> ## Documentation Index
> Fetch the complete documentation index at: https://docs.oddpool.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Market OHLCV
> Open/high/low/close/volume bars for one or many markets.
OHLCV time series for markets on Kalshi or Polymarket. Pass 1 to 50 `market_ids` per request; the response is always an array of wrapped objects (metadata + bars + window stats). Markets not in our snapshot pipeline are silently omitted — compare submitted vs returned `market_ids` to detect.
Probability values are 0–1 (e.g. `0.62` = 62%). Volume is contracts traded during the bar period. Underlying snapshot cadence is 6 hours; `1d` / `1w` / `1m` intervals are aggregated server-side.
Bars go back to **2026-03-21** for both Kalshi and Polymarket. Markets that resolved before that date won't have history; coverage continues to grow forward.
For one bar series per outcome under an event (FOMC dashboards, championship odds, etc.), see [Event OHLCV](/events/ohlcv).
Don't have a `market_id`? Use [Search markets](/search/search-markets) or [Search series](/search/series).
## Parameters
Comma-separated `market_id` list, 1 to 50 entries. Kalshi tickers (e.g. `KXFEDDECISION-26JUN-H0`) or Polymarket condition IDs (`0x…`).
Window start (ISO 8601), inclusive. Defaults to 30 days ago. Mutually exclusive with `last`.
Window end (ISO 8601), exclusive. Defaults to now. Mutually exclusive with `last`.
Window shorthand. `` where unit is `h | d | w | m`. Examples: `30d`, `12h`, `4w`, `6m`. Mutually exclusive with `from`/`to`.
Bar size. One of `6h` (native cadence), `1d`, `1w`, `1m`. Sub-6h granularity is not available — snapshot cadence is 6 hours.
Maximum window is 365 days per request. `last=N` includes the in-progress current bucket — `last=14d&interval=1d` returns \~15 bars (14 completed days + today's partial). Trim the last bar if you only want completed periods.
## Examples
### One market, last 30 days
```bash cURL theme={null}
curl -H "X-API-Key: your_api_key" \
"https://api.oddpool.com/markets/ohlcv?market_ids=KXFEDDECISION-26JUN-H0&last=30d&interval=1d"
```
```python Python theme={null}
import requests
response = requests.get(
"https://api.oddpool.com/markets/ohlcv",
headers={"X-API-Key": "your_api_key"},
params={"market_ids": "KXFEDDECISION-26JUN-H0", "last": "30d", "interval": "1d"},
)
data = response.json()
```
### Multiple markets in one call
```bash cURL theme={null}
curl -H "X-API-Key: your_api_key" \
"https://api.oddpool.com/markets/ohlcv?market_ids=KXFEDDECISION-26JUN-H0,KXFEDDECISION-26JUL-H0&last=14d&interval=1d"
```
```python Python theme={null}
import requests
response = requests.get(
"https://api.oddpool.com/markets/ohlcv",
headers={"X-API-Key": "your_api_key"},
params={
"market_ids": "KXFEDDECISION-26JUN-H0,KXFEDDECISION-26JUL-H0",
"last": "14d",
"interval": "1d",
},
)
markets = response.json()
```
### Realized volatility over the last 30 days
Standard deviation of daily intraday range, in probability points.
```python Python theme={null}
import requests
import statistics
response = requests.get(
"https://api.oddpool.com/markets/ohlcv",
headers={"X-API-Key": "your_api_key"},
params={"market_ids": "KXFEDDECISION-26JUN-H0", "last": "30d", "interval": "1d"},
)
bars = [b for b in response.json()[0]["bars"] if b["high"] is not None]
ranges = [b["high"] - b["low"] for b in bars]
print("mean range:", statistics.mean(ranges))
print("stdev: ", statistics.stdev(ranges))
```
## Response
```json theme={null}
[
{
"market_id": "KXFEDDECISION-26JUN-H0",
"exchange": "kalshi",
"question": "Will the Federal Reserve hold rates at the June 2026 meeting?",
"category": "Economics",
"event_id": "KXFEDDECISION-26JUN",
"event_title": "Fed decision in Jun 2026?",
"status": "active",
"result": null,
"scheduled_close_at": "2026-06-18T18:00:00+00:00",
"interval": "1d",
"snapshot_cadence": "6h",
"window_start": "2026-04-21T03:08:44+00:00",
"window_end": "2026-05-05T03:08:44+00:00",
"stats": {
"window_open": 0.89,
"window_close": 0.95,
"window_high": 0.95,
"window_low": 0.87,
"window_volume": 788507,
"change_pct": 6.7416,
"change_1d": 0.012,
"change_7d": 0.041,
"change_30d": 0.075
},
"bars": [
{"ts": "2026-04-21T00:00:00+00:00", "open": 0.89, "high": 0.91, "low": 0.87, "close": 0.90, "volume": 51230},
{"ts": "2026-04-22T00:00:00+00:00", "open": 0.90, "high": 0.92, "low": 0.89, "close": 0.91, "volume": 48910}
]
}
]
```
### Field reference
| Field | Meaning |
| ---------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `bars[].ts` | Bar-start timestamp. For native `6h`, the actual snapshot timestamp; for aggregated intervals, the bucket start (`2026-05-04T00:00:00Z` for `1d`, etc.). |
| `bars[].open / high / low / close` | Probabilities in `[0, 1]`. **Can be `null`** for a bucket with no underlying snapshots (very thin markets or snapshot gaps); skip or forward-fill in chart code. |
| `bars[].volume` | Contracts traded during the bar. Aggregated intervals (`1d`, `1w`, `1m`) sum across the underlying 6h snapshots. **For per-period flow analysis, prefer `interval=6h`** — aggregated volume can look uneven across consecutive bars. |
| `stats.window_*` | Aggregates over the requested window, derived from the bars. |
| `stats.change_pct` | `(window_close - window_open) / window_open × 100`. **Percent** (e.g. `5.56` = +5.56%). |
| `stats.change_1d / 7d / 30d` | **Probability-point deltas** in `[-1, +1]` (e.g. `0.05` = +5pp). Anchored to the latest snapshot — they answer "where is this vs N days ago" regardless of `from`/`to`/`last`. They will not match `change_pct` even when your window length matches. |
## Errors
| Code | Reason |
| ----- | ----------------------------------------------------------------------------------------------------------- |
| `400` | `market_ids` empty, more than 50 ids, both `last` and `from`/`to` set, invalid interval, or invalid window. |