S&P 500 Risk Regime

The S&P 500 Risk Regime dataset provides a daily, point-in-time binary classification of prevailing equity market conditions.

Each observation reflects whether the S&P 500 was classified as being in a risk-off (1) or risk-on (0) regime on that date.

This dataset is designed for systematic traders and researchers who require a stable, reproducible market state signal for filtering, sizing, or regime-aware modeling.

Why it’s useful

Use this dataset to:

• Filter strategies during elevated volatility or selloff regimes

• Dynamically scale position size based on market conditions

• Improve risk-adjusted returns via regime-aware allocation

• Segment backtests into bull vs stress environments

• Study behavioral or factor performance across volatility states

Because the regime is calculated point-in-time and stored historically, it can be used without introducing lookahead bias.

Endpoint

GET /v1/sp500-risk-regime

Base URL:

Authentication

All requests require an API key.

Pass your key either:

• As a query parameter: ?api_key=your_key

• Or via header:

X-API-Key: your_key

Sample Request

Python

import requests

url = "https://api.alphanume.com/v1/sp500-risk-regime"

params = {
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

cURL

curl "https://api.alphanume.com/v1/sp500-risk-regime?api_key=alp_abc123"

Request Parameters

api_key (required)

Your Alphanume API key.

date (optional)

Return regime classification for a single date (YYYY-MM-DD).

Example:

?date=2026-02-23

date_gte / date_lte / date_gt / date_lt (optional)

Filter by date range.

All dates must be provided in YYYY-MM-DD format.

Any logically valid combination is accepted.

Examples:

?date_gte=2025-01-01&date_lte=2025-12-31

?date_gt=2024-06-01

If no date filters are provided, all available historical observations are returned (subject to tier-based limits).

Response Format

Responses are returned in JSON format.

Example:

{
  "count": 522,
  "data": [
    {
      "date": "2026-02-23",
      "risk_regime": 1
    }
  ]
}

Response Fields

Regime Definition

risk_regime

• 1 → Risk-Off
  Elevated volatility and/or stress conditions. Historically associated with defensive positioning and higher downside risk.

• 0 → Risk-On
  Lower volatility and constructive equity conditions. Historically associated with trend persistence and risk-seeking behavior.

The classification is derived from forward-looking implied volatility metrics and is stored as a fixed daily regime label.

Historical values are not retroactively altered.

Notes on Data Behavior

• New observations are updated daily, at 10:10 AM (America/New York Time)

• Dates are returned as YYYY-MM-DD

• Values are point-in-time

• Historical regime labels remain fixed once published

• Results are ordered by date DESC

Typical Use Cases

• Conditioning equity exposure on volatility state

• Improving Sharpe by avoiding participation in high-stress regimes

• Feature engineering for ML-based trading systems

• Comparing factor returns across risk environments

• Stress-testing strategy robustness