Survey open-source options pricing projects

Table of Contents

This page is a capture in the inbox bucket of the product backlog — a pre-sprint idea, not yet pulled into a sprint as a story.

What

When ORE Studio gets to options pricing screens, evaluate existing open-source projects in this space for reusable techniques, models, or UI patterns rather than designing from scratch. Projects found so far, classified by what they actually provide (pricing models/libraries vs. calculators/visualisation tools):

Pricing libraries / models

  • domokane/FinancePy (Python, ★3064) — broad derivatives-pricing and risk-management library covering fixed-income, equity, FX, and credit derivatives; the most mature/active of the set.
  • dbrojas/optlib (Python, ★1620) — options pricing library, includes a TD Ameritrade API client for live data.
  • attack68/rateslib (Python, ★351) — fixed-income library for bonds, bond futures, IRS/XCS/FX swaps; full curve construction with automatic differentiation and risk sensitivities (delta, cross-gamma). Rates-focused rather than options, but relevant for curve-construction technique.
  • federicomariamassari/willowtree (Python, ★379) — willow tree lattice implementation for derivatives pricing; a specific numerical-method reference.
  • AnthonyBradford/optionmatrix (C++, ★248) — financial derivatives calculator with 171+ pricing models (Black-Scholes, Heston, finite difference, Monte Carlo, Garman-Kohlhagen); C++ codebase, closest language match to ORE Studio.
  • xurendong/derivx (Python, ★21) — core library for exotic/structured derivatives (autocallables, barriers, digitals, vanilla).
  • andleb/derivatives (C++, ★18) — derivatives pricing in modern C++; small but a C++ design reference.

Calculators / visualisation / research tools

  • letianzj/QuantResearch (Jupyter, ★2978) — broad quant research repo: strategies, backtests, some derivatives-pricing notebooks. Research reference rather than a reusable library.
  • YuMan-Tam/deep-hedging (Jupyter, ★164) — deep-hedging demo using machine learning for derivative pricing; ML-approach reference.
  • yzoz/python-option-calculator (Python, ★136) — vanilla European option pricing and visualisation using Black-Scholes in pure Python; simple, readable reference implementation.
  • ViktorIvan8787/options-pricing-toolkit (Python/C++, ★1) — options pricing engine: Monte Carlo, Black-Scholes, Greeks, IV calibration, live vol surface/skew analysis on Apple options; small/early project but demonstrates a live vol-surface UI angle.
  • james-ralph8555/optionsVisualizer (Python, ★19) — visualises how Black-Scholes outputs (price, Greeks) change with respect to other variables, 2D/3D; a UI/visualisation-pattern reference for a pricing screen.

Why

ORE Studio's options pricing screens are future work; surveying prior art now — while it's cheap to do so — avoids re-deriving standard pricing techniques (Black-Scholes, Heston, willow tree, Monte Carlo) and surfaces UI/visualisation patterns (vol surface, Greeks sensitivity plots) worth borrowing from when that work starts.

References

  • See per-project links above.

See also

Emacs 29.3 (Org mode 9.6.15)