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This page covers the API. For the full strategy and intuition behind this dataset, see:
→ [Guide: How Stocks Are Grouped (Ticker Classification)]

Ticker Sector & Industry Classification

The Ticker Sector & Industry Classification dataset provides a mapping of equity tickers into Alphanume-defined sector and industry groups.

Each observation assigns a ticker to a consistent, internally defined classification system derived from underlying business activity. These classifications are designed for quantitative workflows and are not intended to replicate standardized taxonomies.

The dataset is structured to be stable, URL-safe, and directly queryable for use in filtering, grouping, and feature engineering pipelines.

Why it’s useful

Use this dataset to:

• Filter universes by sector or industry exposure
• Build sector-neutral or industry-relative strategies
• Group tickers for cross-sectional analysis
• Construct features based on economic exposure
• Standardize classification across research pipelines
• Join with other datasets for consistent segmentation

Because classifications are stored and served in a consistent format, this dataset can be used as a foundational layer across multiple workflows.

Endpoint

GET /v1/ticker-classification

Base URL

Authentication

All requests require an API key.

Pass your key either:

• As a query parameter

• Or via header

Sample Request

Python

import requests

url = "https://api.alphanume.com/v1/ticker-classification"

params = {
    "api_key": "alp_abc123",
    "sector": "technology"
}

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

cURL

Request Parameters

api_key (required)

Your Alphanume API key.

ticker (optional)

Filter results by a specific ticker.

Example:

?ticker=AAPL

sector (optional)

Filter results by sector.

Must be one of the accepted sector keywords (lowercase, underscore-separated).

Example:

?sector=technology

industry (optional)

Filter results by industry.

Must be one of the accepted industry keywords.

Example:

?industry=semiconductors

Available Sector Values

The following sector values are accepted for the sector parameter.

All values must be lowercase and underscore-separated.

Available Industry Values

The following industry values are accepted for the industry parameter.

All values must be lowercase and underscore-separated.

Parameter Behavior

• All parameters are optional
• If no parameters are provided, the full dataset is returned (subject to tier limits)
• Parameters can be combined

Examples:

?ticker=AAPL
?sector=finance
?industry=software
?sector=finance&industry=banking
?ticker=JPM&sector=finance

Invalid sector or industry values will return a 400 error.

Response Format

Responses are returned in JSON format.

Example:

{
  "count": 3,
  "data": [
    {
      "ticker": "AAPL",
      "alphanume_sector": "technology",
      "alphanume_industry": "hardware_devices"
    },
    {
      "ticker": "MSFT",
      "alphanume_sector": "technology",
      "alphanume_industry": "software"
    }
  ]
}

Response Fields

Classification System

The classification system uses:

• Lowercase formatting
• Underscore-separated values
• Stable internal labels
• Alphanume-defined sector and industry groupings

These values are designed to be:

• URL-safe
• Consistent across endpoints
• Easy to integrate into systematic workflows

Notes on Data Behavior

• Classifications are deterministic and consistent
• Values are not dynamically inferred at query time
• Results are ordered by ticker (ascending)
• No date dimension is applied
• The dataset represents the current mapping of tickers to classifications

Typical Use Cases

• Building sector-neutral equity strategies

• Filtering universes by economic exposure

• Grouping tickers for factor modeling

• Joining classification data with signals and returns

• Creating sector-based dashboards and analytics

• Standardizing classification across research pipelines