protective-collar

Compute protective collar configurations with P&L and Greeks for stock positions.

Updated Aug 23, 2026

Search Tags:#hedging #income #cost-offset #protective-collar #downside-protection

Ready to run

npx skills add https://github.com/keith-mvs/ordinis --skill protective-collar

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: protective-collar
Source: https://github.com/keith-mvs/ordinis/tree/main/docs/knowledge-base/domains/options/strategy-implementations/protective-collar
Command: npx skills add https://github.com/keith-mvs/ordinis --skill protective-collar

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill explains a protective collar: holding stock with a protective put and a short call to offset cost while capping upside.

Core Features & Use Cases

Downside Protection: Put limits loss
Upside Income: Call premium offsets put cost
Cost Efficiency: Often zero-cost or net credit hedges

Quick Start

Example: "Protect a 100-share AAPL position with a 165 put and 185 call."

Frequently Asked Questions about protective-collar

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I protect a stock position from downside risk while generating income?▼

A protective collar combines three positions: holding stock, buying a protective put to limit losses, and selling a covered call to offset the put cost. This strategy caps downside at the put strike while capping upside at the call strike, typically offsetting costs to near-zero or net credit over 30–90 day horizons.

What's the difference between a protective collar and just buying a put option?▼

A protective collar adds a short call to the put, generating premium that offsets or eliminates the put's cost. A put alone provides downside protection but no income offset. The collar trades unlimited upside for cost efficiency, making it ideal when you want defined risk without paying full put premiums.

Can I use Python with numpy and pandas to calculate collar P&L and Greeks?▼

Yes. This Skill uses numpy, pandas, and matplotlib to compute option Greeks, strike selections, P&L across price scenarios, and portfolio-level collar configurations. You'll need numpy≥1.24.0, pandas≥2.0.0, and matplotlib≥3.7.0 to run the analysis.

When should I implement a protective collar instead of other hedging strategies?▼

Use a collar when you own mid-to-large-cap stock, expect volatility within 30–90 days, and want to limit downside while offsetting hedging costs through call premium. It's cost-efficient for positions where you accept a defined cap on gains to reduce or eliminate protection expense.

How do I select the right put and call strikes for a collar hedge?▼

Strike selection depends on your risk tolerance, cost constraints, and return targets. This Skill automates strike recommendations by computing P&L, Greeks, and payoff diagrams across strike pairs, helping you balance protection level, income generation, and upside cap for your portfolio context.

What are the limitations of a protective collar strategy?▼

Collars cap your upside at the call strike, lock in opportunity cost if the stock rallies sharply, and require active management across positions with aligned expiries. Early assignment on short calls or shifts in implied volatility can affect economics before expiration.