FinCovRegularization
1.1.0Covariance Matrix Estimation and Regularization for Finance
Overview
Estimation and regularization for covariance matrix of asset returns. For covariance matrix estimation, three major types of factor models are included: macroeconomic factor model, fundamental factor model and statistical factor model. For covariance matrix regularization, four regularized estimators are included: banding, tapering, hard-thresholding and soft- thresholding. The tuning parameters of these regularized estimators are selected via cross-validation.
Install
Health
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 38%
Downloads
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Checks run against github.com/yanyachen/fincovregularization on 2026-07-31.
Dependencies
Code & Tests
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 1.1.0Latest
- RR 3.2.0 released · 2015-04-16
- 1.0.02015-03-01
- RR 3.1.0 released · 2014-04-10
Package metadata
- First published
- 2015-03-01
- Total releases
- 2 / 11 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 13 KB / 1 file
- Download size
- 25 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet