# Quantlib Python

> QuantLib Python bindings for quantitative finance. Pricing and risk analytics for fixed income, equity, FX, credit derivatives, and structured products. Yield curves, options, swaps, bonds, and Monte Carlo simulation.

- Skill: `mkurman/quantlib-python` (Agent Skill)
- Install (CLI): `npx skillmds@latest add mkurman/quantlib-python`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mkurman/quantlib-python/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: mkurman (https://skillmd.com/u/mkurman)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/mkurman/quantlib-python

---

## Overview

QuantLib Python provides pricing and risk analytics for fixed income, equity, FX, and credit derivatives. Covers yield curves, options, swaps, bonds, caps/floors, swaptions, and structured products. The standard open-source quantitative finance library used by banks, hedge funds, and fintech.

## Installation

```bash
uv pip install QuantLib-Python
```

## Bond Pricing

```python
import QuantLib as ql

ql.Settings.instance().evaluationDate = ql.Date(15, 6, 2024)
schedule = ql.Schedule(
    ql.Date(15, 6, 2023), ql.Date(15, 6, 2028),
    ql.Period(ql.Semiannual),
    ql.UnitedStates(ql.UnitedStates.GovernmentBond),
    ql.Unadjusted, ql.Unadjusted,
    ql.DateGeneration.Backward, False)
bond = ql.FixedRateBond(2, 100.0, schedule, [0.05], ql.ActualActual())
ytm = bond.bondYield(95.0, ql.ActualActual(), ql.Compounded, ql.Semiannual)
print(f"YTM: {ytm:.4%}")
```

## References
- [QuantLib docs](https://www.quantlib.org/)
- [QuantLib-Python](https://quantlib-python-docs.readthedocs.io/)