Time Series Factor Models for Asset Returns
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 22 (1 internal)includes a package overview page
- Examples that run
- 100%17 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 99%
- Return-value docs
- 100%
- Help pages citing references
- 45%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
Forks over time
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/robustport/facmodts on 2026-10-18.
Dependencies
Installing facmodTS adds 40 packages (24 with compiled code, 25 MB of source tarballs). Heaviest: data.table 5.7 MB, PerformanceAnalytics 5.0 MB, robustbase 2.2 MB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0Latest2023-11-09 · current release
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-11-09
- Total releases
- 1 / 3 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5
- Download size
- 60 KB
Cite
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