coredesk 0.1.0

CoreDesk: quant dev-oriented Python library for pricing, risk, and calibration.

CoreDesk

CoreDesk is an open-source, quant-dev–oriented Python library for pricing, risk, and calibration of vanilla derivatives.

It is designed to provide clean, explicit, desk-grade building blocks for quantitative finance, with a strong focus on numerical robustness, readability, and testability.

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🧭 Philosophy

CoreDesk follows four core principles:

• Explicit over implicit No hidden globals, no silent conventions.

• Separation of concerns Products ≠ Models ≠ Market ≠ Engines.

• Numerical robustness Bracketing, tolerances, clear failure modes.

• Desk-grade readability Code written to be read, reviewed, and extended.

This makes CoreDesk suitable for:

• quantitative finance education
• research notebooks
• interview preparation
• prototyping pricing libraries
• model validation and experimentation

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🧱 Architecture overview

coredesk/
├─ core/           # numerical foundations
├─ market/         # conventions & market environment
├─ products/       # financial instruments (payoff only)
├─ models/         # model parameters (no pricing logic)
├─ engines/        # pricing engines
├─ risk/           # Greeks
├─ calibration/    # implied volatility
└─ api/            # user-facing helpers

Module responsibilities

Module	Responsibility
core	math, stats, roots, interpolation, linalg, RNG
market	day count, rate conventions, market inputs
products	contract definitions (payoff only)
models	model parameters (volatility, dynamics)
engines	pricing logic
risk	Greeks
calibration	implied volatility
api	simplified public interface

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✨ Features (v0.1)

• European vanilla options

• Black–Scholes–Merton (spot + dividend yield)

• Black 76 (options on forwards/futures)

• Closed-form pricing

• Analytic Greeks (Delta, Gamma, Vega)

• Implied volatility (Brent solver)

• Robust numerical core:

  • root finding (bisect / brent / newton)
  • interpolation (linear / log-linear)
  • Cholesky & correlation repair
  • reproducible RNG

• Fully tested (pytest)

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📦 Installation

From source (recommended)

git clone https://github.com/baptiste-dehay/coredesk.git
cd coredesk
pip install -e .[dev]

Run tests

python -m pytest

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🚀 Quick start (API)

Black–Scholes price

from coredesk.api.vanilla import bsm_price

price = bsm_price(
    spot=100.0,
    strike=110.0,
    maturity=1.0,
    option_type="call",
    sigma=0.30,
    r=0.02,
    q=0.01,
)

print(price)

Greeks

from coredesk.api.vanilla import bsm_greeks

greeks = bsm_greeks(
    spot=100.0,
    strike=110.0,
    maturity=1.0,
    option_type="call",
    sigma=0.30,
    r=0.02,
    q=0.01,
)

print(greeks.delta, greeks.gamma, greeks.vega)

Implied volatility (BSM)

from coredesk.api.vanilla import bsm_iv

iv = bsm_iv(
    price=price,
    spot=100.0,
    strike=110.0,
    maturity=1.0,
    option_type="call",
    r=0.02,
    q=0.01,
)

print(iv)

Black 76 (options on forwards / futures)

from coredesk.api.vanilla import black76_price, black76_iv

price = black76_price(
    forward=100.0,
    strike=95.0,
    maturity=2.0,
    option_type="put",
    sigma=0.25,
    r=0.01,
)

iv = black76_iv(
    price=price,
    forward=100.0,
    strike=95.0,
    maturity=2.0,
    option_type="put",
    r=0.01,
)

print(price, iv)

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📚 Glossary of functions (Public API)

Pricing

Function	Description
bsm_price	Black–Scholes–Merton price (spot + dividend yield)
black76_price	Black 76 price (options on forwards/futures)

Greeks

Function	Description
bsm_greeks	Delta, Gamma, Vega (spot)
black76_greeks	Delta, Gamma, Vega (forward)

Calibration

Function	Description
bsm_iv	Implied volatility under BSM
black76_iv	Implied volatility under Black 76

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📐 Core numerical toolbox

core.stats

• normal_pdf
• normal_cdf
• normal_ppf

core.roots

• bisect
• newton
• brent

core.interpolation

• linear_interp
• log_linear_interp
• Interp1D

core.linalg

• cholesky
• nearest_correlation
• check_correlation_matrix

core.random

• RNG
• standard normals
• antithetic sampling

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🛣️ Roadmap (Applications)

v0.2 — Curves & discounting

• Yield curves
• Discount factors
• Bootstrapping

v0.3 — Volatility

• Volatility surfaces
• Smile calibration
• Surface interpolation / extrapolation

v0.4 — Monte Carlo

• GBM path simulation
• Multi-asset correlation
• Greeks via Monte Carlo

v0.5 — Advanced products

• American options (LSM)
• Barrier options
• Asian options

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🧪 Testing & quality

• 100% pytest-based
• Finite-difference validation for Greeks
• Numerical tolerances explicit
• Designed to be CI-friendly

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📄 License

Open-source (see LICENSE).

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👤 Author

Baptiste Dehay Quantitative Finance / Financial Engineering "Baptiste is analyzing, the world is watching"