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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.
Passed 19 of 22 test cases with the skill, and 16 of 22 without it.
3 fixed16 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
What is the recommended package name and command when installing QuantLib with uv in Python?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends uv pip install QuantLib-Python | Missed | Passed |
The instructions your model reads when the skill loads.
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.
uv pip install QuantLib-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%}")
test cases passed, vs 16 / 22 without
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