# US Equities Daily Retail Flow

Historical daily retail investor turnover across US-listed equities derived from Vanda’s proprietary retail flow methodology.

This dataset provides institutional investors with daily estimates of retail buying, selling, net turnover, and total turnover across the US equity market.

## Coverage

- US-listed equities
- Daily frequency
- 2012–Present history
- 32M+ observations
- USD-denominated turnover metrics


## Core Metrics

| Metric | Description |
|  --- | --- |
| retail_buy_turnover | Estimated retail buy turnover in USD |
| retail_sell_turnover | Estimated retail sell turnover in USD |
| retail_net_turnover | Estimated net retail turnover in USD |
| retail_total_turnover | Estimated total retail turnover in USD |


## Common Institutional Workflows

### Behavioral Factor Construction

Use retail positioning data as a behavioral factor within systematic investment models and cross-sectional equity research.

### Retail Crowding Analysis

Monitor concentration of retail participation across individual equities, sectors, and thematic baskets.

### Retail Momentum Monitoring

Identify sustained retail buying and selling activity associated with momentum participation and speculative positioning.

### Event Participation Analysis

Measure retail participation around earnings releases, macro events, product launches, and thematic rotations.

### Retail Reversal Detection

Identify inflection points where retail positioning begins reversing following extended participation trends.

## Interpretation Notes

Retail net turnover measures directional retail participation.

Sustained positive retail net turnover may indicate:

- growing speculative participation
- momentum-driven retail demand
- thematic adoption
- increasing retail crowding


Large reversals in retail net turnover may indicate:

- sentiment exhaustion
- retail capitulation
- positioning unwind risk
- reduced speculative participation


## Example Workflows

### Daily Retail Positioning — Single Stock


```sql
SELECT
    date,
    symbol,
    retail_net_turnover
FROM PUBLIC.EQUITY_1D_PUBLIC
WHERE symbol = 'NVDA'
ORDER BY date;
```

### Top Retail Buying Stocks


```sql
SELECT
    symbol,
    retail_buy_turnover
FROM PUBLIC.EQUITY_1D_PUBLIC
WHERE date = CURRENT_DATE - 1
ORDER BY retail_buy_turnover DESC
LIMIT 20;
```

### Retail Momentum — 5 Day Rolling


```sql
SELECT
    symbol,
    date,
    SUM(retail_net_turnover) OVER (
        PARTITION BY symbol
        ORDER BY date
        ROWS BETWEEN 4 PRECEDING AND CURRENT ROW
    ) AS net_flow_5d
FROM PUBLIC.EQUITY_1D_PUBLIC;
```

### Aggregate Retail Positioning


```sql
SELECT
    date,
    SUM(retail_net_turnover) AS total_market_net_flow
FROM PUBLIC.EQUITY_1D_PUBLIC
GROUP BY date
ORDER BY date;
```

## Methodology Overview

Vanda retail flow datasets are derived using proprietary behavioral modeling and aggregation techniques designed to estimate retail investor activity across US-listed securities.

Metrics are designed to capture relative retail participation dynamics and should be interpreted as modeled institutional-grade estimates rather than exchange-reported transaction feeds.

## Integration

The dataset is designed for direct integration into:

- quantitative research pipelines
- factor research frameworks
- Snowflake notebooks
- Python workflows
- BI dashboards
- systematic strategy infrastructure


## Marketplace Listing

Access the dataset directly through Snowflake Marketplace.