Estimating GARCH-MIDAS (MIxed-DAta-Sampling) models (Engle, Ghysels, Sohn, 2013, <doi:10.1162/REST_a_00300>) and related statistical inference, accompanying the paper "Two are better than one: Volatility forecasting using multiplicative component GARCH models" by Conrad and Kleen (2020, <doi:10.1002/jae.2742>). The GARCH-MIDAS model decomposes the conditional variance of (daily) stock returns into a short- and long-term component, where the latter may depend on an exogenous covariate sampled at a lower frequency.
Version: 0.2.1 Depends: R (≥ 3.3.0) Imports: Rcpp, graphics, stats, numDeriv, zoo, maxLik LinkingTo: Rcpp Suggests: testthat, dplyr, ggplot2, covr, rmarkdown Published: 2021-06-17 DOI: 10.32614/CRAN.package.mfGARCH Author: Onno Kleen [aut, cre] Maintainer: Onno Kleen <r at onnokleen.de> BugReports: https://github.com/onnokleen/mfGARCH/issues License: MIT + file LICENSE URL: https://github.com/onnokleen/mfGARCH/ NeedsCompilation: yes Citation: mfGARCH citation info Materials: NEWS CRAN checks: mfGARCH results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=mfGARCH to link to this page.
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