> For the complete documentation index, see [llms.txt](https://statalpha.gitbook.io/statalpha-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://statalpha.gitbook.io/statalpha-docs/stats/odc.md).

# ODC

The **Opening Day Continuation (ODC)** module evaluates how often the market direction in the early minutes of a session continues throughout the trading day.\
It measures the **follow rate**, **strength ratio**, and **volume share** for different starting intervals — e.g., 5, 10, 15, 30, or 60 minutes after the open.

***

## Concept

* Tests whether the direction of the early intervals (e.g., first 5, 10, 15 minutes) continues during the full day.
* Quantifies **directional consistency**, **volatility**, and **volume allocation** for each interval.
* Evaluates both **bullish (green)** and **bearish (red)** starts separately.
* Includes performance breakdown by:
  * Follow rate (% of sessions where early move direction matched the day’s close)
  * Range contribution (how much of the daily range was already covered)
  * Volume share of early intervals
  * False-positive rate (green start → red day)

***

## Parameters

| Parameter                 | Type       | Description                                                         |
| ------------------------- | ---------- | ------------------------------------------------------------------- |
| `symbol`                  | string     | Target symbol (e.g., `AAPL`, `TSLA`, `BTCUSD`)                      |
| `interval_minutes`        | list\[int] | Minutes after open to evaluate (e.g., `5`, `10`, `15`, `30`, `60`)  |
| `start_date` / `end_date` | string     | Custom date range (`YYYY-MM-DD`)                                    |
| `time_window`             | string     | Predefined time window (e.g., `1M`, `3M`, `6M`, `12M`, `24M`, `5Y`) |
| `start_time` / `end_time` | string     | Intraday session window (default `13:30`–`20:00` UTC)               |
| `include_extended_hours`  | bool       | Include pre-/post-market data if `true`                             |
| `limit`                   | int        | Limits the number of results for `/top` and `/flop` endpoints       |
| `sort`                    | string     | Sorting key for `/top` and `/flop` (e.g., `green_follow_rate_pct`)  |

***

## Endpoints

| Endpoint                  | Description                                                                         |
| ------------------------- | ----------------------------------------------------------------------------------- |
| `GET /stats/odc`          | Returns per-day interval metrics (price, volume, direction, range)                  |
| `GET /stats/odc/summary`  | Aggregated metrics per interval (green/red start, follow rate, volume share, range) |
| `GET /stats/odc/top`      | Best intervals ranked by follow rate or chosen metric                               |
| `GET /stats/odc/flop`     | Weakest intervals ranked by lowest follow rate                                      |
| `GET /stats/odc/errors`   | False-positive analysis (green start → red day)                                     |
| `GET /stats/odc/momentum` | Average interval return percentage                                                  |
| `GET /stats/odc/doc`      | Field documentation for all endpoints                                               |

***

## Example Requests

### 1. Retrieve summary statistics

```bash
curl -s -H "Authorization: Bearer $ACCESS_TOKEN" \
  "https://api.statalpha.market/stats/odc/summary?symbol=TSLA&interval_minutes=5&interval_minutes=15&time_window=12M"
```

### 2. Get top-performing intervals

```bash
curl -s -H "Authorization: Bearer $ACCESS_TOKEN" \
  "https://api.statalpha.market/stats/odc/top?symbol=MSFT&interval_minutes=5&interval_minutes=10&limit=3&sort=green_follow_rate_pct"
```

### 3. Check weakest intervals

```bash
curl -s -H "Authorization: Bearer $ACCESS_TOKEN" \
  "https://api.statalpha.market/stats/odc/flop?symbol=AAPL&interval_minutes=5&interval_minutes=10&limit=3"
```

***

## Example Response (summary excerpt)

```json
[
  {
    "interval_minutes": 5,
    "green": {
      "count_start": 132,
      "follow_rate_pct": 62.8,
      "avg_interval_range_pct": 0.92,
      "avg_interval_volume_share": 7.8
    },
    "red": {
      "count_start": 128,
      "follow_rate_pct": 58.4,
      "avg_interval_range_pct": 0.86,
      "avg_interval_volume_share": 8.1
    },
    "time_window": "12M"
  }
]
```

***

## Interpretation

| Metric                                              | Meaning                                                               |
| --------------------------------------------------- | --------------------------------------------------------------------- |
| **green.follow\_rate\_pct / red.follow\_rate\_pct** | Share of sessions where early interval direction matched day’s close  |
| **avg\_interval\_range\_pct**                       | Average volatility during the interval relative to the day’s open     |
| **avg\_interval\_volume\_share**                    | Share of daily volume traded within the interval                      |
| **avg\_interval\_vs\_day\_range\_pct**              | Portion of the day’s total range already reached in the interval      |
| **false\_positive\_rate\_percent**                  | Rate of failed continuations (green start → red day)                  |
| **avg\_interval\_return\_percent**                  | Average return between open and interval end                          |
| **same\_direction\_rate\_percent**                  | How often the early interval and full day moved in the same direction |

***

## Notes

* ODC statistics help identify **time-based continuation patterns** useful for intraday timing or model calibration.
* All users can access the same metrics; plan differences apply only to query flexibility.
* Cached results are returned for repeated requests for consistent performance.


---

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