

Abstract

In this article, we develop a series estimation method for unknown time-inhomogeneous functionals of Lévy processes involved in econometric time series models. To obtain an asymptotic distribution for the proposed estimators, we establish a general asymptotic theory for partial sums of bivariate functionals of time and nonstationary variables. These results show that the proposed estimators in different situations converge to quite different random variables. In addition, the rates of convergence depend on various factors rather than just the sample size. Finite sample simulations are provided to evaluate the finite sample performance of the proposed model and estimation method.

Original languageEnglish
Pages (from-to)125-150
Number of pages26
JournalEconometric Reviews
Volume38
Issue number2
DOIs
Publication statusPublished - 2019

Keywords

  • Asymptotic theory
  • Lévy process
  • orthogonal series expansion
  • series estimation
  • time-inhomogeneous functional

Cite this

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title = "Expansion and estimation of L{\'e}vy process functionals in nonlinear and nonstationary time series regression",
abstract = "In this article, we develop a series estimation method for unknown time-inhomogeneous functionals of L{\'e}vy processes involved in econometric time series models. To obtain an asymptotic distribution for the proposed estimators, we establish a general asymptotic theory for partial sums of bivariate functionals of time and nonstationary variables. These results show that the proposed estimators in different situations converge to quite different random variables. In addition, the rates of convergence depend on various factors rather than just the sample size. Finite sample simulations are provided to evaluate the finite sample performance of the proposed model and estimation method.",
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Expansion and estimation of Lévy process functionals in nonlinear and nonstationary time series regression. / Dong, Chaohua; Gao, Jiti.

In: Econometric Reviews, Vol. 38, No. 2, 2019, p. 125-150.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Expansion and estimation of Lévy process functionals in nonlinear and nonstationary time series regression

AU - Dong, Chaohua

AU - Gao, Jiti

PY - 2019

Y1 - 2019

N2 - In this article, we develop a series estimation method for unknown time-inhomogeneous functionals of Lévy processes involved in econometric time series models. To obtain an asymptotic distribution for the proposed estimators, we establish a general asymptotic theory for partial sums of bivariate functionals of time and nonstationary variables. These results show that the proposed estimators in different situations converge to quite different random variables. In addition, the rates of convergence depend on various factors rather than just the sample size. Finite sample simulations are provided to evaluate the finite sample performance of the proposed model and estimation method.

AB - In this article, we develop a series estimation method for unknown time-inhomogeneous functionals of Lévy processes involved in econometric time series models. To obtain an asymptotic distribution for the proposed estimators, we establish a general asymptotic theory for partial sums of bivariate functionals of time and nonstationary variables. These results show that the proposed estimators in different situations converge to quite different random variables. In addition, the rates of convergence depend on various factors rather than just the sample size. Finite sample simulations are provided to evaluate the finite sample performance of the proposed model and estimation method.

KW - Asymptotic theory

KW - Lévy process

KW - orthogonal series expansion

KW - series estimation

KW - time-inhomogeneous functional

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DO - 10.1080/07474938.2016.1235305

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