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Datasets > International Future Universe

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International Future Universe

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Datasets >

International Future Universe

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International Future Universe

Dataset by QuantConnect

  • About
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Introduction

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 depends on the US Futures Security Master dataset because the US Futures Security Master dataset contains information on symbol changes of the contracts.

This dataset does not contain market data. For market data, see International Futures by TickData and US Futures by AlgoSeek for NKD.

About the Provider

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.

Getting Started

The International Futures Universe dataset provides data for contract filtering/selection:

Select Language:
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);

Data Summary

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

Example Applications

The International Futures Universe dataset enables you to design Futures strategies accurately. Examples include the following strategies:

  • Buying the Futures contract with the most open interest to reduce slippage and market impact
  • Trade speculation on an International Index
  • Trading bull calendar spreads to reduce volatility and margin requirements

For more example algorithms, see Examples.

Supported Assets

The following table shows the available Futures:

TickerFutureStart DateTime ZoneCurrency
HSIHang Seng Index FuturesJan 2010Asia/Hong KongHKD
FESX EURO STOXX 50 Index FuturesJul 1998Europe/BerlinEUR
NKDNikkei 225 Index FuturesJan 2007America/ChicagoUSD

Data Point Attributes

The International Future Universe dataset provides FutureFilterUniverse and FutureUniverse objects.

FutureFilterUniverse Attributes

FutureFilterUniverse objects have the following attributes:

FutureFilterUniverse

FutureUniverse Attributes

FutureUniverse objects have the following attributes:

 


Requesting Data

To add International 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.

Select Language:
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.

Accessing Data

For information about accessing International Future Universe data, see Futures.

Historical Data

You can get historical International Future Universe data in an algorithm and the Research Environment.

Historical Data In Algorithms

To get historical International Future Universe data in an algorithm, call the History<FutureUniverse>history method with continuous Future Symbol and a lookback period. This method returns the all the available contracts for each trading day, not the subset of contracts that pass your universe filter. If there is no data for the period you requested, the history result is empty.

Select Language:
# Add the Future and save a reference to it.
future = self.add_future(Futures.Indices.HANG_SENG)

# DataFrame example where the columns are the FutureUniverse attributes:
history_df = self.history(FutureUniverse, future.symbol, 5, flatten=True)

# Series example where the values are lists of FutureUniverse objects: 
history_series = self.history(FutureUniverse, future.symbol, 5, flatten=False)

# FutureUniverse objects example:
history = self.history[FutureUniverse](future.symbol, 5)
// Add the Future and save a reference to it.
var future = AddFuture(Futures.Indices.HangSeng);

// Get historical data.
var history = History<FutureUniverse>(future.Symbol, 5);

For more information about historical International Future Universe data in algorithms, see Contracts.

Historical Data In Research

To get historical International Future Universe data in the Research Environment, call the History<FutureUniverse>history method with continuous Future Symbol and a time period. This method returns the all the available contracts for each trading day, not the subset of contracts that pass your universe filter. If there is no data for the period you requested, the history result is empty.

Select Language:
# Add the Future and save a reference to it.
future = qb.add_future(Futures.Indices.HANG_SENG)

# DataFrame example where the columns are the FutureUniverse attributes:
history_df = qb.history(FutureUniverse, future.symbol, datetime(2025, 1, 1), datetime(2025, 4, 1), flatten=True)

# Series example where the values are lists of FutureUniverse objects: 
history_series = qb.history(FutureUniverse, future.symbol, 5, flatten=False)

# FutureUniverse objects example:
history = qb.history[FutureUniverse](future.symbol, datetime(2025, 1, 1), datetime(2025, 4, 1))
// Add the Future and save a reference to it.
var future = qb.AddFuture(Futures.Indices.HangSeng);

// Get historical data.
var history = qb.History<FutureUniverse>(future.Symbol, new DateTime(2025, 1, 1), new DateTime(2025, 4, 1));

For more information about historical International Future Universe data in the Research Environment, see Daily Prices History.

Data Point Attributes

The International Future Universe dataset provides FutureFilterUniverse and FutureUniverse objects.

FutureFilterUniverse Attributes

FutureFilterUniverse objects have the following attributes:

FutureFilterUniverse

FutureUniverse Attributes

FutureUniverse objects have the following attributes:

 


Classic Algorithm Example

The following example algorithm uses the ZigZag indicator to determine the trend of Hang Seng Index. It then trades the Index with HSI Futures.

Select Language:
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);
            }
        }
    }
}

 


Licensing Available

Cloud Usage

Cloud Usage

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

Live trading license available

LEAN CLI Downloads Usage

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


About Lean CLI

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.

CLI Command Generator

The CLI command generator is a helpful tool to generate a copy-paste command to download this dataset from the form below.

Select OS:
lean data download \
	--dataset "International Future Universe" \
	--data-type "universe" \
	--ticker "HSI" \
	--market "hkfe" \
	--start "20240509" \
	--end "20250509" 
lean data download `
	--dataset "International Future Universe" `
	--data-type "universe" `
	--ticker "HSI" `
	--market "hkfe" `
	--start "20240509" `
	--end "20250509" 

Pricing | Provider offers 4 licensing options edit edit

Pending

Cloud Access edit edit

edit edit

Free access for International Future universe selection on the QuantConnect Cloud. Create custom filters using expiration dates, and open interest for the International Futures.

  • Every contracts traded since 1998
  • Universe delivery by 6am ET
  • Carefully curated data

PRICE

Free

Documentation Subscribe cli button LEAN CLI Contact Us
Pending

On Premise Download edit edit

edit edit

On premise download of International Future universe data files, including price, expiration dates, and open interest for local backtesting.

  • Ownership of the data
  • Data in LEAN format
  • Local compute resources

PRICE

100 QCC/file

Documentation Subscribe cli button LEAN CLI Contact Us
Pending

Bulk Updates edit edit

edit edit

Bulk download of the entire International Future Universe dataset

  • Download entire International Future Universe
  • Daily delivery via CLI
  • Requires Bulk Download subscription
  • Does not include market data, see International Futures by TickData

PRICE

$960/yr

Documentation Subscribe cli button LEAN CLI Contact Us
Pending

Bulk Downloads edit edit

edit edit

Bulk download of the entire International Future Universe dataset

  • Download entire International Future Universe
  • Daily delivery via CLI
  • Does not include market data, see International Futures by TickData

PRICE

$1,200

Documentation Subscribe cli button LEAN CLI Contact Us

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Pricing

Provider offers 4 licensing options

View Pricing


Starting Date edit edit

  • July 1998

Coverage edit edit

  • 3 contracts

Delivery Methods edit edit

  • Download
  • Cloud

About the Provider

  • Website edit edit
  • Contact the Provider

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Upload a manually created tar or zip file to all cloud data systems.

Add a link and click the Sync Dataset button to upload the dataset

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About Dataset Sync

The dataset synchronizer is an internal tool for the QuantConnect team to upload data to the cloud data storage environments. It supports TAR files which are extracted in the root directory of the cloud data environments.
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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