Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown

DOI10.1016/j.csda.2015.12.005zbMath1466.62199OpenAlexW1921705024MaRDI QIDQ1659146

Steffen Grønneberg, Alvaro Escribano, Genaro Sucarrat

Publication date: 15 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10016/25169

zbMATH Keywords

volatilityARMA-Xlog-GARCH-Xmultivariate log-GARCH-XVARMA-X

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)

Related Items (7)

Inference and model selection in general causal time series with exogenous covariates ⋮ An equation-by-equation estimator of a multivariate log-GARCH-X model of financial returns ⋮ Testing for local covariate trend effects in volatility models ⋮ Goodness-of-fit tests for Log-GARCH and EGARCH models ⋮ On partial-sum processes of ARMAX residuals ⋮ Estimation of multivariate asymmetric power GARCH models ⋮ STATISTICAL INFERENCE FOR MEASUREMENT EQUATION SELECTION IN THE LOG-REALGARCH MODEL

Uses Software

• R
• AutoSEARCH
• gets
• lgarch

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