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International Future Universe
Dataset by QuantConnect
The International Future Universe dataset by QuantConnect lists the available International Future contracts, their daily trading volume, and Open Interest. The data covers 3 contracts (FESX, HSI, and NKD), starts in July 1998, and is delivered on daily frequency. This dataset is created by monitoring the trading activity on the EUREX, HKFE, and CME.
This dataset does not contain market data. For market data, see International Futures by TickData and US Futures by AlgoSeek for NKD.
QuantConnect was founded in 2012 to serve quants everywhere with the best possible algorithmic trading technology. Seeking to disrupt a notoriously closed-source industry, QuantConnect takes a radically open-source approach to algorithmic trading. Through the QuantConnect web platform, more than 50,000 quants are served every month.
The International Futures Universe dataset provides data for contract filtering/selection:
hsi = self.add_future(Futures.Indices.HANG_SENG, Resolution.MINUTE) # "HSI"
hsi.set_filter(0, 90)
fesx = self.add_future(Futures.Indices.EURO_STOXX_50, Resolution.MINUTE) # "FESX"
fesx.set_filter(0, 90)
nkd = self.add_future(Futures.Indices.NIKKEI_225_DOLLAR, Resolution.MINUTE) # "NKD"
nkd.set_filter(0, 90)
var hsi= AddFuture(Futures.Indices.HangSeng, Resolution.Minute) // "HSI";
hsi.SetFilter(0, 90);
var fesx = AddFuture(Futures.Indices.EuroStoxx50, Resolution.Minute) // "FESX";
fesx.SetFilter(0, 90);
var nkd = AddFuture(Futures.Indices.Nikkei225Dollar, Resolution.Minute) // "NKD";
nkd.SetFilter(0, 90);
The following table describes the dataset properties:
Property | Value |
---|---|
Start Date | July 1998 (for details, see Supported Assets) |
Coverage | 3 Contracts |
Data Density | Dense |
Resolution | Daily |
Timezone | Various (for details, see Supported Assets) |
Market Hours | Regular and Extended |
The International Futures Universe dataset enables you to design Futures strategies accurately. Examples include the following strategies:
For more example algorithms, see Examples.
The following table shows the available Futures:
Ticker | Future | Start Date | Time Zone | Currency |
---|---|---|---|---|
HSI | Hang Seng Index Futures | Jan 2010 | Asia/Hong Kong | HKD |
FESX | EURO STOXX 50 Index Futures | Jul 1998 | Europe/Berlin | EUR |
NKD | Nikkei 225 Index Futures | Jan 2007 | America/Chicago | USD |
The International Future Universe dataset provides FutureFilterUniverse and FuturesChain objects.
FutureFilterUniverse objects have the following attributes:
FuturesChain objects have the following attributes:
To add US Future Universe data to your algorithm, call the AddFutureadd_future method. Save a reference to the Future object so you can access the data later in your algorithm. To define which contracts should be in your universe, specify the filter when requesting the Future data.
The AddFutureadd_future method provides a daily stream of Future chain data. To get the most recent daily chain, call the FuturesChainfutures_chain method with the underlying Future Symbol. The FuturesChainfutures_chain method returns data on all the tradable contracts, not just the contracts that pass your universe filter.
class InternationalFuturesDataAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2013, 12, 20)
self.set_end_date(2014, 2, 20)
self.set_cash(1000000)
self.universe_settings.asynchronous = True
self._future = self.add_future(Futures.Indices.HANG_SENG)
# Set our contract filter for this Future chain.
self._future.set_filter(lambda universe: universe.standards_only().front_month())
# Get the entire Futures chain for the current day.
chain = self.futures_chain(self._future.symbol, flatten=True).data_frame
public class InternationalFuturesDataAlgorithm : QCAlgorithm
{
private Future _future;
public override void Initialize()
{
SetStartDate(2013, 12, 20);
SetEndDate(2014, 2, 20);
SetCash(1000000);
UniverseSettings.Asynchronous = true;
var future = AddFuture(Futures.Indices.HangSeng);
// Set our contract filter for this Future chain.
_future.SetFilter((universe) => universe.StandardsOnly().FrontMonth());
// Get the entire Futures chain for the current day.
var chain = FuturesChain(_future.Symbol);
}
}
For more information about creating Future Universes, see Futures.
You can get historical International Future Universe data in an algorithm and the Research Environment.
To get historical International Future Universe data in an algorithm, call the Historyhistory method with the list Future contract Symbol objects. You may obtain all available Future contracts on a date by calling the FuturesChainfutures_chain method. Note that this method will return all available contracts despite your previous filter. If there is no data for the period you requested, the history result is empty.
# Subscribe to the underlying Future and save a reference to the Symbol.
symbol = self.add_future(Futures.Indices.HANG_SENG).symbol
# Get the contracts available on this day.
contracts = [x.symbol for x in self.futures_chain(symbol)]
# Request the historical data to obtain the data.
# DataFrame objects
history_df = self.history(contracts, 10, Resolution.DAILY, flatten=True)
open_interest = self.history(OpenInterest, contracts, 10, Resolution.DAILY, flatten=True)
# Open Interest objects
open_interest = self.history[OpenInterest](contracts, 10, Resolution.DAILY)
// Subscribe to the underlying Future and save a reference to the Symbol.
var symbol = AddFuture(Futures.Indices.HangSeng).Symbol
// Get the contracts available on this day.
var contracts = contracts = FuturesChain(symbol).Select(x => x.Symbol).ToList();
// Request the historical data to obtain the data.
// Slice objects
var history = History(contracts, 10, Resolution.Daily);
// Open Interest objects
var openInterest = History<OpenInterest>(contracts, 10, Resolution.Daily);
For more information about historical International Future Universe data in algorithms, see History Requests.
To get historical International Future Universe data in the Research Environment for an entire Futures chain, call the FutureHistoryfuture_history method with the canonical Future Symbol.
qb = QuantBook()
future = qb.add_future(Futures.Indices.HANG_SENG)
future.set_filter(0, 90)
history = qb.future_history(future.symbol, datetime(2020, 6, 1), datetime(2020, 6, 5), Resolution.DAILY)
history_df = history.data_frame
all_history = history.get_all_data()
expiries = history.get_expiry_dates()
var qb = new QuantBook();
var future = qb.AddFuture(Futures.Indices.HangSeng);
future.SetFilter(0, 90);
var history = qb.FutureHistory(future.Symbol, new DateTime(2020, 6, 1), new DateTime(2020, 6, 5));
You can also do similar in the research environment like in the algorithm to obtain the price and open interest data.
qb = QuantBook()
end = datetime(2020, 6, 5)
qb.set_start_date(end)
symbol = qb.add_future(Futures.Indices.HANG_SENG).symbol
# Get the contracts available on this day.
contracts = [x.symbol for x in qb.futures_chain(symbol)]
# Request the historical data to obtain the data.
history_df = qb.history(contracts, datetime(2020, 6, 1), end, Resolution.DAILY, flatten=True)
open_interest = qb.history(OpenInterest, contracts, datetime(2020, 6, 1), end, Resolution.DAILY, flatten=True)
var qb = new QuantBook();
var end = new DateTime(2020, 6, 5);
qb.SetStartDate(end)
var future = qb.AddFuture(Futures.Indices.HangSeng);
// Get the contracts available on the day.
var contracts = qb.FuturesChain(future.Symbol).Select(x => x.Symbol);
// Request the historical data to obtain the data.
var history = qb.History(contracts, new DateTime(2020, 6, 1), end, Resolution.Daily);
var openInterest = qb.History<OpenInterest>(contracts, new DateTime(2020, 6, 1), end, Resolution.Daily);
The International Future Universe dataset provides FutureFilterUniverse and FuturesChain objects.
FutureFilterUniverse objects have the following attributes:
FuturesChain objects have the following attributes:
The following example algorithm uses the ZigZag indicator to determine the trend of Hang Seng Index. It then trades the Index with HSI Futures.
class InternationalFuturesDataAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2021, 1, 1)
self.set_end_date(2021, 7, 1)
# Set the time zone to HKT to make it more comparable with the exchange.
self.set_time_zone(TimeZones.HONG_KONG)
# Set the account currency as HKD to trade HSI Futures.
self.set_account_currency("HKD", 1000000)
# Seed the last price of the contracts for filling.
self.set_security_initializer(BrokerageModelSecurityInitializer(self.brokerage_model, FuncSecuritySeeder(self.get_last_known_prices)))
# Request HSI Futures to trade.
# Note that we will trade the contract with the highest open interest for liquidity.
self.hsi_future = self.add_future(
Futures.Indices.HANG_SENG,
extended_market_hours=True,
data_mapping_mode=DataMappingMode.LAST_TRADING_DAY,
contract_depth_offset=0
)
# Adds contracts that expiry within 90 days. We will trade the farthest contract
self.hsi_future.set_filter(0,90)
# Request the corresponding underlying Index for feeding indicator for trade signal generation.
hsi_index = self.add_index("HSI").symbol
# Create a ZigZag indicator to trade Hang Seng Index price pivot points.
self._zz = self.zz(hsi_index, 0.15, 5, Resolution.DAILY)
# Warm up indicator for immediate readiness to trade.
self.warm_up_indicator(hsi_index, self._zz, Resolution.DAILY)
def on_data(self, slice: Slice) -> None:
# Only place trade if the Future contracts is in market opening hours to avoid stale fills.
if self.is_market_open(self.hsi_future.symbol) and self._zz.is_ready:
pivot = self._zz.pivot_type
# If the last pivot point is a low point, the current trend is increasing after this low point.
if pivot == PivotPointType.LOW:
contracts = sorted([x.symbol for x in slice.future_chains.get(self.hsi_future.symbol)],
key=lambda x: x.id.date)
self.set_holdings(contracts[-1], 0.2)
# If the last pivot point is a high point, the current trend is decreasing after this high point.
if pivot == PivotPointType.HIGH:
contracts = sorted([x.symbol for x in slice.future_chains.get(self.hsi_future.symbol)],
key=lambda x: x.id.date)
self.set_holdings(contracts[-1], -0.2)
public class InternationalFuturesDataAlgorithm : QCAlgorithm
{
private Future _hsiFuture;
private ZigZag _zz;
public override void Initialize()
{
SetStartDate(2021, 1, 1);
SetEndDate(2021, 7, 1);
// Set the time zone to HKT to make it more comparable with the exchange.
SetTimeZone(TimeZones.HongKong);
// Set the account currency as HKD to trade HSI Futures.
SetAccountCurrency("HKD", 1000000);
// Seed the last price of the contracts for filling.
SetSecurityInitializer(new BrokerageModelSecurityInitializer(BrokerageModel, new FuncSecuritySeeder(GetLastKnownPrices)));
// Request HSI Futures to trade.
// Note that we will trade the contract with the highest open interest for liquidity.
_hsiFuture = AddFuture(
Futures.Indices.HangSeng,
extendedMarketHours: true,
dataMappingMode: DataMappingMode.LastTradingDay,
contractDepthOffset: 0
);
// Adds contracts that expiry within 90 days. We will trade the farthest contract
_hsiFuture.SetFilter(0,90);
// Request the corresponding underlying index for feeding indicators for trade signal generation.
var hsiIndex = AddIndex("HSI").Symbol;
// Create a ZigZag indicator to trade Hang Seng Index price pivot points.
_zz = ZZ(hsiIndex, 0.15m, 5, Resolution.Daily);
// Warm up indicator for immediate readiness to trade.
WarmUpIndicator(hsiIndex, _zz, Resolution.Daily);
}
public override void OnData(Slice slice)
{
// Only place trade if the Future contracts is in market opening hours to avoid stale fills.
if (IsMarketOpen(_hsiFuture.Symbol) && _zz.IsReady)
{
var pivot = _zz.PivotType;
FuturesChain chain;
// If the last pivot point is low, the current trend is increasing after this low point.
if (pivot == PivotPointType.Low && slice.FutureChains.TryGetValue(_hsiFuture.Symbol, out chain))
{
var contract = chain.OrderBy(x => x.Expiry).LastOrDefault()?.Symbol;
SetHoldings(contract, 0.2m);
}
// If the last pivot point is high, the current trend decreases after this high point.
if (pivot == PivotPointType.High && slice.FutureChains.TryGetValue(_hsiFuture.Symbol, out chain))
{
var contract = chain.OrderBy(x => x.Expiry).LastOrDefault()?.Symbol;
SetHoldings(contract, -0.2m);
}
}
}
}
International Future Universe is allowed to be used in the cloud for personal and commercial projects for free. The data is permissioned for use within the licensed organization only
Free | Documentation
International Future Universe can be downloaded on premise with the LEAN CLI, for a charge per file downloaded. This download is for the licensed organization's internal LEAN use only and cannot be redistributed or converted in any format.
Starting at 100 QCC/file | Learn More
LEAN CLI is a cross-platform wrapper on the QuantConnect algorithmic trading engine called LEAN. The CLI makes using LEAN incredibly easy, reducing most of the pain points of developing and managing an algorithmic trading strategy to a few lines of bash.
Using the CLI you can download the same data QuantConnect hosts in the cloud for a small fee. These fees are per file downloaded, and are paid for in QuantConnect-Credits (QCC). We recommend purchasing credits to enable downloading.
The CLI command generator is a helpful tool to generate a copy-paste command to download this dataset from the form below.
lean data download \
--dataset "International Future Universe" \
--data-type "universe" \
--ticker "HSI" \
--market "hkfe" \
--start "20240330" \
--end "20250330"
lean data download `
--dataset "International Future Universe" `
--data-type "universe" `
--ticker "HSI" `
--market "hkfe" `
--start "20240330" `
--end "20250330"
Free access for International Future universe selection on the QuantConnect Cloud. Create custom filters using expiration dates, and open interest for the International Futures.
On premise download of International Future universe data files, including price, expiration dates, and open interest for local backtesting.
Bulk download of the entire International Future Universe dataset
Bulk download of the entire International Future Universe dataset
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Take extreme care to carefully structure your data TAR package with
the same folders as the LEAN data folder. Ensure all folders and file names are lowercase as Linux is case-sensitive.
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