# Cboe Macro Volatility (`khnaami/cboe-macro-volatility`) Actor

Macro volatility intelligence and tail-risk engine tracking official CBOE indices.
Key Capabilities:
Ingests VIX (30-day implied vol), VVIX (volatility of volatility), and SKEW (black-swan tail risk index).
Generates the Exhibit 1 Implied Volatility vs. Realized Volatility (IV-RV) Spread Matrix.

- **URL**: https://apify.com/khnaami/cboe-macro-volatility.md
- **Developed by:** [khalid naami](https://apify.com/khnaami) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Cboe Macro Volatility & Institutional Quant Risk Analytics Actor

Institutional-grade cross-asset volatility monitor, **Cboe SKEW Black Swan Tail-Risk Model**, **Exhibit 1 Global Implied vs Realized Volatility Spread Matrix**, **VIX/VVIX Vol-of-Vol Dynamics**, and **1-Month Cross-Asset Correlation Heatmap**.

***

### 🚀 Key Frameworks & Quantitative Models

#### 1. Cboe SKEW Index (^SKEW) — Black Swan & Crash Risk Model

The Cboe SKEW Index measures the relative pricing of deep Out-of-the-Money (OTM) Put options on the S\&P 500 relative to At-the-Money options, quantifying institutional crash hedging demand:

- **`< 120` (Low Tail Risk / Benign Floor):** Minimal crash hedging; OTM put insurance is historically cheap.
- **`120 – 135` (Normal Historical Corridor):** Balanced institutional hedging equilibrium.
- **`135 – 155` (Elevated Tail Risk):** Aggressive institutional put purchasing; elevated crash awareness.
- **`155 – 160` (Extreme Peak / Reversal Ceiling):** Tail hedges reached maximum satiation and extreme expense. Historically marks reversal exhaustion.
- **`165 – 170+` (Black Swan Crisis Spike):** Rare global systemic shock level (e.g., 2008 Lehman collapse, 2020 COVID shock).

#### 2. Exhibit 1: Global Volatilities & Realized Spread Matrix

Evaluates 14+ major global asset classes (SPX, NDX, DIA, Russell 2000, Gold, Silver, Bitcoin, Ethereum, Euro, GBP, Dollar Index, Crude Oil, 10Y Yield, 30Y Yield):

- **1-Month Implied Volatility ($IV\_{1M}$)**
- **1-Month Realized Volatility ($RV\_{1M} = \text{std}(\text{ret}\_{21d}) \times \sqrt{252} \times 100$)**
- **Variance Risk Premium Spread ($IV - RV$)**: Identifies overpriced options (rich premium to harvest) vs underpriced options (cheap protection).
- **1-Year Historical IV Percentile ($P\_{\text{IV}}$)**.

#### 3. VIX vs VVIX Dynamics (Vol-of-Vol Velocity)

- Measures the pricing velocity and uncertainty of equity market volatility itself.
- High VVIX ($> 110$) indicates sharp hedging rotation and explosive tail-risk acceleration.

#### 4. 1-Month Cross-Asset Correlation Heatmap (21 Trading Days)

- Computes daily rolling pairwise Pearson correlations between equities, crypto, precious metals, FX, oil, and treasury yields to identify asset decoupling and hedging effectiveness.

***

### 📥 Input Parameters

| Parameter | Type | Default | Description |
|---|---|---|---|
| `lookbackPeriod` | `String` | `"1y"` | Lookback period for historical volatility curves and 1-year percentiles (`6mo`, `1y`, `2y`, `5y`). |
| `correlationWindowDays` | `Integer` | `21` | Rolling trading days for pairwise cross-asset correlation matrix (default 21 days = 1 month). |
| `includeCorrelationMatrix` | `Boolean` | `true` | Compute full pairwise correlation matrix. |
| `includeHistoricalSeries` | `Boolean` | `true` | Include historical time-series datasets. |

***

### 📤 Output Structure

#### 1. Default Dataset (Exhibit 1 Spreads Table)

```json
{
  "assetClass": "S&P 500 (SPX)",
  "ticker": "SPY",
  "volatilityTicker": "^VIX",
  "impliedVolatility1M": 14.85,
  "realizedVolatility1M": 11.20,
  "ivRvSpreadPts": 3.65,
  "historicalPercentile1Y": 34.2,
  "pricingCondition": "Options Fairly Priced (IV ≈ RV)",
  "updatedAt": "2026-09-30T21:30:00Z"
}
```

#### 2. Key-Value Store (`OUTPUT`)

Comprehensive JSON object containing:

- **`liveIndices`**: Real-time snapshots of VIX, VVIX, SKEW, VXN, RVX, GVZ, OVX.
- **`skewTailRiskModel`**: Tail-risk regime status, benchmark bands, and actionable bias.
- **`vixVvixDynamics`**: Vol-of-vol stress level and ratio.
- **`globalVolatilitiesExhibit1`**: Full asset class spread table.
- **`crossAssetCorrelationMatrix`**: Pairwise correlation heatmap values.
- **`automatedQuantNarrative`**: Institutional macro commentary.

***

### 🎯 Institutional Use Cases

- **Options Selling & Premium Harvesting**: Systematically spot assets with elevated positive Variance Risk Premiums ($IV \gg RV$).
- **Tail-Risk Hedging & Portfolio Protection**: Time tail-risk put hedge acquisitions when SKEW is low ($< 120$) and avoid buying hedges at extreme ceiling zones ($> 155$).
- **Cross-Asset Volatility Arbitrage**: Capitalize on volatility dislocations across equities, crypto, oil, and gold.

# Actor input Schema

## `lookbackPeriod` (type: `string`):

Lookback period for historical volatility series and 1-year percentiles.

## `correlationWindowDays` (type: `integer`):

Number of trading days for rolling cross-asset correlation matrix (default 21 days = 1 Month).

## `includeCorrelationMatrix` (type: `boolean`):

Compute full pairwise correlation matrix across equities, commodities, crypto, FX, and rates.

## `includeHistoricalSeries` (type: `boolean`):

Include daily historical time series of Cboe volatility indices (VIX, VVIX, SKEW, etc.).

## Actor input object example

```json
{
  "lookbackPeriod": "1y",
  "correlationWindowDays": 21,
  "includeCorrelationMatrix": true,
  "includeHistoricalSeries": true
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset items and records produced by the Actor

## `overview` (type: `string`):

Summary report stored in Key-Value store

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("khnaami/cboe-macro-volatility").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("khnaami/cboe-macro-volatility").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call khnaami/cboe-macro-volatility --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,khnaami/cboe-macro-volatility"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/iaFVCOsVPCWoCd6P5/builds/JOHBH023AZF5Kf8oA/openapi.json