ppar

Portfolio performance attribution, contribution, and ex-post risk analytics.

ppar compares a portfolio with a benchmark, explains active return by classification, and produces reviewable HTML tables and PNG charts. It runs locally and supports both Axys/APX exports and a small vendor-neutral CSV format.

Start here

ppar requires Python 3.11.9 or newer.

python -m pip install ppar

# Axys/APX demonstration workspace (the default)
ppar setup ./my_ppar
ppar run ./my_ppar

# Vendor-neutral demonstration workspace
ppar setup ./my_generic_ppar --generic
ppar run ./my_generic_ppar

Both setup commands create a complete runnable workspace:

my_ppar/
  README.md
  ppar.yaml
  input/
  output/

Edit ppar.yaml and replace the demonstration files under input/ with your data. Every run writes the complete result atomically to output/; a failed run leaves the previous successful output intact.

What it produces

The standard quarterly workspace writes security and classification attribution tables, attribution and contribution charts, cumulative return charts, heatmaps, and an ex-post risk-statistics table.

Python

from ppar import Analytics
from ppar.attribution import View

analytics = Analytics("portfolio.csv", "benchmark.csv")
overall = analytics.attribution().to_polars(View.OVERALL_ATTRIBUTION)
print(overall)

Public tabular results are Polars DataFrames. HTML, PNG, and CSV output is available from the owning attribution or risk object.

Documentation

• Configuration
• Methodology
• Python API
• Maintenance

License

Downloading, installing, accessing, copying, or using ppar constitutes acceptance of the license. The public package grants a time-limited internal evaluation license; production and other commercial use require a separate written agreement.