Derivus

An xVA quantitative library written in pure python using pytorch, with adjoint algorithmic differentiation throughout.

A job is a JSON program: market data, deals and a calculation block go in, results come out. The engine compiles the job — factor discovery, dependency ordering, process construction — then executes it against Monte-Carlo scenarios. Sensitivities come from AAD rather than bumping, so a full greek vector costs one backward pass however many factors it covers.

Installation

pip install derivus

Requires python >= 3.8 and pytorch >= 2.0. A GPU build of pytorch is strongly recommended — the scenario engine is written for it.

Optional extras:

pip install "derivus[garch]"        # GARCHSpotModel calibration (lazy import; the rest runs without it)
pip install "derivus[interactive]"  # jupyter and matplotlib
pip install "derivus[docs]"         # the mkdocs toolchain DV_Docs generates config for

To work on Derivus itself, install from a clone instead:

pip install -e .

Usage

import derivus as dv

cx = dv.Context()
cx.load_json('job.json')
calc, results = cx.run_job()

The JSON is the whole contract — every feature is reachable from it, and a user script should never need to import derivus internals. Three console scripts are installed:

Layout

Scripts under experiments/ are run from the repo root, e.g. python experiments/production_solver.py.

Market data

No market data ships with the source. Exchange settlements, open interest and curve history are licensed by their providers and are not ours to redistribute, so data/ is gitignored and you supply your own.

The suite needs nothing from you. Its inputs live in tests/fixtures/ and are calibrated parameters — HMM transition matrices, VAR coefficients, GARCH fits — because a fitted statistic is not the series it was fitted to. A fresh clone runs the whole suite green, with two calibration tests skipping and naming the file they want.

To run those two, put a CSV at data/pl_exp.csv with a date index and a CommodityPrice.PLATINUM column. tests/fixtures/calibration_config.json shows the wider shape the calibration scripts expect.

Documentation

Build it locally with DV_Docs, or read the sources under docs_src/. The developer section (docs_src/developer/) is the internal view: architecture, the calculation lifecycle, the dependency system, the resolver layer and the house conventions.

Licence

PolyForm Noncommercial License 1.0.0 — free for any noncommercial purpose, including research, teaching and personal projects. Commercial use requires a separate licence.

Derivus continues work previously published as RiskFlow under GPL-3.0. Anyone who received that release keeps their rights under those terms; this repository is licensed separately by the same copyright holder.