About US Future Universe

The US Future Universe dataset by QuantConnect lists the available US Future contracts, their daily trading volume, and Open Interest. The data covers the 162 most liquid contracts, starts in May 2009, and is delivered on daily frequency. This dataset is created by monitoring the trading activity on the CFE, CBOT, CME, COMEX, NYMEX, and ICE*.

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 US Futures by AlgoSeek.

About QuantConnect

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.

Add US Future Universe

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About QuantConnect

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.

Algorithm Example

class USFuturesDataAlgorithm(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
        # Requesting data on gold and micro-gold contracts.
        # Filter the universe to trade only the contracts expiring within 90 days to ensure liquidity.
        self.mini_gold = self.add_future(Futures.Metals.GOLD) 
        self.mini_gold.set_filter(0, 90)
        
        self.micro_gold = self.add_future(Futures.Metals.MICRO_GOLD) 
        self.micro_gold.set_filter(0, 90)
        
        # Save a cache of the mapped symbol to trade.
        self.contract = {self.mini_gold.symbol: None, self.micro_gold.symbol: None}
    
    def on_data(self, slice: Slice) -> None:
        for symbol, chain in slice.future_chains.items():
            if symbol in self.contract:
                # Select the contract with the greatest open interest to trade with the most efficiency.
                most_liquid_contract = sorted(chain, key=lambda contract: contract.open_interest, reverse=True)[0]
                
                if self.contract[symbol] is None or most_liquid_contract.symbol != self.contract[symbol].symbol:
                    # Liquidate any unmapped contracts.
                    if self.contract[symbol] is not None:
                        self.liquidate(self.contract[symbol].symbol)
                    self.contract[symbol] = most_liquid_contract
                    
                    # Buy mini-gold and short micro-gold contracts as planned.
                    if symbol == self.mini_gold.symbol:
                        self.market_order(self.contract[symbol].symbol, 1)
                    elif symbol == self.micro_gold.symbol:
                        self.market_order(self.contract[symbol].symbol, -1)

Example Applications

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

Pricing

Provider offers 4 licensing options

Pricing