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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