Py Vollib Options Pricing

Py Vollib Options Pricing: Py Vollib Options Pricing: specialized toolkit for 3+ finance workflows covered in the triggers section.

QuantitativeDerivativesData
✓ 0 reported success·v0.1.0·

Overview

Py Vollib Options Pricing skill for finance analytics + 回测. Covers 3+ use cases. (batch-v1 draft, needs English review) This skill is built on open-source project tangweigang-jpg/doramagic-skills and embeds 15 anti-pattern constraints. Visit doramagic.ai/r/py-vollib-options-pricing for bilingual documentation and use cases. Compatible with the Doramagic ecosystem (Claude Code, Cursor, openclaw, ChatGPT, Gemini, etc.).

Blueprint Source

finance-bp-127

tangweigang-jpg/doramagic-skills6360a632 source files

Constraints

60total
45fatal
45 must-not-violate

Evidence Quality

Confidence89%

Medium confidence — review before critical use

45 non-negotiable constraints

FATALresource_boundaryfinance-C-005

WHENWhen using ref_python for production calculations

ACTIONuse ref_python implementations in production systems

CONSEQUENCEref_python is 10-100x slower than production (uses pure Python scipy instead of optimized lets_be_rational C implementation), causing severe performance degradation

domain-constraint
FATALclaim_boundaryfinance-C-012

WHENWhen considering ref_python for mission-critical trading

ACTIONdeploy ref_python in any production trading system

CONSEQUENCEPure Python implementation lacks the speed and reliability guarantees of the optimized lets_be_rational C implementation, risking financial losses

domain-constraint
FATALdomain_rulefinance-C-015

WHENWhen implementing option pricing with BSM model

ACTIONadjust forward price for dividend yield using F = S * exp((r-q)*t)

CONSEQUENCEWithout dividend yield adjustment, BSM forward price will be incorrect, causing systematic mispricing for dividend-paying stocks. The option price will be systematically higher or lower than the true theoretical value.

domain-constraint

FAQ

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Changelog

v0.1.02026-04-23·Contributors: tangweigang-jpg

v0.1.0: Initial release on Doramagic.ai. Auto-generated batch-v1 metadata and FAQs based on tangweigang-jpg/doramagic-skills.