option-adjusted-spread

Calculate option-adjusted spread for bonds with embedded options using Monte Carlo simulation and binomial tree models.

Updated Aug 23, 2026

Search Tags:#valuation #options #bonds #fixed income #monte carlo #OAS #binomial tree

One-click install

npx skills add https://github.com/keith-mvs/ordinis --skill option-adjusted-spread

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: option-adjusted-spread
Source: https://github.com/keith-mvs/ordinis/tree/main/.claude/skills/option-adjusted-spread
Command: npx skills add https://github.com/keith-mvs/ordinis --skill option-adjusted-spread

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, scipy, and includes references (resource) and assets (resource) components.

What problem does it solve?

Valuing bonds with embedded options (callable, putable, MBS) is complex and requires advanced financial models. This skill automates these calculations, providing accurate pricing and yield comparisons to help you make informed investment decisions and identify mispricing opportunities.

Core Features & Use Cases

Automated OAS Calculation: Precisely calculate Option-Adjusted Spread using Monte Carlo simulation and binomial tree methodologies.
Embedded Option Valuation: Accurately price callable bonds, putable bonds, and mortgage-backed securities (MBS) by adjusting for their embedded optionality.
Spread Comparison: Clearly distinguish OAS from Z-spread and nominal spread, providing a true measure of credit and liquidity risk.
Use Case: Quickly determine the fair value and true yield spread of a callable corporate bond, allowing you to compare it accurately against non-callable alternatives and identify mispricing opportunities without manual, error-prone calculations.

Quick Start

Calculate the option-adjusted spread for a 10-year callable bond with a 5% coupon, callable at par in year 5, using a binomial tree model.