mfGARCH: Mixed-Frequency GARCH Models
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 + fileLICENSE |
| URL: | https://github.com/onnokleen/mfGARCH/ |
| NeedsCompilation: | yes |
| Citation: | mfGARCH citation info |
| Materials: | NEWS |
| CRAN checks: | mfGARCH results |
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