US Equities Intraday Retail Flow

Near real-time retail investor turnover across US-listed equities derived from Vanda’s proprietary retail flow methodology.

This dataset provides intraday estimates of retail buying, selling, net turnover, and total turnover throughout the US trading session.

• US-listed equities
• Intraday frequency
• Updated every 10 minutes during US market hours
• 6B+ observations
• 27K+ symbols
• USD-denominated turnover metrics

Monitor evolving retail participation dynamics throughout the trading session.

Identify accelerating retail demand and intraday speculative participation.

Analyze equities experiencing elevated retail participation alongside abnormal price activity.

Track concentrated intraday retail positioning and potential squeeze dynamics.

Measure retail participation during earnings releases, macro events, and thematic volatility.

Intraday retail turnover provides a real-time view of changing retail participation across the market.

Rapid increases in retail buy turnover may indicate:

• speculative participation surges
• momentum chasing
• thematic retail rotation
• crowding acceleration

Sharp reversals in intraday retail positioning may indicate:

• retail profit taking
• sentiment reversal
• positioning unwind
• volatility-driven retail de-risking

SELECT
    ts,
    symbol,
    retail_net_turnover
FROM PUBLIC.EQUITY_10MIN_PUBLIC
WHERE symbol = 'NVDA'
ORDER BY ts;

SELECT
    symbol,
    retail_buy_turnover
FROM PUBLIC.EQUITY_10MIN_PUBLIC
WHERE ts >= DATEADD(hour, -1, CURRENT_TIMESTAMP)
ORDER BY retail_buy_turnover DESC
LIMIT 20;

SELECT
    symbol,
    ts,
    SUM(retail_net_turnover) OVER (
        PARTITION BY symbol
        ORDER BY ts
        ROWS BETWEEN 5 PRECEDING AND CURRENT ROW
    ) AS rolling_intraday_flow
FROM PUBLIC.EQUITY_10MIN_PUBLIC;

SELECT
    ts,
    SUM(retail_net_turnover) AS market_net_flow
FROM PUBLIC.EQUITY_10MIN_PUBLIC
GROUP BY ts
ORDER BY ts;

Vanda intraday retail flow datasets are generated using proprietary behavioral modeling and aggregation techniques designed to estimate evolving retail participation across US-listed equities throughout the trading session.

Metrics are intended for institutional monitoring and research workflows and should be interpreted as modeled institutional-grade estimates.

The dataset is designed for integration into:

• intraday research systems
• quantitative trading infrastructure
• execution analytics
• systematic monitoring dashboards
• Python workflows
• Snowflake notebooks

Access the dataset directly through Snowflake Marketplace.