Finding Individual Futures Contract Trade Data
Summary
The document addresses how to obtain prices for a specific futures contract rather than a continuous series. It uses a wheat contract identified by exchange, delivery month, and year as an example, and asks whether Quandl provides this contract-level data or whether another source is needed.
The response suggests Databento and demonstrates requesting historical trade records for named futures symbols over a selected date range. The displayed sample includes event and receive timestamps, symbol, trade price, size, and other record fields, illustrating that the source can return individual contract-level observations rather than only a stitched continuous contract. The example is a practical pointer for researchers seeking raw trades, but it does not compare vendors, explain coverage or licensing, or establish that all exchanges and historical periods are available. The symbols and dates shown are illustrative of the query, not a general guarantee of data availability.
Key ideas
- Continuous futures series and individual contract records serve different research needs.
- A contract can be identified by its symbol, including its delivery month and year.
- The response points to Databento as a source for historical contract-level trade data.
- The sample output illustrates timestamps, prices, sizes, and symbols in returned records.
- The document does not assess provider coverage, licensing, or alternative vendors.
Tags
Full text
# Does Quandl offer raw futures data?
# Does Quandl offer raw futures data?
I am interested in downloading price data for individual futures contracts. For example, the price of the CBOT (CME) Wheat future ZWU3, which is the September 2023 contract for wheat, which will stop trading on 25 Aug 2023. So in general Exchange code + contract month + year, although specification is different per exchange.
Quandl offers the continuous contract, I'm not so interested in that. So -
- Is there any way to get raw futures prices on quandl?
- Is there another source for this data?
Thanks.
## Answer by Katie (score 2)
https://quant.stackexchange.com/a/76641
Have you tried Databento for this?
```
import databento as db
hist = db.Historical()
df = hist.timeseries.get_range(
dataset='GLBX.MDP3',
schema='trades',
symbols=['ZWU3', 'ZWZ3'],
start='2023-09-06',
end='2023-09-06',
).to_df()
print(df)
```
```
ts_event rtype publisher_id instrument_id action side depth price size flags ts_in_delta sequence symbol
ts_recv
2023-09-06 00:00:00.048889101+00:00 2023-09-06 00:00:00+00:00 0 1 11548 T N 0 601.25 38 0 15887 13383956 ZWZ3
2023-09-06 00:00:00.050593420+00:00 2023-09-06 00:00:00+00:00 0 1 11548 T N 0 600.50 15 0 15740 13383977 ZWZ3
2023-09-06 00:00:00.067415901+00:00 2023-09-06 00:00:00.002203413+00:00 0 1 11548 T N 0 601.25 5 0 18638 13384054 ZWZ3
2023-09-06 00:00:00.068546997+00:00 2023-09-06 00:00:00.044519411+00:00 0 1 11548 T A 0 600.25 1 0 15169 13384138 ZWZ3
2023-09-06 00:00:00.069071381+00:00 2023-09-06 00:00:00.048949485+00:00 0 1 11548 T B 0 600.50 1 130 14889 13384177 ZWZ3
... ... ... ... ... ... ... ... ... ... ... ... ... ...
2023-09-06 18:19:57.552399668+00:00 2023-09-06 18:19:57.552082273+00:00 0 1 11548 T A 0 609.50 1 128 18729 25113311 ZWZ3
2023-09-06 18:19:59.426980100+00:00 2023-09-06 18:19:59.426556417+00:00 0 1 11548 T N 0 610.00 2 0 18160 25118320 ZWZ3
2023-09-06 18:19:59.525244392+00:00 2023-09-06 18:19:59.524931395+00:00 0 1 11548 T A 0 609.50 1 128 18572 25118969 ZWZ3
2023-09-06 18:19:59.688887631+00:00 2023-09-06 18:19:59.688240591+00:00 0 1 11548 T N 0 609.50 1 0 15136 25119908 ZWZ3
2023-09-06 18:19:59.860866128+00:00 2023-09-06 18:19:59.860231917+00:00 0 1 11548 T N 0 609.50 1 0 16191 25120794 ZWZ3
[11976 rows x 13 columns]
```Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.