https://github.com/open-risk/transitionmatrix

Statistical analysis and visualization of state transition phenomena
https://github.com/open-risk/transitionmatrix

credit-rating credit-risk credit-scoring hacktoberfest markov-chain python rating-migration state-space transition-matrix

Last synced: 3 months ago
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Statistical analysis and visualization of state transition phenomena

• Host: GitHub
• URL: https://github.com/open-risk/transitionmatrix
• Owner: open-risk
• License: apache-2.0
• Created: 2017-11-11T17:25:08.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2024-09-30T17:24:19.000Z (10 months ago)
• Last Synced: 2024-10-14T01:44:17.048Z (9 months ago)
• Topics: credit-rating, credit-risk, credit-scoring, hacktoberfest, markov-chain, python, rating-migration, state-space, transition-matrix
• Language: Python
• Homepage: https://www.openriskmanagement.com/tags/transition-matrix/
• Size: 5.72 MB
• Stars: 83
• Watchers: 3
• Forks: 32
• Open Issues: 14
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.rst
  • Funding: .github/FUNDING.yml
  • License: LICENSE.txt

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README

        
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Intro

=========================

transitionMatrix is a Python powered library for the statistical analysis and visualization of state transition phenomena. It can be used to analyze any dataset that captures timestamped transitions in a discrete state space. Use cases include credit rating transitions, system state event logs etc. 

You can use transitionMatrix to

- Estimate transition matrices from historical event data using a variety of estimators

- Manipulate transition matrices (generators, comparisons etc.)

- Visualize event data and transition matrices

- Provide standardized data sets for testing

- Model transitions using threshold processes

- Map credit ratings using mapping tables between popularly used rating systems 

Key Information

================

* Author: [Open Risk](http://www.openriskmanagement.com)

* License: Apache 2.0

* Code Documentation: [Read The Docs](https://transitionmatrix.readthedocs.io/en/latest/index.html)

* Mathematical Documentation: [Open Risk Manual](https://www.openriskmanual.org/wiki/Transition_Matrix)

* Development website: [Github](https://github.com/open-risk/transitionMatrix)

* Project Chat: [Open Risk Commons](https://www.openriskcommons.org/c/open-source/transitionmatrix/15)

**NB: transitionMatrix is still in active development. If you encounter issues or have suggestions please raise them in our github repository or come discuss at our discourse server**

Support and Training

=========================

* The Open Risk Academy has free courses demonstrating the use of the library. The current list is: 

    * [Analysis of Credit Migration using Python TransitionMatrix](https://www.openriskacademy.com/course/view.php?id=38)

* Support for transitionMatrix and other open source libraries developed by [Open Risk](https://www.openriskmanagement.com) is available upon request

Examples

========

The [code documentation](https://transitionmatrix.readthedocs.io/en/latest/index.html) includes a large number of examples, jupyter notebooks and more. 

Plotting individual transition trajectories

![single entity](examples/single_entity.png)

Sampling transition data

![sampled histories](examples/sampled_histories.png)

Estimation of transition matrices using cohort methods

![estimation](examples/estimation.png)

Estimation of transition matrices using duration methods

![transition probabilities](examples/transition_probabilities.png)

Visualization of a transition matrix

![transition matrix](examples/TransitionMatrix.png)

Visualization using a Logarithmic Sankey diagram

![logarithmic sankey](examples/sankey.png)

Generating stochastic process transition thresholds

![thresholds](../portfolioAnalytics/examples/Thresholds.png)

Stressing Transition Matrices

![stressing transition matrices](../portfolioAnalytics/examples/stressed_density.png)

Computation and Visualization of Credit Curves

![credit curves](examples/credit_curves.png)

Working with credit states

![image](examples/scale_conversions.png)