correlationMatrix Documentation
correlationMatrix is a Python powered library for the statistical analysis and visualization of correlation phenomena. It can be used to analyze any dataset that captures timestamped values (timeseries) The present use cases focus on typical analysis of market correlations, e.g., via factor models
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
Online documentation for transitionMatrix is currently hosted at readthedocs: