Statistics
Statistics provides official summary statistics of each instrument that's published by the venue. This generally includes properties like daily volume, open interest, preliminary and final settlement prices, and official open, high, and low prices.
Fields (statistics)
| Field | Type | Description |
|---|---|---|
ts_recv | uint64_t | The capture-server-received timestamp expressed as the number of nanoseconds since the UNIX epoch. See ts_recv. |
ts_event | uint64_t | The matching-engine-received timestamp expressed as the number of nanoseconds since the UNIX epoch. See ts_event. |
rtype | uint8_t | A sentinel value indicating the record type. Always 24 in the statistics schema. See Rtype. |
publisher_id | uint16_t | The publisher ID assigned by Databento, which denotes the dataset and venue. See Publishers. |
instrument_id | uint32_t | The numeric instrument ID. See Instrument identifiers. |
ts_ref | uint64_t | The reference timestamp expressed as the number of nanoseconds since the UNIX epoch. |
price | int64_t | The value for price statistics where every 1 unit corresponds to 1e-9, i.e. 1/1,000,000,000 or 0.000000001. See Prices. |
quantity | int64_t | The value for non-price statistics. Will be INT64_MAX when unused. |
sequence | uint32_t | The message sequence number assigned at the venue. |
ts_in_delta | int32_t | The matching-engine-sending timestamp expressed as the number of nanoseconds before ts_recv. See ts_in_delta. |
stat_type | uint16_t | The type of statistic value contained in the message. See Types of statistics table below. |
channel_id | uint16_t | The channel ID within the venue. |
update_action | uint8_t | Indicates if the statistic is newly added (1) or deleted (2). (Deleted is only used with some stat_types) |
stat_flags | uint8_t | Additional flags associated with certain stat types and datasets. Refer to the Venues and datasets section for details. |
Some fields are not applicable depending on the type of statistic. Null, invalid or inapplicable values are represented by the maximum value of the field's type. For example, null is represented by 2^64-1 for ts_event, which has an unsigned 64-bit integer type. In cases where the value is actually zero or null has the same meaning as zero, zero is used instead.
Types of statistics
| Type | stat_type | price | quantity | stat_flags | ts_ref | Description |
|---|---|---|---|---|---|---|
| Opening price | 1 | ✓ | The price and quantity of the first trade of an instrument. | |||
| Indicative opening price | 2 | ✓ | ✓ | The probable price of the first trade of an instrument published during pre-open. | ||
| Settlement price | 3 | ✓ | ✓ | ✓ | The settlement price of an instrument. Flags will indicate whether the price is final or preliminary and actual or theoretical. | |
| Trading session low price | 4 | ✓ | The lowest trade price of an instrument during the trading session. | |||
| Trading session high price | 5 | ✓ | The highest trade price of an instrument during the trading session. | |||
| Cleared volume | 6 | ✓ | ✓ | The number of contracts cleared for an instrument on the previous trading date. | ||
| Lowest offer | 7 | ✓ | The lowest offer price for an instrument during the trading session. | |||
| Highest bid | 8 | ✓ | The highest bid price for an instrument during the trading session. | |||
| Open interest | 9 | ✓ | ✓ | The current number of outstanding contracts of an instrument. | ||
| Fixing price | 10 | ✓ | ✓ | The volume-weighted average price (VWAP) for a fixing period. | ||
| Close price | 11 | ✓ | The last trade price and quantity during a trading session. | |||
| Net change | 12 | ✓ | The change in price from the close price of the previous session to the most recent close price. | |||
| Volume-weighted average price | 13 | ✓ | ✓ | The volume-weighted average price (VWAP) during the trading session. | ||
| Volatility | 14 | ✓ | ✓ | The implied volatility associated with the settlement price. | ||
| Delta | 15 | ✓ | ✓ | The options delta associated with the settlement price. | ||
| Uncrossing price | 16 | ✓ | The auction uncrossing price and quantity. This is used for auctions that are neither the official opening auction nor the official closing auction. |
Types of statistics by publisher
The table below shows which statistics are available depending on dataset and publisher.
| Type | Cboe BZX Depth Pitch | CME Globex MDP 3.0 | Databento US Equities Summary | Eurex Exchange | European Energy Exchange | ICE | Nasdaq Basic | Nasdaq TotalView-ITCH | NYSE Arca Integrated | NYSE Integrated | OPRA |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Opening price | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Indicative opening price | ✓ | ||||||||||
| Settlement price | ✓ | ✓ | ✓ | ✓ | |||||||
| Trading session low price | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||
| Trading session high price | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||
| Cleared volume | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||
| Lowest offer | ✓ | ✓ | |||||||||
| Highest bid | ✓ | ✓ | |||||||||
| Open interest | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||
| Fixing price | ✓ | ||||||||||
| Close price | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |
| Net change | ✓ | ||||||||||
| Volume-weighted average price | ✓ | ||||||||||
| Volatility | ✓ | ||||||||||
| Delta | ✓ | ||||||||||
| Uncrossing price | ✓ | ✓ | ✓ |
Official vs. Databento summary statistics
The key distinction of the statistics schema is these are official summary statistics provided by the venue—Databento doesn't compute these statistics.
On most venues, Databento also provides separate OHLCV data that could be used in place of official open, high, low, and settlement prices, and volume from the statistics schema.
These schemas are different and may vary for a few intentional reasons:
- Often, official statistics have opaque methodology or are difficult to replicate because they're tallied by hand
- Some venues include volumes and open interest from open outcry, auction, block trades, RFQs, or other events that may not be disseminated in the electronic trading session or public feeds
- Some venues double count volumes
The main purpose of Databento's summary data is that it provides more consistency: we derive it systematically from the tick data or full order book data during the electronic trading session and ensures consistency with our tick data; we publish at more deterministic times, and we normalize across venues using a UTC midnight cutoff universally. For electronic trading and research applications, this consistency may be more important, whereas for back office and administrative applications, official statistics may be preferable.