AbaQuant documentation¶
AbaQuant 1.0.0rc1 is an applied actuarial and quantitative-finance library for Python. It combines pricing models, financial mathematics, market-data facades, credit analytics, portfolio construction, rate curves, visualizations, exportable reports, and provenance-aware result objects.
The documentation is now organized as Sphinx-native reStructuredText rather than Markdown. Pages are grouped by task and domain so the tree can scale without becoming a flat list.
Important
AbaQuant outputs are model-derived estimates. They are not investment advice, credit ratings, trading signals, legal advice, accounting advice, or tax advice.
Documentation map¶
Section |
Purpose |
|---|---|
Installation, first workflows, conventions, units, rates, signs, and return assumptions. |
|
Architecture, stable public imports, and provenance model. |
|
Function-level reference for every source module, including signatures, parameters, returns, methods, and properties. |
|
Derivatives, financial math, portfolio, credit, market data, rates, visualization, reports, and assumptions. |
|
Example gallery and workflow selection guide. |
|
Validation workflow, release checklist, and v1.0.0rc1 release notes. |
Core workflow¶
market data or manual inputs
|
v
models, allocators, rate curves, credit inputs
|
v
analytics, scenario grids, calibration, backtests
|
v
visualizations, reports, dashboards
|
v
provenance metadata for auditability
Getting started
Reference
Complete API reference
Analytical domains
Operations