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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 + file LICENSE |
| URL: |
https://github.com/onnokleen/mfGARCH/ |
| NeedsCompilation: |
yes |
| Citation: |
mfGARCH citation info |
| Materials: |
NEWS |
| CRAN checks: |
mfGARCH results |
Documentation:
Downloads:
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https://CRAN.R-project.org/package=mfGARCH
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.