FinceptQuantLib

Quantitative finance library from Fincept Corporation: pricing, risk and analytics for fixed income, derivatives and portfolios. Pure Python on top of SciPy, typed, and validated against SciPy and closed-form references.

Installation

pip install finceptquantlib

Requires Python 3.11+.

Quick start

from datetime import date
import finceptquantlib as fql

# Curves, swaps and bonds
curve = fql.ZeroCurve(date(2025, 1, 15), [0.5, 1, 2, 5, 10], [0.040, 0.041, 0.042, 0.043, 0.045])
swap = fql.InterestRateSwap(10_000_000, date(2025, 1, 15), date(2030, 1, 15), fixed_rate=0.042)
swap.par_rate(date(2025, 1, 15), curve)                                  # 0.04378

bond = fql.FixedRateBond(date(2025, 1, 15), date(2035, 1, 15), coupon_rate=0.045)
bond.price_from_yield(0.05, settlement_date=date(2025, 1, 15))           # 96.1027

# Options
call = fql.bs_call(S=100, K=105, r=0.03, q=0.01, sigma=0.25, T=1.0)      # 8.6124
fql.bs_implied_vol(call, S=100, K=105, r=0.03, q=0.01, T=1.0,
                   option_type=fql.OptionType.CALL)                      # 0.25

heston = fql.HestonModel(
    fql.HestonParameters(v0=0.04, kappa=1.5, theta=0.05, sigma=0.5, rho=-0.7),
    spot=100, rate=0.03, dividend=0.01,
)
heston.european_call_price(105, 1.0)                                     # 5.9313

# Portfolios and risk
cov = [[0.040, 0.006, 0.010], [0.006, 0.090, 0.012], [0.010, 0.012, 0.0625]]
weights = fql.max_sharpe_portfolio([0.08, 0.12, 0.10], cov, rf_rate=0.02).weights
fql.calculate_var(weights, cov, confidence=0.95, portfolio_value=1_000_000)  # 267,522

Every public name is available from the top-level package and from its subpackage (fql.ZeroCurve is finceptquantlib.curves.ZeroCurve).

Modules

Development

git clone https://github.com/Fincept-Corporation/finceptquantlib.git
cd finceptquantlib
pip install -e ".[dev]"
pytest            # unit tests and docstring examples
ruff check src tests

See CONTRIBUTING.md for guidelines and CHANGELOG.md for release notes.

License

MIT. See LICENSE.

FinceptQuantLib is provided for research and analytics. It is not investment advice; validate results independently before relying on them for trading, risk or regulatory reporting.