Skip to main content

Estimate factors off of the FRED-MD dataset

Project description

FredMD

Build

This package downloads the FRED-MD dataset and estimates common factors. It also implements the Bai-Ng (2002) factor selection information critrea. The alogrithms in this package are adapted from the matlab programs provided on the FRED-MD web page.

Installation

This package can be installed via pip.

Useage

from FredMD import FredMD

fmd = FredMD(Nfactor=None, vintage=None, maxfactor=8, standard_method=2, ic_method=2)
fmd.estimate_factors()
f = fmd.factors

References

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

FredMD-0.0.6.tar.gz (5.5 kB view details)

Uploaded Source

Built Distribution

FredMD-0.0.6-py3-none-any.whl (7.0 kB view details)

Uploaded Python 3

File details

Details for the file FredMD-0.0.6.tar.gz.

File metadata

  • Download URL: FredMD-0.0.6.tar.gz
  • Upload date:
  • Size: 5.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for FredMD-0.0.6.tar.gz
Algorithm Hash digest
SHA256 20344eab0223939ecaa5baa659e564c46d30a20d2311ab98338ab61fc25e8dec
MD5 2bf8968d434d361c574317a09d29fc25
BLAKE2b-256 9003082a53d2d429b5e773dffd38e00812746de00526b02454d473cd5d55d96e

See more details on using hashes here.

File details

Details for the file FredMD-0.0.6-py3-none-any.whl.

File metadata

  • Download URL: FredMD-0.0.6-py3-none-any.whl
  • Upload date:
  • Size: 7.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for FredMD-0.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 b816fc4dbeeaabba5073369e972d65501c191c48880eccc8edb77418aacbad85
MD5 1d5c5069be48d39b72ce7489facacb77
BLAKE2b-256 ac3015f88f75c124b64e174653e14e2be267699e907222f7ed05b6423a7f895a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page