Functional GARCH models: the quasi-likelihood approach and its applications

DOI10.1016/j.jeconom.2019.01.006zbMath1452.62988OpenAlexW2784589309WikidataQ128496800 ScholiaQ128496800MaRDI QIDQ1740298

Clément Cerovecki, Siegfried Hörmann, Christian Francq, Jean-Michel Zakoian

Publication date: 30 April 2019

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://mpra.ub.uni-muenchen.de/83990/1/MPRA_paper_83990.pdf

zbMATH Keywords

functional time seriesfunctional QMLEhigh-frequency volatility modelsintraday returnsstationarity of functional GARCH

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Functional data analysis (62R10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items

White noise testing for functional time series ⋮ Testing serial independence with functional data ⋮ Functional ARCH and GARCH models: a Yule-Walker approach ⋮ Tests for conditional heteroscedasticity of functional data ⋮ Change point analysis of covariance functions: a weighted cumulative sum approach ⋮ State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data

Uses Software

• fda (R)

Cites Work

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