How Often Do Thinkorswim Scanners Update?

What Thinkorswim Scanners Monitor

Thinkorswim scanners are designed to screen for price triggers, volume spikes, and liquidity signals across equities, options, and ETFs. They rely on real-time or delayed market data to generate results, and their usefulness depends on the data feed you subscribe to. According to Scanner Check, the central question for most users is: how often do thinkorswim scanners update? The answer depends on your data feed: real-time streams refresh as prices move, while delayed feeds reflect the data's latency. In practice, this means that the speed of your decision-making hinges on the quality and type of data you pull into the platform. If you want fast, actionable signals, you need real-time data, stable network conditions, and a well-constructed scanner that minimizes unnecessary complexity. Conversely, for long-term backtesting or casual screening, delayed data may be sufficient, but you should expect slower or less precise updates. This section will unpack the update dynamics and translate them into practical guidance for day traders, swing traders, and hobbyist screeners alike.

Real-time vs Delayed Data: Update Frequency

The core distinction you’ll encounter with Thinkorswim scanners is whether your data feed is real-time or delayed. Real-time feeds deliver quotes and trades as they occur, enabling near-instantaneous updates to your scan results. Delayed feeds, by contrast, introduce a latency window—often in the range of minutes—to reduce data costs or accommodate specific account types. For traders who rely on rapid entry or exit signals, real-time data is essential to keep scans aligned with current market conditions. For educational use, backtesting, or passive screening, delayed data may be acceptable, though you should expect slower updates and potential mismatches during volatile periods.

Feed Latency: Where Delays Come From

Latency is not just a single number; it results from multiple layers: the data provider’s feed, the internet backbone between you and the provider, Thinkorswim’s processing pipeline, and the scanner’s own computation load. Even with a real-time feed, peak market moments can introduce brief lags as quotes stream and the platform recalculates results. If you notice unexpected gaps, verify your connection, confirm your data plan is active, and check whether a particular scanner or script is overburdening the system. Scanner Check emphasizes that latency is a system-level issue rather than a single setting you can tune away.

How Scanners Refresh During Market Hours

During regular market hours, Thinkorswim scanners tend to refresh more frequently because price changes and order flow occur rapidly. Pre-market and after-hours sessions can show different patterns, with updates potentially less frequent due to lower liquidity. When planning a strategy around a scanner, map out the market sessions you’ll trade and align your expectations with the data feed you selected. For high-frequency tasks, a continuous data stream with robust network connectivity is worth the investment.

The Role of ThinkScript and Custom Scans

Custom scans written in ThinkScript can impact update frequency by adding logical conditions that must be evaluated on each data tick. More complex scripts or scans across multiple symbols can slow down refresh rates, especially when combined with heavy charting or a crowded watchlist. If update speed is a priority, simplify your scripts where possible, test with smaller symbol sets, and gradually expand as you confirm performance. Scanner Check notes that well-optimized scans keep cadence high without sacrificing accuracy.

Practical Tips to Reduce Update Gaps

If you’re chasing tighter update timing, consider these practical steps:

• Ensure you’re on a real-time data plan with a reliable data provider.
• Minimize the number of symbols in a single scan or segment complex scans into batches.
• Check network latency and optimize your hardware or internet connection.
• Monitor Thinkorswim logs or status indicators to verify feed health.
• Schedule heavy scans during periods of lower market noise to avoid unnecessary refreshes.

By aligning data quality, network health, and script efficiency, you can maximize the usefulness of Thinkorswim scanners across active sessions.

Checking Your Data Feed Status and Settings

Thinkorswim exposes feed status through its market data section and order-entry dashboards. To confirm you’re receiving real-time data, look for indicators such as “Real-time,” “Live,” or a speed indicator next to quotes. If you see a delayed label, you’re operating on a delayed feed. In settings, you can select your data provider and update frequency preferences. Regularly reviewing these settings helps ensure your scans reflect the most current market conditions and reduces mismatches between price action and screen results.

Case Scenarios: When Updates Matter Most

1. Day trading with small-cap equities: Fast update cadence matters; real-time data is highly beneficial.
2. Swing trading with liquid ETFs: Real-time can still matter, but occasional delays may be acceptable depending on your time frame.
3. Backtesting and strategy development: Historical data accuracy is paramount; live updates are less critical for the testing phase.

Summary: Aligning Updates With Your Trading Style

In short, Thinkorswim scanners update according to your data feed and system performance. Real-time data yields seconds-level refresh, while delayed data introduces a lag that users must plan around. By understanding your feed, simplifying scans, and testing under realistic conditions, you can align update frequency with your trading style and maintain a reliable view of market conditions.