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Implements the three parallel forecast combinations of Markov Switching GARCH and extreme learning machine model along with the selection of appropriate model for volatility forecasting. For method details see Hsiao C, Wan SK (2014). <doi:10.1016/j.jeconom.2013.11.003>, Hansen BE (2007). <doi:10.1111/j.1468-0262.2007.00785.x>, Elliott G, Gargano A, Timmermann A (2013). <doi:10.1016/j.jeconom.2013.04.017>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.6) |
| Imports: | nnfor, MSGARCH, forecast |
| Published: | 2020-10-08 |
| Author: | Rajeev Ranjan Kumar [aut, cre], Girish Kumar Jha [aut, ths, ctb], Neeraj Budhlakoti [ctb] |
| Maintainer: | Rajeev Ranjan Kumar <rrk.uasd at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | MSGARCHelm results |
| Reference manual: | MSGARCHelm.pdf |
| Package source: | MSGARCHelm_0.1.0.tar.gz |
| Windows binaries: | r-devel: MSGARCHelm_0.1.0.zip, r-release: MSGARCHelm_0.1.0.zip, r-oldrel: MSGARCHelm_0.1.0.zip |
| macOS binaries: | r-release (arm64): MSGARCHelm_0.1.0.tgz, r-oldrel (arm64): MSGARCHelm_0.1.0.tgz, r-release (x86_64): MSGARCHelm_0.1.0.tgz, r-oldrel (x86_64): MSGARCHelm_0.1.0.tgz |
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