Futures

The functions from the OpenBB Terminal Futures menu is part of the SDK layer, and provides methods for programmatically accessing the data and charts associated with them. Get started by importing the OpenBB SDK to the Python script or Jupyter Notebook file.

How to Use

Below is a brief description of each function within the Futures module:

Path	Type	Description
openbb.futures.curve	Function	Futures Forward Curve Data
openbb.futures.curve_chart	Function	Futures Forward Curve Chart
openbb.futures.search	Function	Search Available Futures
openbb.futures.historical	Function	Historical OHLC+V Data
openbb.futures.historical_chart	Function	Chart Historical Price of Individual Contracts

Examples

Import Statements

The examples here will assume that the block below is included at the top of the file:

from openbb_terminal.sdk import openbb
import pandas as pd
%matplotlib inline

Search

Futures can be searched by description, exchange, or category.

openbb.futures.search(description = 'Eurodollar')

	Ticker	Description	Exchange	Category
66	GE	Eurodollar Futures	CME	currency
67	GLB	One-Month Eurodollar Futures	CME	currency
152	SED	SED (SOFR-Eurodollar) Spread Futures	CME	bonds

The historical front-month price is captured to a DataFrame with:

Curve

The forward curve data for a symbol is fetched with:

eurodollar = openbb.futures.curve('GE')

Expiration	Futures
2022-11-01 00:00:00	95.3561
2022-12-01 00:00:00	94.9925
2023-01-01 00:00:00	94.985
2023-02-01 00:00:00	94.9
2023-03-01 00:00:00	94.825

To display a chart of the data, use curve_chart:

openbb.futures.curve_chart(symbol = 'GE')

Historical

The historical function can fetch the historical front-month price:

wti_continuous = obb.futures.historical('CL')

Or, while actively trading, individual contracts. The example below requests historical data for the December WTI contract from 2023 to 2030, starting at the first recorded trading day of the December 2030 contract.

cl_2312 = openbb.futures.historical(symbols = ['CL'], expiry = '2023-12')
cl_2312 = cl_2312.rename(columns={'Adj Close':'2023-12'})
cl_2412 = openbb.futures.historical(symbols = ['CL'], expiry = '2024-12')
cl_2412 = cl_2412.rename(columns={'Adj Close':'2024-12'})
cl_2512 = openbb.futures.historical(symbols = ['CL'], expiry = '2025-12')
cl_2512 = cl_2512.rename(columns={'Adj Close':'2025-12'})
cl_2612 = openbb.futures.historical(symbols = ['CL'], expiry = '2026-12')
cl_2612 = cl_2612.rename(columns={'Adj Close':'2026-12'})
cl_2712 = openbb.futures.historical(symbols = ['CL'], expiry = '2027-12')
cl_2712 = cl_2712.rename(columns={'Adj Close':'2027-12'})
cl_2812 = openbb.futures.historical(symbols = ['CL'], expiry = '2028-12')
cl_2812 = cl_2812.rename(columns={'Adj Close':'2028-12'})
cl_2912 = openbb.futures.historical(symbols = ['CL'], expiry = '2029-12')
cl_2912 = cl_2912.rename(columns={'Adj Close':'2029-12'})
cl_3012 = openbb.futures.historical(symbols = ['CL'], expiry = '2030-12')
cl_3012 = cl_3012.rename(columns={'Adj Close':'2030-12'})

historical = pd.DataFrame(data = [cl_2312['2023-12'],cl_2412['2024-12'],cl_2512['2025-12'],cl_2612['2026-12'],cl_2712['2027-12'],cl_2812['2028-12'],cl_2912['2029-12'],cl_3012['2030-12']]).transpose()
historical = historical.dropna()

historical

Date	2023-12	2024-12	2025-12	2026-12	2027-12	2028-12	2029-12	2030-12
2020-01-24 00:00:00	49.61	50.14	50.7	51.56	51.63	51.63	51.63	51.63
2020-01-27 00:00:00	49.94	50.6	51.18	51.05	51.12	51.12	51.12	51.12
2020-01-28 00:00:00	50.17	50.78	51.23	51.55	51.62	51.62	51.62	51.62
2020-01-29 00:00:00	50.07	50.64	51.13	51.6	51.67	51.67	51.67	51.67
2020-01-30 00:00:00	50.27	50.91	51.44	51.49	51.56	51.56	51.56	51.56
2022-11-09 00:00:00	76.69	71.62	68.01	65.1	62.52	60.17	58.12	56.49
2022-11-10 00:00:00	77	71.64	67.89	64.86	62.26	59.91	57.86	56.23
2022-11-11 00:00:00	78.81	73.1	69.22	66.19	63.6	61.25	59.2	57.57
2022-11-14 00:00:00	77.4	72.35	68.89	66.15	63.62	61.25	59.13	57.5
2022-11-15 00:00:00	78.82	73.66	70.14	67.36	64.94	62.62	60.49	58.68