alphagbm-iv-rank

Calculate IV Rank and IV Percentile from 252-day ATM IV history.

1.7k|225|Updated Apr 6, 2026
One-click install
npx skills add https://github.com/AlphaGBM/skills --skill alphagbm-iv-rank
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: alphagbm-iv-rank
Source: https://github.com/AlphaGBM/skills/tree/main/skills/alphagbm-iv-rank
Command: npx skills add https://github.com/AlphaGBM/skills --skill alphagbm-iv-rank

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Current IV levels are noisy and difficult to interpret in isolation. This skill computes IV Rank and IV Percentile to place current IV in the context of its 252-day history, helping users decide when IV is high or low and how to time volatility trades.

Core Features & Use Cases

  • IV Rank and IV Percentile calculations with historical context.
  • IV history data, HV/IV relationships, and zone-based trading signals to guide premium decisions.
  • Use Case: Evaluate whether to buy or sell premium by comparing current IV to its historical range and acting on IV zones.

Quick Start

Ask your AI to compute the current IV rank and percentile for a ticker and generate the IV history and zone-based trading signals.

Frequently Asked Questions about alphagbm-iv-rank

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

FAQPage Schema
How do I calculate IV rank and percentile for options trading?

IV rank and percentile are calculated by comparing a ticker's current ATM implied volatility to its 252 trading-day history. This contextualizes current IV levels, helping you assess whether volatility is high or low for timing premium trades.

What is the difference between IV rank and IV percentile for evaluating volatility?

IV rank and percentile both measure current IV against its 252-day historical range. IV rank shows where current IV sits relative to highs and lows, while IV percentile indicates the frequency of historical IV occurrences below the current level.

When do I need to use historical implied volatility data for options strategies?

Historical implied volatility data is needed to evaluate whether to buy or sell premium by identifying IV extremes. Comparing current ATM IV to its 252-day history generates zone classifications and trading signals for volatility timing.

Can I generate trading signals based on IV zones for US equities?

Yes, you can generate zone-based trading signals for US equities by classifying current IV levels against the 252-day window. This guides premium decisions by indicating if implied volatility is elevated or depressed relative to recent history.

Does the IV rank calculation use real-time options data or mock data?

The IV rank calculation uses mock data for demo tickers to compute the 252-day historical comparison. It evaluates current ATM IV against this history to deliver IV rank, percentile, and zone classifications for options analysis.

What are the limitations of using a 252-day window for volatility analysis?

The 252-day window limits volatility analysis to roughly one trading year of history, which may miss longer-term IV cycles. It focuses strictly on ATM IV relationships and excludes other option Greeks or deep historical data for screening IV extremes.