Package: facmodTS 1.0

Doug Martin

facmodTS: Time Series Factor Models for Asset Returns

Supports teaching methods of estimating and testing time series factor models for use in robust portfolio construction and analysis. Unique in providing not only classical least squares, but also modern robust model fitting methods which are not much influenced by outliers. Includes returns and risk decompositions, with user choice of standard deviation, value-at-risk, and expected shortfall risk measures. "Robust Statistics Theory and Methods (with R)", R. A. Maronna, R. D. Martin, V. J. Yohai, M. Salibian-Barrera (2019) <doi:10.1002/9781119214656>.

Authors:Doug Martin [cre, aut], Eric Zivot [aut], Sangeetha Srinivasan [aut], Avinash Acharya [ctb], Yi-An Chen [ctb], Kirk Li [ctb], Lingjie Yi [ctb], Justin Shea [ctb], Mido Shammaa [ctb], Jon Spinney [ctb]

facmodTS_1.0.tar.gz
facmodTS_1.0.zip(r-4.5)facmodTS_1.0.zip(r-4.4)facmodTS_1.0.zip(r-4.3)
facmodTS_1.0.tgz(r-4.4-any)facmodTS_1.0.tgz(r-4.3-any)
facmodTS_1.0.tar.gz(r-4.5-noble)facmodTS_1.0.tar.gz(r-4.4-noble)
facmodTS_1.0.tgz(r-4.4-emscripten)facmodTS_1.0.tgz(r-4.3-emscripten)
facmodTS.pdf |facmodTS.html✨
facmodTS/json (API)

# Install 'facmodTS' in R:
install.packages('facmodTS', repos = c('https://robustport.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/robustport/facmodts/issues

On CRAN:

10 exports 1 stars 1.26 score 46 dependencies 271 downloads

Last updated 9 months agofrom:a1b8d1394e. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 14 2024
R-4.5-winOKSep 14 2024
R-4.5-linuxOKSep 14 2024
R-4.4-winOKSep 14 2024
R-4.4-macOKSep 14 2024
R-4.3-winOKSep 14 2024
R-4.3-macOKSep 14 2024

Exports:fitTsfmfitTsfm.controlfitTsfmLagLeadBetafitTsfmMTfitTsfmUpDnfmCovfmEsDecompfmSdDecompfmVaRDecomppaFm

Dependencies:backportsbootcheckmatecodetoolscorpcordata.tableDEoptimRdigestforeachGenSAiteratorslarslatticeleapsMASSMatrixMatrixModelsmcomnormtmvtnormnumDerivpcaPPPerformanceAnalyticsPortfolioAnalyticspsopyinitquadprogquantregR.cacheR.methodsS3R.ooR.utilsregistryRobStatTMrobustbaseROIROI.plugin.symphonyrrcovRsymphonysandwichslamsnSparseMsurvivalxtszoo

Readme and manuals

Help Manual

Help pageTopics
Fit a time series factor model using time series regressioncoef.tsfm fitted.tsfm fitTsfm residuals.tsfm
List of control parameters for 'fitTsfm'fitTsfm.control
Fit a lagged and lead Betas factor model using time series regressionfitTsfmLagLeadBeta
Fit a market timing time series factor modelfitTsfmMT
Fit a up and down market factor model using time series regressionfitTsfmUpDn
Covariance Matrix for assets' returns from fitted factor model.fmCov fmCov.ffm fmCov.sfm fmCov.tsfm
Decompose ES into individual factor contributionsfmEsDecomp fmEsDecomp.ffm fmEsDecomp.sfm fmEsDecomp.tsfm
Decompose standard deviation into individual factor contributionsfmSdDecomp fmSdDecomp.ffm fmSdDecomp.sfm fmSdDecomp.tsfm
Decompose VaR into individual factor contributionsfmVaRDecomp fmVaRDecomp.ffm fmVaRDecomp.sfm fmVaRDecomp.tsfm
Compute cumulative mean attribution for factor modelspaFm
plot '"pafm"' objectplot.pafm
Plots from a fitted time series factor modelplot.tsfm
Plot actual against fitted values of up and down market time series factor modelplot.tsfmUpDn
Predicts asset returns based on a fitted time series factor modelpredict.tsfm
Predicts asset returns based on a fitted up and down market time series factor modelpredict.tsfmUpDn
Print object of class '"pafm"'.print.pafm
Prints a fitted time series factor modelprint.tsfm
Prints out a fitted up and down market time series factor model objectprint.tsfmUpDn
summary '"pafm"' object.summary.pafm
Summarizing a fitted time series factor modelprint.summary.tsfm summary.tsfm
Summarizing a fitted up and down market time series factor modelprint.summary.tsfmUpDn summary.tsfmUpDn