Skip to main content

A package to simulate autocorrelated time series of signs

Project description

tradeflow : generate autocorrelated time series of signs

tradeflow lets you generate autocorrelated time series of signs.

Installation

pip install tradeflow

How to use

You can create an autoregressive model from a training time series of signs time_series_signs:

>>> import tradeflow
>>>
>>> ar_model = tradeflow.AR(signs=time_series_signs, max_order=50, order_selection_method='pacf', information_criterion=None)

To fit the model parameters, you have to call the fit function:

>>> ar_model.fit(method='yule_walker')

You can then easily simulate an autocorrelated time series of signs by calling the simulate function:

>>> simulated_signs = ar_model.simulate(size=15, seed=1)
>>> print(simulated_signs)

Documentation

Read the full documentation here.

License

Copyright (c) 2024 Martin Gangand

Distributed under the terms of the MIT license.

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

tradeflow-0.0.7.tar.gz (14.7 kB view details)

Uploaded Source

Built Distribution

tradeflow-0.0.7-py3-none-any.whl (18.4 kB view details)

Uploaded Python 3

File details

Details for the file tradeflow-0.0.7.tar.gz.

File metadata

  • Download URL: tradeflow-0.0.7.tar.gz
  • Upload date:
  • Size: 14.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for tradeflow-0.0.7.tar.gz
Algorithm Hash digest
SHA256 e27588f57bc487d6b676eabcdd3cb12ebe9c1b7f8ad06c97f35e9670b8acb1eb
MD5 352bc5b48ec03fbfaa747bda9cd20f81
BLAKE2b-256 1ef5efea3ab40284bd5aea67b80422002f748dee4e7136b5994d4828af9585da

See more details on using hashes here.

File details

Details for the file tradeflow-0.0.7-py3-none-any.whl.

File metadata

  • Download URL: tradeflow-0.0.7-py3-none-any.whl
  • Upload date:
  • Size: 18.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for tradeflow-0.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 31064d339b656dfec58e40676c197a176f5f9a45f2a8372b3391a5b22e6e52d6
MD5 37aefc8b2043ca24e559931cb9db6a73
BLAKE2b-256 9cc1cd22bb1078340faff8a771c3d86bfaca5b017fdaad2c937ca58e88ded20b

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