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The US Index Options dataset depends on the US Index Option Universe dataset because the US Index Option Universe dataset contains information on the available contracts, including their daily Greeks and implied volatility values. Before you download US Index Options data, open the Pricing page of your organization and subscribe to the US Index Option Universe History by QuantConnect data package. You need billing permissions to change the organization's subscriptions.

After you subscribe to local access (see Prerequisites), open a terminal in your organization workspace and run the following commands to bulk download the data and its prerequisites.

To download the US Index Option Universe data, run:

$ lean data download --dataset "US Index Option Universe" --data-type "Bulk" --start "20250403" --end "20250403"

To download the US Index Options data for a resolution, run the following command, replacing <resolution> with daily, hour, or minute and adjusting the date range:

$ lean data download --dataset "US Index Options" --data-type "Bulk" --resolution "<resolution>" --start "20230101" --end "20230105"

You can also use the CLI Command Generator. For more information, see Using the CLI.

After you bulk download the US Index Options dataset, new daily updates are available at 8 PM Coordinated Universal Time (UTC) two days after each trading day. Instead of directly calling the lean data download command, you can place a Python script in the data directory of your organization workspace and run it to update your data files. The following example script updates all data resolutions:

import os
import pandas as pd
from datetime import datetime, time, timedelta
from pytz import timezone
from os.path import abspath, dirname
os.chdir(dirname(abspath(__file__)))

OVERWRITE = False

# Define a method to download the data
def __download_data(resolution, start=None, end=None):
    print(f"Updating {resolution} data...")
    command = f'lean data download --dataset "US Index Options" --data-type "Bulk"  --resolution "{resolution}"'
    if start:
        end = end if end else start
        command += f" --start {start} --end {end}"
    if OVERWRITE:
        command += " --overwrite"
    print(command)
    os.system(command)

def __get_end_date() -> str:
    now = datetime.now(timezone("US/Eastern"))
    if now.time() > time(7,30):
        return (now - timedelta(1)).strftime("%Y%m%d")
    print('New data is available at 07:30 AM EST')
    return (now - timedelta(2)).strftime("%Y%m%d")

def __download_high_frequency_data(latest_on_cloud):
    for resolution in ["minute"]:
        dir_name = f"indexoption/usa/{resolution}/spx".lower()
        if not os.path.exists(dir_name):
            __download_data(resolution, '19980101')
            continue
        latest_on_disk = sorted(os.listdir(dir_name))[-1].split('_')[0]
        if latest_on_disk >= latest_on_cloud:
            print(f"{resolution} data is already up to date.")
            continue
        __download_data(resolution, latest_on_disk, latest_on_cloud)

def __download_low_frequency_data(latest_on_cloud):
    for resolution in ["daily", "hour"]:
        file_name = f"indexoption/usa/{resolution}/spx.zip".lower()
        if not os.path.exists(file_name):
            __download_data(resolution)
            continue
        latest_on_disk = str(pd.read_csv(file_name, header=None)[0].iloc[-1])[:8]
        if latest_on_disk >= latest_on_cloud:
            print(f"{resolution} data is already up to date.")
            continue
        __download_data(resolution)

if __name__ == "__main__":
    latest_on_cloud = __get_end_date()
    __download_low_frequency_data(latest_on_cloud)
    __download_high_frequency_data(latest_on_cloud)

The preceding script checks the date of the most recent minute resolution data you have for SPX. If there is new minute data available, it downloads the new data files and overwrites your hourly and daily files. If you don't intend to download all resolutions, adjust this script to your needs.

To update your local copy of the US Index Option Universe data, run the following command, or use the universe auto-update script below:

$ lean data download --dataset "US Index Option Universe" --data-type "Bulk" --start "20250403" --end "20250403"

import os
from datetime import datetime, time, timedelta
from pytz import timezone
from os.path import abspath, dirname
os.chdir(dirname(abspath(__file__)))

OVERWRITE = False

def __get_start_date() -> str:
    dir_name = f"indexoption/usa/universes"
    files = [] if not os.path.exists(dir_name) else sorted(os.listdir(dir_name)) 
    return files[-1].split(".")[0] if files else '19980101'

def __get_end_date() -> str:
    now = datetime.now(timezone("US/Eastern"))
    if now.time() > time(7, 0):
        return (now - timedelta(1)).strftime("%Y%m%d")
    print('New data is available at 07:00 AM EST')
    return (now - timedelta(2)).strftime("%Y%m%d")

if __name__ == "__main__":
    start, end = __get_start_date(), __get_end_date()
    if start >= end:
        exit("Your data is already up to date.")
            
    command = f'lean data download --dataset "US Index Option Universe" --data-type "Bulk" --start {start} --end {end}'
    if OVERWRITE:
        command += " --overwrite"
    print(command)
    os.system(command)

To download data for selected tickers instead of the full dataset, run a non-interactive lean data download command. First, download the US Index Option Universe data for the ticker to get the available contracts:

$ lean data download --dataset "US Index Option Universe" --data-type "Trade" --ticker "SPXW" --start "20250630" --end "20260630"

Then download the US Index Options data for the tickers, resolution, and date range you need. The dataset provides trade, quote, and open interest data, so run a command for each data type you need. For example, to download minute-resolution data for SPXW:

$ lean data download --dataset "US Index Options" --data-type "Trade" --ticker "SPXW" --resolution "Minute" --start "20230101" --end "20230105"
$ lean data download --dataset "US Index Options" --data-type "Quote" --ticker "SPXW" --resolution "Minute" --start "20230101" --end "20230105"
$ lean data download --dataset "US Index Options" --data-type "Open Interest" --ticker "SPXW" --resolution "Minute" --start "20230101" --end "20230105"

To download data interactively or to use the CLI Command Generator, see Using the CLI.

The following table shows the size of the US Index Options dataset for each resolution:

For examples, see the Data / indexoption / usa / daily directory in the LEAN repository.

Download in Bulk

To download the US Index Options dataset in bulk, subscribe to it on the Pricing page of your organization. The price depends on your organization tier and the resolution you need. The bulk download also requires the US Index Option Universe subscription. The following table shows the price ($/year) to download the historical data of each resolution for each organization tier:

After the first bulk subscription ends, subscribe to the updates to keep your local data current. The following table shows the price ($/year) of the updates of each resolution for each organization tier:

The following table shows the annual price ($/year) of the US Index Option Universe historical and updates subscriptions for each organization tier:

The following table shows the total cost of downloading the required datasets in bulk at minute resolution on the Quant Researcher tier. Other organization tiers apply their own rates, shown in the preceding tables.

Download by Ticker

The file format of the US Index Option Universe data is one file per underlying Index and each file costs 100 QCC = $1 USD. The US Index Options dataset is available in several resolutions. The resolution you need depends on the US Index Option subscriptions you create in your algorithm and the resolution of data you get in history requests. The following table describes the file format and costs of each resolution:

For example, the following algorithm subscribes to minute resolution data for a universe of SPXW Index Option contracts:

public class USIndexOptionsDataAlgorithm : QCAlgorithm
{
    public override void Initialize()
    {
        SetStartDate(2020, 1, 1);
        SetEndDate(2021, 1, 1);
        AddIndexOption("SPX", "SPXW");
    }
}

class USIndexOptionsDataAlgorithm(QCAlgorithm):
    def initialize(self):
        self.set_start_date(2020, 1, 1)
        self.set_end_date(2021, 1, 1)
        self.add_index_option("SPX", "SPXW")

The following table shows the data cost of the preceding algorithm:

The preceding table assumes you download trade, quote, and open interest data. However, you can run backtests with only trade data.