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Alphagbm Iv Rank

CommunityPopular
AlphaGBM
alphagbm-iv-rank

IV Rank and IV Percentile analysis showing where current implied volatility stands relative to its 252-day history. Returns IV rank (0-100), IV percentile (0-100), IV history data, and trading signals based on IV zone. Use when: deciding whether to buy or sell premium, checking if IV is high or low, timing volatility trades, screening for IV extremes. Triggers on: "IV rank AAPL", "is NVDA IV high", "IV percentile SPY", "historical IV TSLA", "is volatility cheap for META", "IV rank scan", "should I sell premium".

Overview

PublisherAlphaGBM
Repositoryskills
Skill namealphagbm-iv-rank
Stars
2.7K
Forks
290
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AlphaGBM on GitHub. Read the source before you install it.

Installation

Install the Alphagbm Iv Rank AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AlphaGBM/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/alphagbm-iv-rank .claude/skills/alphagbm-iv-rank
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alphagbm Iv Rank in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Alphagbm Iv Rank on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Alphagbm Iv Rank is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AlphaGBM IV Rank

Prerequisites

  • Account authentication: Set env ALPHAGBM_API_KEY (format agbm_xxxx...). The live snapshot requires authentication even though it does not consume analysis credits.
  • Base URL: Default https://alphagbm.zeabur.app. Override with env ALPHAGBM_BASE_URL.

What This Skill Does

Calculates IV Rank and IV Percentile for any ticker, placing current implied volatility in historical context. Answers the key question: "Is IV high or low right now, and what should I do about it?"

Key Metrics

MetricFormulaWhat It Means
IV Rank(Current IV - 52w Low) / (52w High - 52w Low) x 100Where IV sits in its annual range. 0 = at the low, 100 = at the high
IV Percentile% of days in past year where IV was lower than todayWhat % of the time IV was cheaper than now. 80 = IV was lower 80% of the time
Current IV30-day ATM implied volatilityThe market's current expectation of annualized movement
IV 52w HighHighest 30-day IV in past 252 trading daysPeak IV -- usually during selloffs or events
IV 52w LowLowest 30-day IV in past 252 trading daysTrough IV -- usually during calm, grinding markets
HV/IV RatioHistorical Volatility / Implied Volatility>1 means realized vol exceeds implied (IV may be cheap)

IV Zones and Trading Signals

IV RankZoneWhat It MeansSuggested Action
80-100Very HighIV is near its annual peak -- options are expensiveSell premium: short strangles, iron condors, credit spreads
60-80HighIV is elevated -- above-average option pricesLean toward selling, but selective; good for covered calls
40-60ModerateIV is in the middle -- neither cheap nor expensiveStrategy-neutral; use directional view to decide
20-40LowIV is depressed -- options are cheapLean toward buying; good for debit spreads, long straddles
0-20Very LowIV is near its annual trough -- options are very cheapBuy premium: long straddles, debit spreads, calendars (sell back month)

API Endpoint

IV Snapshot (instant, no quota cost)

GET /api/options/snapshot/<SYMBOL>

Returns: ATM IV, IV Rank, HV 30d, VRP, VRP level. This endpoint does not consume analysis credits, but it still requires authentication.

Volatility Risk Premium (VRP)

VRP = Implied Vol - Historical Vol

VRP measures the gap between what the market expects (IV) and what actually happens (HV). It is a key signal for whether to sell or buy premium.

VRP LevelValueSellerBuyer
very_high>=15%Very favorableUnfavorable
high5-15%FavorableSlightly unfavorable
normal+/-5%NeutralNeutral
low-15% to -5%UnfavorableFavorable
very_low<-15%Very unfavorableVery favorable

How to Use

Input

  • Required: Ticker symbol
  • Optional: Lookback period (default 252 days), IV measure (30-day ATM, 60-day, or custom)

Output Structure

json
{
  "ticker": "AAPL",
  "price": 218.45,
  "iv_current": 28.5,
  "iv_rank": 42,
  "iv_percentile": 55,
  "iv_52w_high": 48.2,
  "iv_52w_low": 18.8,
  "iv_52w_mean": 30.1,
  "hv_30d": 25.2,
  "hv_iv_ratio": 0.88,
  "zone": "moderate",
  "signal": "No strong IV edge. Use directional conviction to choose strategy.",
  "iv_history": {
    "dates": ["2025-04-01", "2025-04-02", "..."],
    "iv_values": [32.1, 31.8, "..."],
    "hv_values": [28.5, 28.3, "..."]
  },
  "notable_events": [
    {"date": "2026-01-28", "iv": 48.2, "event": "Earnings spike"},
    {"date": "2025-08-05", "iv": 44.1, "event": "Market selloff"}
  ]
}

Example Queries

User SaysWhat Happens
"IV rank AAPL"IV rank, percentile, zone, and trading signal
"Is NVDA IV high?"IV rank + zone classification + comparison to 52w range
"IV percentile SPY"Percentile with historical context
"Historical IV TSLA"Full 252-day IV history with HV overlay
"Is volatility cheap for META?"IV rank + HV/IV ratio + buy/sell recommendation
"Should I sell premium on QQQ?"IV rank-based answer with suggested strategies

Mock Data

Offline demo tickers are available without an API key: AAPL, NVDA, SPY, TSLA, META. They use bundled sample data from mock-data/; they are not live API access.

Related Skills

  • alphagbm-vol-surface -- Full 3D IV landscape across strikes and expirations
  • alphagbm-vol-smile -- IV skew for a specific expiration
  • alphagbm-options-strategy -- IV zone informs whether to buy or sell premium
  • alphagbm-options-score -- IV attractiveness is a key scoring factor

Powered by AlphaGBM -- Real-data options & research intelligence for traders and AI agents. 10K+ users.

Frequently asked questions

What does the Alphagbm Iv Rank AI skill do?

IV Rank and IV Percentile analysis showing where current implied volatility stands relative to its 252-day history. Returns IV rank (0-100), IV percentile (0-100), IV history data, and trading signals based on IV zone. Use when: deciding whether to buy or sell premium, checking if IV is high or low, timing volatility trades, screening for IV extremes. Triggers on: "IV rank AAPL", "is NVDA IV high", "IV percentile SPY", "historical IV TSLA", "is volatility cheap for META", "IV rank scan", "should I sell premium".

Why use Alphagbm Iv Rank on TypingMind?

Because you install it once and use it with any model. Alphagbm Iv Rank is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Alphagbm Iv Rank in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AlphaGBM/skills/tree/main/skills/alphagbm-iv-rank. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Alphagbm Iv Rank?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Alphagbm Iv Rank?

As many as you like. As long as a model supports skills, you can use Alphagbm Iv Rank with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Alphagbm Iv Rank AI skill free?

Yes. It is published on GitHub by AlphaGBM under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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