Determination of vector error correction models in high dimensions

DOI10.1016/j.jeconom.2018.09.018zbMath1452.62941OpenAlexW2900300175MaRDI QIDQ1739869

Chong Liang, Melanie Schienle

Publication date: 29 April 2019

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

Full work available at URL: https://publikationen.bibliothek.kit.edu/1000092474

zbMATH Keywords

VECMLassohigh-dimensional time seriescredit default swapcointegration rank and lag selection

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to actuarial sciences and financial mathematics (62P05) Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items

Counterfactual Analysis With Artificial Controls: Inference, High Dimensions, and Nonstationarity ⋮ Automated Estimation of Heavy-Tailed Vector Error Correction Models ⋮ Forecasting vector autoregressions with mixed roots in the vicinity of unity ⋮ Sparse vector error correction models with application to cointegration‐based trading ⋮ Predictive quantile regression with mixed roots and increasing dimensions: the ALQR approach ⋮ Inference in Heavy-Tailed Nonstationary Multivariate Time Series ⋮ An Automated Approach Towards Sparse Single-Equation Cointegration Modelling

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