Rajandran R Creator of OpenAlgo - OpenSource Algo Trading framework for Indian Traders. Building GenAI Applications. Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for more than a decade. Designed and published 100+ open source trading systems on various trading tools. Strongly believe that market understanding and robust trading frameworks are the key to the trading success. Building Algo Platforms, Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in

Professional vs Non Professional Datafeeds

3 min read

In the context of U.S. stock market data feeds, the distinction between professional and non-professional subscribers is a classification used by exchanges and data vendors to determine pricing, access levels, and usage rights. This stems from exchange policies (e.g., NYSE, Nasdaq) and affects how data feeds are distributed and billed. Here’s the breakdown:

1. Definition

  • Professional Subscriber:
    • An individual or entity using market data for business, commercial, or profit-generating purposes, typically in a professional capacity.
    • Examples: Traders at a hedge fund, financial analysts, brokers, or anyone employed by a firm that uses the data for trading, client services, or market analysis.
  • Non-Professional Subscriber:
    • An individual using market data for personal, non-commercial purposes, not tied to their occupation or a business.
    • Examples: Retail investors managing their own portfolios, hobbyists, or students learning about markets.

2. Key Differences

a. Purpose of Use

  • Professional: Data is used for work-related or revenue-generating activities (e.g., advising clients, executing trades for a firm).
  • Non-Professional: Data is for personal investment or education, not tied to income or business operations.

b. Cost

  • Professional: Significantly more expensive due to perceived commercial value. Fees can range from tens to hundreds of dollars per month per user for real-time data, depending on the feed (e.g., NYSE or Nasdaq Level 1/2).
  • Non-Professional: Much cheaper, often a flat fee (e.g., $1–$15/month for real-time SIP data) or free for delayed data through retail brokers.

c. Access and Contracts

  • Professional: Requires signing detailed agreements with exchanges or vendors, often audited to ensure compliance with usage terms. Firms may need to report the number of users or devices accessing the data.
  • Non-Professional: Simpler self-certification process—users typically check a box or sign a basic subscriber agreement affirming personal use.

d. Data Depth

  • Professional: Often granted access to richer feeds (e.g., Level 2, direct exchange data) for advanced trading needs.
  • Non-Professional: Usually limited to Level 1 or SIP data, sufficient for casual trading but less granular.

e. Regulatory Oversight

  • Professional: Subject to stricter scrutiny by exchanges and regulators to prevent misuse or redistribution of data.
  • Non-Professional: Less oversight, as usage is assumed to be low-impact and individual.

3. Why Vendors Ask

Data vendors (e.g., Bloomberg, Interactive Brokers, Thomson Reuters) ask about professional vs. non-professional status because:

  • Exchange Rules: Exchanges like NYSE and Nasdaq mandate this distinction to enforce tiered pricing and protect their data revenue. Vendors pass these rules onto users.
  • Liability: Vendors must report subscriber types to exchanges and ensure compliance, or they risk fines.
  • Pricing Models: Fees are tailored based on usage—professionals subsidize the system, while non-professionals get affordable access.

4. Examples in Practice

  • Professional: A day trader working for a prop trading firm subscribes to Nasdaq TotalView for $50+/month per user, paid by the firm.
  • Non-Professional: A retail investor using Robinhood gets free delayed data or pays $5/month for real-time NBBO via SIP.

Real-Time NBBO via SIP

What It Is:

  • NBBO: Stands for National Best Bid and Offer. It’s the highest bid price and lowest ask price available across all U.S. exchanges for a given stock at any moment. Think of it as the “best deal” snapshot for buyers and sellers.
  • SIP: Stands for Securities Information Processor. It’s a centralized system that collects, consolidates, and distributes market data (quotes and trades) from all U.S. exchanges (like NYSE, Nasdaq, etc.) into a single feed.
  • Real-Time: Means the data is delivered with minimal delay—as trades and quotes happen, you see them almost instantly (though SIP has a slight lag, often milliseconds).

How It Works:

  • The SIP aggregates data from exchanges under plans like the CTA (Consolidated Tape Association) for NYSE-listed stocks and UTP (Unlisted Trading Privileges) for Nasdaq-listed stocks.
  • It processes this into a unified stream, including the NBBO, last sale prices, and trade volumes.
  • Example: If Apple (AAPL) has a best bid of $150.00 on NYSE and a best ask of $150.05 on Nasdaq, the NBBO is $150.00/$150.05, and SIP delivers that in real time.

Key Features:

  • Latency: Slower than direct feeds (50–500 milliseconds delay) because it consolidates data from multiple sources.
  • Cost: Affordable—often $1–$15/month for non-professionals via brokers like Robinhood or TD Ameritrade.
  • Depth: Limited to Level 1 data (best bid/ask, last trade), not the full order book.

Use Case:

  • Ideal for retail investors or casual traders who need a reliable, broad market view without needing ultra-fast execution or deep market details.

Nasdaq TotalView

What It Is:

  • Nasdaq TotalView: A premium, direct data feed from the Nasdaq exchange that provides a comprehensive view of the order book for Nasdaq-listed stocks.
  • Direct Feed: Unlike SIP, it comes straight from Nasdaq, bypassing consolidation, so it’s faster and more detailed.

How It Works:

  • TotalView shows the full depth of book—not just the NBBO, but every bid and ask price at every price level, along with the number of shares at each level.
  • Example: For AAPL, you might see:
    • Bid: $150.00 (500 shares), $149.99 (200 shares), $149.98 (1000 shares), etc.
    • Ask: $150.05 (300 shares), $150.06 (400 shares), $150.07 (700 shares), etc.
  • It also includes every order (market-by-order data), not just the top of the book.

Key Features:

  • Latency: Much faster than SIP (often under 50 microseconds), critical for high-speed trading.
  • Cost: Expensive—can be $50–$100+/month per user, targeting professionals like hedge funds or algo traders.
  • Depth: Level 2+ data, showing the entire order queue, not just the best prices.
  • Extras: Includes Net Order Imbalance Indicator (NOII) for Nasdaq opening/closing auctions, giving insight into supply/demand before the market opens or closes.

Use Case:

  • Perfect for professional traders, high-frequency trading (HFT) firms, or anyone needing to see market depth and act on microsecond-level changes.

Bottom Line

The professional/non-professional split is about who you are (job role) and how you use the data (commercial vs. personal). Vendors ask to align with exchange pricing structures and ensure fair access. If you’re unsure which applies to you, check the vendor’s subscriber agreement or contact their support—misclassifying can lead to back charges or service cuts. Let me know if you need help with a specific vendor’s terms!

Rajandran R Creator of OpenAlgo - OpenSource Algo Trading framework for Indian Traders. Building GenAI Applications. Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for more than a decade. Designed and published 100+ open source trading systems on various trading tools. Strongly believe that market understanding and robust trading frameworks are the key to the trading success. Building Algo Platforms, Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in

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