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Package: BEKKs 1.4.7

Markus J. Fülle

BEKKs: Multivariate Conditional Volatility Modelling and Forecasting

Methods and tools for estimating, simulating and forecasting of so-called BEKK-models (named after Baba, Engle, Kraft and Kroner) based on the fast Berndt–Hall–Hall–Hausman (BHHH) algorithm described in Hafner and Herwartz (2008) <doi:10.1007/s00184-007-0130-y>. For an overview, we refer the reader to Fülle et al. (2024) <doi:10.18637/jss.v111.i04>.

Authors:Markus J. Fülle [aut, cre], Alexander Lange [aut], Christian M. Hafner [aut], Helmut Herwartz [aut]

BEKKs_1.4.7.tar.gz
BEKKs_1.4.7.zip(r-4.7-x86_64)BEKKs_1.4.7.zip(r-4.7-arm64)BEKKs_1.4.7.zip(r-4.6-x86_64)BEKKs_1.4.7.zip(r-4.6-arm64)
BEKKs_1.4.7.tar.gz(r-4.7-arm64)BEKKs_1.4.7.tar.gz(r-4.7-x86_64)BEKKs_1.4.7.tar.gz(r-4.6-arm64)BEKKs_1.4.7.tar.gz(r-4.6-x86_64)
BEKKs_1.4.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BEKKs/json (API)

# Install 'BEKKs' in R:

install.packages('BEKKs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

GoldStocksBonds - Gold stock and Bond returns
StocksBonds - Daily stock and Bond returns

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas cpp openmp

1.60 score 1 stars 20 scripts 691 downloads 6 exports 63 dependencies

Last updated from:01b20c6761. Checks:8 OK, 2 ERROR. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	260
linux-devel-x86_64	OK	290
source / vignettes	OK	284
linux-release-arm64	OK	262
linux-release-x86_64	OK	307
windows-devel-arm64	ERROR	267
windows-devel-x86_64	OK	241
windows-release-arm64	ERROR	309
windows-release-x86_64	OK	313
wasm-release	OK	123

Exports:backtest bekk_fit bekk_spec portmanteau.test VaR virf

Dependencies:cli codetools cpp11 digest dplyr farver FNN future future.apply generics ggfortify ggplot2 globals glue gmp gridExtra gtable isoband kernlab KernSmooth ks labeling lattice lifecycle listenv lubridate magrittr mathjaxr Matrix mclust mgcv moments multicool mvtnorm nlme numDeriv parallelly pbapply pillar pkgconfig plyr pracma purrr R6 RColorBrewer Rcpp RcppArmadillo reshape2 rlang S7 scales stringi stringr tibble tidyr tidyselect timechange utf8 vctrs viridisLite withr xts zoo

Help page	Topics
Backtesting via Value-at-Risk (VaR)	backtest
Estimating multivariate BEKK-type volatility models	bekk_fit
BEKK specification method	bekk_spec
BEKKs: Volatility modelling	BEKKs
Gold stock and Bond returns	GoldStocksBonds
Performing a Portmanteau test checking for remaining correlation in the empirical co-variances of the estimated BEKK residuals.	portmanteau.test
Forecasting conditional volatilities with BEKK models	predict predict.bekk predict.bekka predict.dbekk predict.dbekka predict.sbekk predict.sbekka
bekkFit method	logLik.bekkFit print.bekkFit residuals.bekkFit
Simulating BEKK models	simulate simulate.bekk simulate.bekka simulate.dbekk simulate.dbekka simulate.sbekk simulate.sbekka
Daily stock and Bond returns	StocksBonds
Calculating Value-at-Risk (VaR)	VaR
Estimating multivariate volatility impulse response functions (VIRF) for BEKK models	virf

Package: BEKKs 1.4.7

BEKKs: Multivariate Conditional Volatility Modelling and Forecasting

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)