search icon search icon
  • Learning Center Home Learning Center Home All Courses
  • My courses in progress My courses in progress In Progress
  • My courses Completed My courses Completed Completed
  • My Wish List My Wish List Wish List
  • My Wish List My Wish List Articles

Learning Center

Your Quantitative Foundation

A collection of courses from independent educators to improve your quant skill base and create better strategies.

Available Courses

Solidify and expand your quant skill base with courses at QuantConnect

Boot Camp 101 / US Equities

Learn algorithmic trading with python for US Equities. Guided strategy development in easily digestible portions.

Author: QuantConnect

Free  |  95,986 People Enrolled

Boot Camp 102 / FOREX

Learn algorithmic trading with python for FX. Guided strategy development in easily digestible portions.

Author: QuantConnect

Free  |  20,577 People Enrolled

Boot Camp 103 / Futures

Learn algorithmic trading with python for Futures. Guided strategy development in easily digestible portions.

Author: QuantConnect

Free  |  7,421 People Enrolled

Algorithmic Trading A-Z | The Complete Course

In this algorithmic trading tutorial series you will learn everything you need to know to start writing your own trading bots using Python and the QuantConnect quantitative trading platform.

Author: Louis

Free  |  28,770 People Enrolled

Complete Algorithmic Trading Course

Master algorithmic trading on QuantConnect; backtest and live trade Stocks, Options, Futures, Forex, and Crypto.

Author: Cheng Li

Paid  |  Enroll on Udemy

Python for Finance and Algorithmic Trading with QuantConnect

Learn to use Python, Pandas, Matplotlib, and the QuantConnect Lean Engine to perform financial analysis and trading.

Author: Jose Portilla, Pierian Training

Paid  |  Enroll on Udemy

Crypto Trading with QuantConnect (C#)

Learn to write programs that algorithmically trade cryptocurrencies using QuantConnect (C#).

Author: Eric Summers

Paid  |  Enroll on Udemy

List Your Course List Your Course

List Your Course

Quant Developer

FREE UPGRADE

Start

  • create new algorithm create new algorithm New Algorithm
  • open project open project Open Project
  • open project open project Explore Strategies

Resources

Notes icons

Organization Notes

start icon

Get Started with Algorithm Lab

Close Widget Close Widget
  • Signed Up
  • Create a Project Complete Task Complete Task
  • Backtest Your Project Complete Task Complete Task
  • Live Deploy Your Project Complete Task Complete Task
research icon

New Research

Optimizing a Gold-SPY Portfolio Using Hidden Markov Models for Market Downtime

Gold-SPY portfolio optimization using Hidden Markov Models for minimizing market downturn risk....

Read

News & Releases

announce icon

New Announcement

Hands on AI Trading with Python, QuantConnect, and AWS

Read
roadmap icon

Upcoming Roadmap

Online Members
+ Add Members
Quick Links
Research Community Quant League Documentation Learn

Begin Your QuantConnect Journey

Algorithm Lab is your playground for developing and refining trading algorithms with QuantConnect. Utilize advanced tools, historical data, and robust backtesting to enhance your trading strategies. Transform your ideas into actionable insights and optimize your trading approach with ease.

Sign Up for Free

Already have an account Log In.

Begin Your QuantConnect Journey

Algorithm Lab is your playground for developing and refining trading algorithms with QuantConnect. Utilize advanced tools, historical data, and robust backtesting to enhance your trading strategies. Transform your ideas into actionable insights and optimize your trading approach with ease.

Sign Up for Free

Already have an account Log In.

data Manager View
Requesting coding environment...

QuantConnect Datasets

Datasets

  • all datasets all datasets All Datasets 4
  • list datasets list datasets List Dataset
  • list datasets list datasets Data Issues +99
  • status status Data Status
  • sales report sales report Sales Report
  • All
  • Geospatial Data
  • Commerce Data
  • Financial Market Data
  • Consumer Data
  • B2B Data
  • Transport and Logistics Data
  • Environmental Data
  • Credit Rating Data
  • Real Estate Data
  • Web Data
  • Legal Data
  • Healthcare Data
  • Entertainment Data
  • Energy Data
  • Industry Data
  • Political Data
  • News and Events

Datasets > US Futures

Datasets >

US Futures

dataset-logo

US Futures

Dataset by AlgoSeek

Introduction

The US Futures dataset by AlgoSeek provides Futures data, including price, volume, open interest, and expiry. The data covers the 162 most liquid contracts, starts in May 2009, and is delivered on any frequency from tick to daily. This dataset is created by monitoring the trading activity on the CFE, CBOT, CME, COMEX, NYMEX, and ICE*.

This dataset also depends on the US Futures Security Master because the US Futures Security Master dataset contains information to construct continuous Futures.

About the Provider

AlgoSeek is a leading historical intraday US market data provider offering the most comprehensive and detailed market data and analytics products in the financial industry covering equities, futures, options, cash forex, and cryptocurrencies. AlgoSeek data is built for quantitative trading and machine learning. For more information about AlgoSeek, visit algoseek.com.

Getting Started

The following snippet demonstrates how to request data from the US Futures dataset:

Select Language: 
future = self.add_future(Futures.Metals.GOLD)
future.set_filter(0, 90)
var future = AddFuture(Futures.Metals.Gold);
future.SetFilter(0, 90);

Data Summary

The following table describes the dataset properties:

Property Value
Start Date May 2009
Asset Coverage 162 Futures
Data Density Dense
Resolution Tick, Second, Minute, Hour, & Daily
Timezone
  • Chicago (CFE, CME or CBOT)
  • New York (ICE, NYMEX or COMEX)
Market Hours Regular and Extended

This dataset only includes Sugar (SB) from the ICE exchange.

Volume Discrepancies

The volume of the daily trade bars from this dataset is different from the daily volume that CME and other platforms like Yahoo Finance report because the CME includes pit trades in their daily volume calculation. In contrast, the volume of the daily trade bars in this dataset (from AlgoSeek) doesn't include pit trades because pit trades are over-the-counter, which algorithms can't trade.

Another discrepancy occurs from the start and end times of the daily bars. Daily bars from the CME and Yahoo Finance span from 5 PM Central Time (CT) to 4 PM CT on the following day. In contrast, QuantConnect consolidates daily bars from from 12 AM Eastern Time (ET) to 12 AM ET the following day. Therefore, to calculate the daily volume in the same way that CME does (excluding the pit trades), sum the volume of intraday bars that span 5 PM CT to 4 PM CT on the following day. For an example implementation, see Examples.

Example Applications

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

  • Buying the Futures contract with the most open interest to reduce slippage and market impact
  • Trading bull calendar spreads to reduce volatility and margin requirements
Select Language:

For more example algorithms, see Examples.

Data Point Attributes

The US Futures dataset provides FuturesChain, Future, and OpenInterest objects. To configure the continuous Future settings, use the DataNormalizationMode and DataMappingMode enumerations.

DataNormalizationMode Values

The DataNormalizationMode enumeration has the following values:

DataNormalizationMode
    No modifications to the asset price at all. For Equities, dividends are paid in cash and splits are applied directly to your portfolio quantity. (0)
  • RAW: DataNormalizationMode
    • Splits and dividends are backward-adjusted into the price of the asset. The price today is identical to the current market price. (1)
  • ADJUSTED: DataNormalizationMode
    • Equity splits are applied to the price adjustment but dividends are paid in cash to your portfolio. This normalization mode allows you to manage dividend payments (e.g. reinvestment) while still giving a smooth time series of prices for indicators. (2)
  • SPLIT_ADJUSTED: DataNormalizationMode
    • Equity splits are applied to the price adjustment and the value of all future dividend payments is added to the initial asset price. (3)
  • TOTAL_RETURN: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The first contract has the true price. Factor 0. (4)
  • FORWARD_PANAMA_CANAL: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The last contract has the true price. Factor 0. (5)
  • BACKWARDS_PANAMA_CANAL: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, multiplying the prices by their ratio. The last contract has the true price. Factor 1. (6)
  • BACKWARDS_RATIO: DataNormalizationMode
    • Splits and dividends are adjusted into the prices in a given date. Only for history requests. (7)
  • SCALED_RAW: DataNormalizationMode
    No modifications to the asset price at all. For Equities, dividends are paid in cash and splits are applied directly to your portfolio quantity. (0)
  • Raw: DataNormalizationMode
    • Splits and dividends are backward-adjusted into the price of the asset. The price today is identical to the current market price. (1)
  • Adjusted: DataNormalizationMode
    • Equity splits are applied to the price adjustment but dividends are paid in cash to your portfolio. This normalization mode allows you to manage dividend payments (e.g. reinvestment) while still giving a smooth time series of prices for indicators. (2)
  • SplitAdjusted: DataNormalizationMode
    • Equity splits are applied to the price adjustment and the value of all future dividend payments is added to the initial asset price. (3)
  • TotalReturn: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The first contract has the true price. Factor 0. (4)
  • ForwardPanamaCanal: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The last contract has the true price. Factor 0. (5)
  • BackwardsPanamaCanal: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, multiplying the prices by their ratio. The last contract has the true price. Factor 1. (6)
  • BackwardsRatio: DataNormalizationMode
    • Splits and dividends are adjusted into the prices in a given date. Only for history requests. (7)
  • ScaledRaw: DataNormalizationMode

DataMappingMode Values

The DataMappingMode enumeration has the following values:

DataMappingMode
    The contract maps on the previous day of expiration of the front month (0)
  • LAST_TRADING_DAY: DataMappingMode
    • The contract maps on the first date of the delivery month of the front month. If the contract expires prior to this date, then it rolls on the contract's last trading date instead (1)
  • FIRST_DAY_MONTH: DataMappingMode
    • The contract maps when the following back month contract has a higher open interest that the current front month (2)
  • OPEN_INTEREST: DataMappingMode
    • The contract maps when any of the back month contracts of the next year have a higher volume that the current front month (3)
  • OPEN_INTEREST_ANNUAL: DataMappingMode
    The contract maps on the previous day of expiration of the front month (0)
  • LastTradingDay: DataMappingMode
    • The contract maps on the first date of the delivery month of the front month. If the contract expires prior to this date, then it rolls on the contract's last trading date instead (1)
  • FirstDayMonth: DataMappingMode
    • The contract maps when the following back month contract has a higher open interest that the current front month (2)
  • OpenInterest: DataMappingMode
    • The contract maps when any of the back month contracts of the next year have a higher volume that the current front month (3)
  • OpenInterestAnnual: DataMappingMode

Future Attributes

Future objects have the following attributes:

Future
    Gets or sets whether or not this security should be considered tradable
  • is_tradable: bool
    • Returns true if this is the future chain security, false if it is a specific future contract
  • is_future_chain: bool
    • Returns true if this is a specific future contract security, false if it is the future chain security
  • is_future_contract: bool
    • Gets the expiration date
  • expiry: DateTime
    • Specifies if futures contract has physical or cash settlement on settlement
  • settlement_type: SettlementType
    • Gets or sets the underlying security object.
  • underlying: Security
    • Gets or sets the currently mapped symbol for the security
  • mapped: Symbol
    • Gets or sets the contract filter
  • contract_filter: IDerivativeSecurityFilter<Symbol>
    • This securities QuantConnect.Interfaces.IShortableProvider
  • shortable_provider: IShortableProvider
    • Gets all the subscriptions for this security
  • subscriptions: List<SubscriptionDataConfig>
    • QuantConnect.Securities.Security.Symbol for the asset.
  • symbol: Symbol
    • Gets the Cash object used for converting the quote currency to the account currency
  • quote_currency: Cash
    • Gets the symbol properties for this security
  • symbol_properties: SymbolProperties
    • Type of the security.
  • type: SecurityType
    • There has been at least one datapoint since our algorithm started running for us to determine price.
  • has_data: bool
    • True if the security has been delisted from exchanges and is no longer tradable
  • is_delisted: bool
    • Data cache for the security to store previous price information.
  • cache: SecurityCache
    • Holdings class contains the portfolio, cash and processes order fills.
  • holdings: SecurityHolding
    • Exchange class contains the market opening hours, along with pre-post market hours.
  • exchange: SecurityExchange
    • Fee model used to compute order fees for this security
  • fee_model: IFeeModel
    • Fill model used to produce fill events for this security
  • fill_model: IFillModel
    • Slippage model use to compute slippage of market orders
  • slippage_model: ISlippageModel
    • Gets the portfolio model used by this security
  • portfolio_model: ISecurityPortfolioModel
    • Gets the buying power model used for this security
  • buying_power_model: IBuyingPowerModel
    • Gets the buying power model used for this security, an alias for QuantConnect.Securities.Security.BuyingPowerModel
  • margin_model: IBuyingPowerModel
    • Gets or sets the margin interest rate model
  • margin_interest_rate_model: IMarginInterestRateModel
    • Gets the settlement model used for this security
  • settlement_model: ISettlementModel
    • Gets the volatility model used for this security
  • volatility_model: IVolatilityModel
    • Customizable data filter to filter outlier ticks before they are passed into user event handlers. By default all ticks are passed into the user algorithms.
  • data_filter: ISecurityDataFilter
    • Customizable price variation model used to define the minimum price variation of this security. By default minimum price variation is a constant find in the symbol-properties-database.
  • price_variation_model: IPriceVariationModel
    • Provides dynamic access to data in the cache
  • data: object
    • Read only property that checks if we currently own stock in the company.
  • hold_stock: bool
    • Alias for HoldStock - Do we have any of this security
  • invested: bool
    • Local time for this market
  • local_time: DateTime
    • Get the current value of the security.
  • price: decimal
    • Leverage for this Security.
  • leverage: decimal
    • If this uses tradebar data, return the most recent high.
  • high: decimal
    • If this uses tradebar data, return the most recent low.
  • low: decimal
    • If this uses tradebar data, return the most recent close.
  • close: decimal
    • If this uses tradebar data, return the most recent open.
  • open: decimal
    • Access to the volume of the equity today
  • volume: decimal
    • Gets the most recent bid price if available
  • bid_price: decimal
    • Gets the most recent bid size if available
  • bid_size: decimal
    • Gets the most recent ask price if available
  • ask_price: decimal
    • Gets the most recent ask size if available
  • ask_size: decimal
    • Access to the open interest of the security today
  • open_interest: int
    • Gets the fundamental data associated with the security if there is any, otherwise null.
  • fundamentals: Fundamental
    • Gets or sets the specified custom property through the indexer. This is a wrapper around the QuantConnect.Securities.Security.Get``1(System.String) and QuantConnect.Securities.Security.Add(System.String,System.Object) methods.
  • item: object
    • The default time of day for settlement
  • DEFAULT_SETTLEMENT_TIME: TimeSpan
    • The default number of days required to settle a futures sale
  • DEFAULT_SETTLEMENT_DAYS: Int32
    Gets or sets whether or not this security should be considered tradable
  • IsTradable: bool
    • Returns true if this is the future chain security, false if it is a specific future contract
  • IsFutureChain: bool
    • Returns true if this is a specific future contract security, false if it is the future chain security
  • IsFutureContract: bool
    • Gets the expiration date
  • Expiry: DateTime
    • Specifies if futures contract has physical or cash settlement on settlement
  • SettlementType: SettlementType
    • Gets or sets the underlying security object.
  • Underlying: Security
    • Gets or sets the currently mapped symbol for the security
  • Mapped: Symbol
    • Gets or sets the contract filter
  • ContractFilter: IDerivativeSecurityFilter<Symbol>
    • This securities QuantConnect.Interfaces.IShortableProvider
  • ShortableProvider: IShortableProvider
    • Gets all the subscriptions for this security
  • Subscriptions: List<SubscriptionDataConfig>
    • QuantConnect.Securities.Security.Symbol for the asset.
  • Symbol: Symbol
    • Gets the Cash object used for converting the quote currency to the account currency
  • QuoteCurrency: Cash
    • Gets the symbol properties for this security
  • SymbolProperties: SymbolProperties
    • Type of the security.
  • Type: SecurityType
    • There has been at least one datapoint since our algorithm started running for us to determine price.
  • HasData: bool
    • True if the security has been delisted from exchanges and is no longer tradable
  • IsDelisted: bool
    • Data cache for the security to store previous price information.
  • Cache: SecurityCache
    • Holdings class contains the portfolio, cash and processes order fills.
  • Holdings: SecurityHolding
    • Exchange class contains the market opening hours, along with pre-post market hours.
  • Exchange: SecurityExchange
    • Fee model used to compute order fees for this security
  • FeeModel: IFeeModel
    • Fill model used to produce fill events for this security
  • FillModel: IFillModel
    • Slippage model use to compute slippage of market orders
  • SlippageModel: ISlippageModel
    • Gets the portfolio model used by this security
  • PortfolioModel: ISecurityPortfolioModel
    • Gets the buying power model used for this security
  • BuyingPowerModel: IBuyingPowerModel
    • Gets the buying power model used for this security, an alias for QuantConnect.Securities.Security.BuyingPowerModel
  • MarginModel: IBuyingPowerModel
    • Gets or sets the margin interest rate model
  • MarginInterestRateModel: IMarginInterestRateModel
    • Gets the settlement model used for this security
  • SettlementModel: ISettlementModel
    • Gets the volatility model used for this security
  • VolatilityModel: IVolatilityModel
    • Customizable data filter to filter outlier ticks before they are passed into user event handlers. By default all ticks are passed into the user algorithms.
  • DataFilter: ISecurityDataFilter
    • Customizable price variation model used to define the minimum price variation of this security. By default minimum price variation is a constant find in the symbol-properties-database.
  • PriceVariationModel: IPriceVariationModel
    • Provides dynamic access to data in the cache
  • Data: object
    • Read only property that checks if we currently own stock in the company.
  • HoldStock: bool
    • Alias for HoldStock - Do we have any of this security
  • Invested: bool
    • Local time for this market
  • LocalTime: DateTime
    • Get the current value of the security.
  • Price: decimal
    • Leverage for this Security.
  • Leverage: decimal
    • If this uses tradebar data, return the most recent high.
  • High: decimal
    • If this uses tradebar data, return the most recent low.
  • Low: decimal
    • If this uses tradebar data, return the most recent close.
  • Close: decimal
    • If this uses tradebar data, return the most recent open.
  • Open: decimal
    • Access to the volume of the equity today
  • Volume: decimal
    • Gets the most recent bid price if available
  • BidPrice: decimal
    • Gets the most recent bid size if available
  • BidSize: decimal
    • Gets the most recent ask price if available
  • AskPrice: decimal
    • Gets the most recent ask size if available
  • AskSize: decimal
    • Access to the open interest of the security today
  • OpenInterest: int
    • Gets the fundamental data associated with the security if there is any, otherwise null.
  • Fundamentals: Fundamental
    • Gets or sets the specified custom property through the indexer. This is a wrapper around the QuantConnect.Securities.Security.Get``1(System.String) and QuantConnect.Securities.Security.Add(System.String,System.Object) methods.
  • [System.String]: object
    • The default time of day for settlement
  • DefaultSettlementTime: TimeSpan
    • The default number of days required to settle a futures sale
  • DefaultSettlementDays: Int32

FuturesChain Attributes

FuturesChain objects have the following attributes:

FuturesChain
    Gets the most recent trade information for the underlying. This may be a QuantConnect.Data.Market.Tick or a QuantConnect.Data.Market.TradeBar
  • underlying: BaseData
    • Gets all ticks for every futures contract in this chain, keyed by symbol
  • ticks: Ticks
    • Gets all trade bars for every futures contract in this chain, keyed by symbol
  • trade_bars: TradeBars
    • Gets all quote bars for every futures contract in this chain, keyed by symbol
  • quote_bars: QuoteBars
    • Gets all contracts in the chain, keyed by symbol
  • contracts: FuturesContracts
    • Gets the set of symbols that passed the QuantConnect.Securities.Future.Future.ContractFilter
  • filtered_contracts: HashSet<Symbol>
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • data_type: MarketDataType
    • True if this is a fill forward piece of data
  • is_fill_forward: bool
    • Current time marker of this data packet.
  • time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • end_time: DateTime
    • Symbol representation for underlying Security
  • symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • price: decimal
    Gets the most recent trade information for the underlying. This may be a QuantConnect.Data.Market.Tick or a QuantConnect.Data.Market.TradeBar
  • Underlying: BaseData
    • Gets all ticks for every futures contract in this chain, keyed by symbol
  • Ticks: Ticks
    • Gets all trade bars for every futures contract in this chain, keyed by symbol
  • TradeBars: TradeBars
    • Gets all quote bars for every futures contract in this chain, keyed by symbol
  • QuoteBars: QuoteBars
    • Gets all contracts in the chain, keyed by symbol
  • Contracts: FuturesContracts
    • Gets the set of symbols that passed the QuantConnect.Securities.Future.Future.ContractFilter
  • FilteredContracts: HashSet<Symbol>
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • DataType: MarketDataType
    • True if this is a fill forward piece of data
  • IsFillForward: bool
    • Current time marker of this data packet.
  • Time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • EndTime: DateTime
    • Symbol representation for underlying Security
  • Symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • Value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • Price: decimal

OpenInterest Attributes

OpenInterest objects have the following attributes:

OpenInterest
    Type of the Tick: Trade or Quote.
  • tick_type: TickType
    • Quantity exchanged in a trade.
  • quantity: decimal
    • Exchange code this tick came from QuantConnect.Exchanges
  • exchange_code: string
    • Exchange name this tick came from QuantConnect.Exchanges
  • exchange: string
    • Sale condition for the tick.
  • sale_condition: string
    • For performance parsed sale condition for the tick.
  • parsed_sale_condition: UInt32
    • Bool whether this is a suspicious tick
  • suspicious: bool
    • Bid Price for Tick
  • bid_price: decimal
    • Asking price for the Tick quote.
  • ask_price: decimal
    • Alias for "Value" - the last sale for this asset.
  • last_price: decimal
    • Size of bid quote.
  • bid_size: decimal
    • Size of ask quote.
  • ask_size: decimal
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • data_type: MarketDataType
    • True if this is a fill forward piece of data
  • is_fill_forward: bool
    • Current time marker of this data packet.
  • time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • end_time: DateTime
    • Symbol representation for underlying Security
  • symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • price: decimal
    Type of the Tick: Trade or Quote.
  • TickType: TickType
    • Quantity exchanged in a trade.
  • Quantity: decimal
    • Exchange code this tick came from QuantConnect.Exchanges
  • ExchangeCode: string
    • Exchange name this tick came from QuantConnect.Exchanges
  • Exchange: string
    • Sale condition for the tick.
  • SaleCondition: string
    • For performance parsed sale condition for the tick.
  • ParsedSaleCondition: UInt32
    • Bool whether this is a suspicious tick
  • Suspicious: bool
    • Bid Price for Tick
  • BidPrice: decimal
    • Asking price for the Tick quote.
  • AskPrice: decimal
    • Alias for "Value" - the last sale for this asset.
  • LastPrice: decimal
    • Size of bid quote.
  • BidSize: decimal
    • Size of ask quote.
  • AskSize: decimal
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • DataType: MarketDataType
    • True if this is a fill forward piece of data
  • IsFillForward: bool
    • Current time marker of this data packet.
  • Time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • EndTime: DateTime
    • Symbol representation for underlying Security
  • Symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • Value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • Price: decimal

Supported Assets

The following list shows the available (162) Futures:

  • Futures.Currencies.AUD: Australian Dollar Futures (CME: 6A)
  • Futures.Currencies.AUDCAD: Australian Dollar/Canadian Dollar Futures (CME: ACD)
  • Futures.Currencies.AUDJPY: Australian Dollar/Japanese Yen Futures (CME: AJY)
  • Futures.Currencies.AUDNZD: Australian Dollar/New Zealand Dollar Futures (CME: ANE)
  • Futures.Currencies.BRL: Brazillian Real Futures (CME: 6L)
  • Futures.Currencies.BTC: Bitcoin Futures (CME: BTC)
  • Futures.Currencies.CAD: Canadian Dollar Futures (CME: 6C)
  • Futures.Currencies.CADJPY: Canadian Dollar/Japanese Yen Futures (CME: CJY)
  • Futures.Currencies.CHF: Swiss Franc Futures (CME: 6S)
  • Futures.Currencies.ETH: Ether Futures (CME: ETH)
  • Futures.Currencies.EUR: Euro FX Futures (CME: 6E)
  • Futures.Currencies.EURAUD: Euro/Australian Dollar Futures (CME: EAD)
  • Futures.Currencies.EURCAD: Euro/Canadian Dollar Futures (CME: ECD)
  • Futures.Currencies.EuroFXEminiFutures.Currencies.EURO_FX_EMINI: E-mini Euro FX Futures (CME: E7)
  • Futures.Currencies.EURSEK: Euro/Swedish Krona Futures (CME: ESK)
  • Futures.Currencies.GBP: British Pound Futures (CME: 6B)
  • Futures.Currencies.JapaneseYenEminiFutures.Currencies.JAPANESE_YEN_EMINI: E-mini Japanese Yen Futures (CME: J7)
  • Futures.Currencies.JPY: Japanese Yen Futures (CME: 6J)
  • Futures.Currencies.MicroAUDFutures.Currencies.MICRO_AUD: Micro AUD/USD Futures (CME: M6A)
  • Futures.Currencies.MicroBTCFutures.Currencies.MICRO_BTC: Micro Bitcoin Futures (CME: MBT)
  • Futures.Currencies.MicroCADFutures.Currencies.MICRO_CAD: Micro USD/CAD Futures (CME: M6C)
  • Futures.Currencies.MicroCADUSDFutures.Currencies.MICRO_CADUSD: Micro CAD/USD Futures (CME: MCD)
  • Futures.Currencies.MicroCHFFutures.Currencies.MICRO_CHF: Micro CHF/USD Futures (CME: MSF)
  • Futures.Currencies.MicroEtherFutures.Currencies.MICRO_ETHER: Micro Ether Futures (CME: MET)
  • Futures.Currencies.MicroEURFutures.Currencies.MICRO_EUR: Micro EUR/USD Futures (CME: M6E)
  • Futures.Currencies.MicroGBPFutures.Currencies.MICRO_GBP: Micro GBP/USD Futures (CME: M6B)
  • Futures.Currencies.MicroINRUSDFutures.Currencies.MICRO_INRUSD: Micro INR/USD Futures (CME: MIR)
  • Futures.Currencies.MicroJPYFutures.Currencies.MICRO_JPY: Micro JPY/USD Futures (CME: MJY)
  • Futures.Currencies.MicroUSDCHFFutures.Currencies.MICRO_USDCHF: Micro USD/CHF Futures (CME: M6S)
  • Futures.Currencies.MicroUSDCNHFutures.Currencies.MICRO_USDCNH: Micro USD/CNH Futures (CME: MNH)
  • Futures.Currencies.MicroUSDJPYFutures.Currencies.MICRO_USDJPY: Micro USD/JPY Futures (CME: M6J)
  • Futures.Currencies.MXN: Mexican Peso Futures (CME: 6M)
  • Futures.Currencies.NZD: New Zealand Dollar Futures (CME: 6N)
  • Futures.Currencies.RUB: Russian Ruble Futures (CME: 6R)
  • Futures.Currencies.StandardSizeUSDOffshoreRMBCNHFutures.Currencies.STANDARD_SIZE_USD_OFFSHORE_RMBCNH: Standard-Size USD/Offshore RMB (CNH) Futures (CME: CNH)
  • Futures.Currencies.ZAR: South African Rand Futures (CME: 6Z)
  • Futures.Dairy.CashSettledButterFutures.Dairy.CASH_SETTLED_BUTTER: Cash-settled Butter Futures (CME: CB)
  • Futures.Dairy.CashSettledCheeseFutures.Dairy.CASH_SETTLED_CHEESE: Cash-settled Cheese Futures (CME: CSC)
  • Futures.Dairy.ClassIIIMilkFutures.Dairy.CLASS_III_MILK: Class III Milk Futures (CME: DC)
  • Futures.Dairy.ClassIVMilkFutures.Dairy.CLASS_IV_MILK: Class IV Milk Futures (CME: GDK)
  • Futures.Dairy.DryWheyFutures.Dairy.DRY_WHEY: Dry Whey Futures (CME: DY)
  • Futures.Dairy.NonfatDryMilkFutures.Dairy.NONFAT_DRY_MILK: Non-fat Dry Milk Futures (CME: GNF)
  • Futures.Energy.ArgusLLSvsWTIArgusTradeMonthFutures.Energy.ARGUS_LL_SVS_WTI_ARGUS_TRADE_MONTH: Argus LLS vs. WTI (Argus) Trade Month Futures (NYMEX: AE5)
  • Futures.Energy.ArgusPropaneFarEastIndexFutures.Energy.ARGUS_PROPANE_FAR_EAST_INDEX: Argus Propane Far East Index Futures (NYMEX: A7E)
  • Futures.Energy.ArgusPropaneSaudiAramcoFutures.Energy.ARGUS_PROPANE_SAUDI_ARAMCO: Argus Propane (Saudi Aramco) Futures (NYMEX: A9N)
  • Futures.Energy.BrentCrudeOilVsDubaiCrudeOilPlattsFutures.Energy.BRENT_CRUDE_OIL_VS_DUBAI_CRUDE_OIL_PLATTS: Brent Crude Oil vs. Dubai Crude Oil (Platts) Futures (NYMEX: ADB)
  • Futures.Energy.BrentLastDayFinancialFutures.Energy.BRENT_LAST_DAY_FINANCIAL: Brent Last Day Financial Futures (NYMEX: BZ)
  • Futures.Energy.ChicagoEthanolPlattsFutures.Energy.CHICAGO_ETHANOL_PLATTS: Chicago Ethaanol (Platts) Futures (NYMEX: CU)
  • Futures.Energy.ClearbrookBakkenSweetCrudeOilMonthlyIndexNetEnergyFutures.Energy.CLEARBROOK_BAKKEN_SWEET_CRUDE_OIL_MONTHLY_INDEX_NET_ENERGY: Clearbrook Bakken Sweet Crude Oil Monthly Index (Net Energy) Futures (NYMEX: CSW)
  • Futures.Energy.ConwayPropaneOPISFutures.Energy.CONWAY_PROPANE_OPIS: Conway Propane (OPIS) Futures (NYMEX: A8K)
  • Futures.Energy.CrudeOilWTIFutures.Energy.CRUDE_OIL_WTI: Crude Oil WTI Futures (NYMEX: CL)
  • Futures.Energy.DubaiCrudeOilPlattsFinancialFutures.Energy.DUBAI_CRUDE_OIL_PLATTS_FINANCIAL: Dubai Crude Oil (Platts) Financial Futures (NYMEX: DCB)
  • Futures.Energy.EastWestGasolineSpreadPlattsArgusFutures.Energy.EAST_WEST_GASOLINE_SPREAD_PLATTS_ARGUS: East-West Gasoline Spread (Platts-Argus) Futures (NYMEX: EWG)
  • Futures.Energy.EastWestNaphthaJapanCFvsCargoesCIFNWESpreadPlattsFutures.Energy.EAST_WEST_NAPHTHA_JAPAN_C_FVS_CARGOES_CIFNWE_SPREAD_PLATTS: East-West Naphtha: Japan C&F vs. Cargoes CIF NWE Spread (Platts) Futures (NYMEX: EWN)
  • Futures.Energy.EthanolFutures.Energy.ETHANOL: Ethanol Futures (CBOT: EH)
  • Futures.Energy.EthanolT2FOBRdamIncludingDutyPlattsFutures.Energy.ETHANOL_T_2_FOB_RDAM_INCLUDING_DUTY_PLATTS: Ethanol T2 FOB Rdam Including Duty (Platts) Futures (NYMEX: AZ1)
  • Futures.Energy.EuropeanNaphthaPlattsCrackSpreadFutures.Energy.EUROPEAN_NAPHTHA_PLATTS_CRACK_SPREAD: European Naphtha (Platts) Crack Spread Futures (NYMEX: EN)
  • Futures.Energy.EuropeanPropaneCIFARAArgusFutures.Energy.EUROPEAN_PROPANE_CIFARA_ARGUS: European Propane CIF ARA (Argus) Futures (NYMEX: APS)
  • Futures.Energy.EuropeanPropaneCIFARAArgusVsNaphthaCargoesCIFNWEPlattsFutures.Energy.EUROPEAN_PROPANE_CIFARA_ARGUS_VS_NAPHTHA_CARGOES_CIFNWE_PLATTS: European Propane CIF ARA (Argus) vs. Naphtha Cargoes CIF NWE (Platts) Futures (NYMEX: EPN)
  • Futures.Energy.FreightRouteTC14BalticFutures.Energy.FREIGHT_ROUTE_TC_14_BALTIC: Freight Route TC14 (Baltic) Futures (NYMEX: FRC)
  • Futures.Energy.GasolineFutures.Energy.GASOLINE: Gasoline RBOB Futures (NYMEX: RB)
  • Futures.Energy.GasolineEurobobOxyNWEBargesArgusFutures.Energy.GASOLINE_EUROBOB_OXY_NWE_BARGES_ARGUS: Gasoline Euro-bob Oxy NWE Barges (Argus) Futures (NYMEX: B7H)
  • Futures.Energy.GroupThreeSuboctaneGasolinePlattsVsRBOBFutures.Energy.GROUP_THREE_SUBOCTANE_GASOLINE_PLATTS_VS_RBOB: Group Three Sub-octane Gasoliine (Platts) vs. RBOB Futures (NYMEX: AA8)
  • Futures.Energy.GroupThreeULSDPlattsVsNYHarborULSDFutures.Energy.GROUP_THREE_ULSD_PLATTS_VS_NY_HARBOR_ULSD: Group Three ULSD (Platts) vs. NY Harbor ULSD Futures (NYMEX: AA6)
  • Futures.Energy.GulfCoastCBOBGasolineA2PlattsVsRBOBGasolineFutures.Energy.GULF_COAST_CBOB_GASOLINE_A_2_PLATTS_VS_RBOB_GASOLINE: Gulf Coast CBOB Gasoline A2 (Platts) vs. RBOB Gasoline Futures (NYMEX: CRB)
  • Futures.Energy.GulfCoastHSFOPlattsVsEuropeanThreePointFivePercentFuelOilBargesFOBRdamPlattsFutures.Energy.GULF_COAST_HSFO_PLATTS_VS_EUROPEAN_THREE_POINT_FIVE_PERCENT_FUEL_OIL_BARGES_FOB_RDAM_PLATTS: Gulf Coast HSFO (Platts) vs. European 3.5% Fuel Oil Barges FOB Rdam (Platts) Futures (NYMEX: GCU)
  • Futures.Energy.HeatingOilFutures.Energy.HEATING_OIL: Heating Oil Futures (NYMEX: HO)
  • Futures.Energy.LosAngelesCARBOBGasolineOPISvsRBOBGasolineFutures.Energy.LOS_ANGELES_CARBOB_GASOLINE_OPI_SVS_RBOB_GASOLINE: Los Angeles CARBOB Gasoline (OPIS) vs. RBOB Gasoline Futures (NYMEX: AJL)
  • Futures.Energy.LosAngelesCARBDieselOPISvsNYHarborULSDFutures.Energy.LOS_ANGELES_CARB_DIESEL_OPI_SVS_NY_HARBOR_ULSD: Los Angeles CARB Diesel (OPIS) vs. NY Harbor ULSD Futures (NYMEX: AKL)
  • Futures.Energy.LosAngelesJetOPISvsNYHarborULSDFutures.Energy.LOS_ANGELES_JET_OPI_SVS_NY_HARBOR_ULSD: Los Angeles Jet (OPIS) vs. NY Harbor ULSD Futures (NYMEX: AJS)
  • Futures.Energy.MarsArgusVsWTIFinancialFutures.Energy.MARS_ARGUS_VS_WTI_FINANCIAL: Mars (Argus) vs. WTI Financial Futures (NYMEX: AYX)
  • Futures.Energy.MarsArgusVsWTITradeMonthFutures.Energy.MARS_ARGUS_VS_WTI_TRADE_MONTH: Mars (Argus) vs. WTI Trade Month Futures (NYMEX: AYV)
  • Futures.Energy.MicroCrudeOilWTIFutures.Energy.MICRO_CRUDE_OIL_WTI: Micro WTI Crude Oil Futures (NYMEX: MCL)
  • Futures.Energy.MicroEuropeanFOBRdamMarineFuelZeroPointFivePercentBargesPlattsFutures.Energy.MICRO_EUROPEAN_FOB_RDAM_MARINE_FUEL_ZERO_POINT_FIVE_PERCENT_BARGES_PLATTS: Micro European FOB Rdam Marine Fuel 0.5% Barges (Platts) Futures (NYMEX: R5O)
  • Futures.Energy.MicroEuropeanThreePointFivePercentOilBargesFOBRdamPlattsFutures.Energy.MICRO_EUROPEAN_THREE_POINT_FIVE_PERCENT_OIL_BARGES_FOB_RDAM_PLATTS: Micro European 3.5% Fuel Oil Barges FOB Rdam (Platts) Futures (NYMEX: MEF)
  • Futures.Energy.MicroGasoilZeroPointOnePercentBargesFOBARAPlattsFutures.Energy.MICRO_GASOIL_ZERO_POINT_ONE_PERCENT_BARGES_FOBARA_PLATTS: Micro Gasoil 0.1% Barges FOB ARA (Platts) Futures (NYMEX: M1B)
  • Futures.Energy.MicroSingaporeFOBMarineFuelZeroPointFivePercetPlattsFutures.Energy.MICRO_SINGAPORE_FOB_MARINE_FUEL_ZERO_POINT_FIVE_PERCET_PLATTS: Micro Singapore FOB Marine Fuel 0.5% (Platts) Futures (NYMEX: S5O)
  • Futures.Energy.MicroSingaporeFuelOil380CSTPlattsFutures.Energy.MICRO_SINGAPORE_FUEL_OIL_380_CST_PLATTS: Micro Singapore Fuel Oil 380CST (Platts) Futures (NYMEX: MAF)
  • Futures.Energy.MiniEuropeanThreePointPercentFiveFuelOilBargesPlattsFutures.Energy.MINI_EUROPEAN_THREE_POINT_PERCENT_FIVE_FUEL_OIL_BARGES_PLATTS: Mini European 3.5% Fuel Oil Barges FOB Rdam (Platts) Futures (NYMEX: A0D)
  • Futures.Energy.MiniSingaporeFuelOil180CstPlattsFutures.Energy.MINI_SINGAPORE_FUEL_OIL_180_CST_PLATTS: Mini Singapore Fuel Oil 180 cst (Platts) Futures (NYMEX: A0F)
  • Futures.Energy.MontBelvieuEthaneOPISFutures.Energy.MONT_BELVIEU_ETHANE_OPIS: Mont Belvieu Ethane (OPIS) Futures (NYMEX: AC0)
  • Futures.Energy.MontBelvieuLDHPropaneOPISFutures.Energy.MONT_BELVIEU_LDH_PROPANE_OPIS: Mont Belvieu LDH Propane (OPIS) Futures (NYMEX: B0)
  • Futures.Energy.MontBelvieuNaturalGasolineOPISFutures.Energy.MONT_BELVIEU_NATURAL_GASOLINE_OPIS: Mont Belvieu Natural Gasoline (OPIS) Futures (NYMEX: A7Q)
  • Futures.Energy.MontBelvieuNormalButaneOPISFutures.Energy.MONT_BELVIEU_NORMAL_BUTANE_OPIS: Mont Belvieu Normal Butane (OPIS) Futures (NYMEX: AD0)
  • Futures.Energy.NaturalGasFutures.Energy.NATURAL_GAS: Natural Gas Futures (NYMEX: NG)
  • Futures.Energy.NaturalGasHenryHubLastDayFinancialFutures.Energy.NATURAL_GAS_HENRY_HUB_LAST_DAY_FINANCIAL: Natural Gas (Henry Hub) Last-day Financial Futures (NYMEX: HH)
  • Futures.Energy.NaturalGasHenryHubPenultimateFinancialFutures.Energy.NATURAL_GAS_HENRY_HUB_PENULTIMATE_FINANCIAL: Natural Gas (Henry Hub) Penultimate Financial Futures (NYMEX: HP)
  • Futures.Energy.OnePercentFuelOilCargoesFOBNWEPlattsVsThreePointFivePercentFuelOilBargesFOBRdamPlattsFutures.Energy.ONE_PERCENT_FUEL_OIL_CARGOES_FOBNWE_PLATTS_VS_THREE_POINT_FIVE_PERCENT_FUEL_OIL_BARGES_FOB_RDAM_PLATTS: 1% Fuel Oil Cargoes FOB NWE (Platts) vs. 3.5% Fuel Oil Barges FOB Rdam (Platts) Futures (NYMEX: FSS)
  • Futures.Energy.PremiumUnleadedGasoline10ppmFOBMEDPlattsFutures.Energy.PREMIUM_UNLEADED_GASOLINE_10_PPM_FOBMED_PLATTS: Premium Unleaded Gasoline 10 ppm FOB MED (Platts) Futures (NYMEX: A3G)
  • Futures.Energy.PropaneNonLDHMontBelvieuOPISFutures.Energy.PROPANE_NON_LDH_MONT_BELVIEU_OPIS: Propane Non-LDH Mont Belvieu (OPIS) Futures (NYMEX: A1R)
  • Futures.Energy.RBOBGasolineCrackSpreadFutures.Energy.RBOB_GASOLINE_CRACK_SPREAD: RBOB Gasoline Crack Spread Futures (NYMEX: ARE)
  • Futures.Energy.RBOBGasolineVsEurobobOxyNWEBargesArgusThreeHundredFiftyThousandGallonsFutures.Energy.RBOB_GASOLINE_VS_EUROBOB_OXY_NWE_BARGES_ARGUS_THREE_HUNDRED_FIFTY_THOUSAND_GALLONS: RBOB Gasoline vs. Euro-bob Oxy NWE Barges (Argus) (350,000 gallons) Futures (NYMEX: EXR)
  • Futures.Energy.SingaporeFuelOil380cstPlattsVsEuropeanThreePointFivePercentFuelOilBargesFOBRdamPlattsFutures.Energy.SINGAPORE_FUEL_OIL_380_CST_PLATTS_VS_EUROPEAN_THREE_POINT_FIVE_PERCENT_FUEL_OIL_BARGES_FOB_RDAM_PLATTS: Singapore Fuel Oil 380 cst (Platts) vs. European 3.5% Fuel Oil Barges FOB Rdam (Platts) Futures (NYMEX: EVC)
  • Futures.Energy.SingaporeGasoilPlattsVsLowSulphurGasoilFuturesFutures.Energy.SINGAPORE_GASOIL_PLATTS_VS_LOW_SULPHUR_GASOIL_FUTURES: Singapore Gasoil (Platts) vs. Low Sulphur Gasoil Futures (NYMEX: AGA)
  • Futures.Energy.SingaporeMogas92UnleadedPlattsBrentCrackSpreadFutures.Energy.SINGAPORE_MOGAS_92_UNLEADED_PLATTS_BRENT_CRACK_SPREAD: Singapore Mogas 92 Unleaded (Platts) Brent Crack Spread Futures (NYMEX: D1N)
  • Futures.Energy.ThreePointFivePercentFuelOilBargesFOBRdamPlattsCrackSpreadFutures.Energy.THREE_POINT_FIVE_PERCENT_FUEL_OIL_BARGES_FOB_RDAM_PLATTS_CRACK_SPREAD: 3.5% Fuel Oil Barges FOB Rdam (Platts) Crack Spread Futures (NYMEX: FO)
  • Futures.Energy.ThreePointFivePercentFuelOilBargesFOBRdamPlattsCrackSpread1000mtFutures.Energy.THREE_POINT_FIVE_PERCENT_FUEL_OIL_BARGES_FOB_RDAM_PLATTS_CRACK_SPREAD_1000_MT: 3.5% Fuel Oil Barges FOB Rdam (Platts) Crack Spread (1000mt) Futures (NYMEX: BOO)
  • Futures.Energy.WTIBrentFinancialFutures.Energy.WTI_BRENT_FINANCIAL: WTI-Brent Financial Futures (NYMEX: BK)
  • Futures.Energy.WTIFinancialFutures.Energy.WTI_FINANCIAL: WTI Financial Futures (NYMEX: CSX)
  • Futures.Energy.WTIHoustonArgusVsWTITradeMonthFutures.Energy.WTI_HOUSTON_ARGUS_VS_WTI_TRADE_MONTH: WTI Houston (Argus) vs. WTI Trade Month Futures (NYMEX: HTT)
  • Futures.Energy.WTIHoustonCrudeOilFutures.Energy.WTI_HOUSTON_CRUDE_OIL: WTI Houston Crude Oil Futures (NYMEX: HCL)
  • Futures.Financials.EuroDollarFutures.Financials.EURO_DOLLAR: EuroDollar Futures (CME: GE)
  • Futures.Financials.FiveYearUSDMACSwapFutures.Financials.FIVE_YEAR_USDMAC_SWAP: 5-Year USD MAC Swap Futures (CBOT: F1U)
  • Futures.Financials.MicroY10TreasuryNoteFutures.Financials.MICRO_Y_10_TREASURY_NOTE: Micro 10-Year Yield Futures (CBOT: 10Y)
  • Futures.Financials.MicroY2TreasuryBondFutures.Financials.MICRO_Y_2_TREASURY_BOND: Micro 2-Year Yield Futures (CBOT: 2YY)
  • Futures.Financials.MicroY30TreasuryBondFutures.Financials.MICRO_Y_30_TREASURY_BOND: Micro 30-Year Yield Futures (CBOT: 30Y)
  • Futures.Financials.MicroY5TreasuryBondFutures.Financials.MICRO_Y_5_TREASURY_BOND: Micro 5-Year Yield Futures (CBOT: 5YY)
  • Futures.Financials.UltraTenYearUSTreasuryNoteFutures.Financials.ULTRA_TEN_YEAR_US_TREASURY_NOTE: Ultra 10-Year U.S. Treasury Note Futures (CBOT: TN)
  • Futures.Financials.UltraUSTreasuryBondFutures.Financials.ULTRA_US_TREASURY_BOND: Ultra U.S. Treasury Bond Futures (CBOT: UB)
  • Futures.Financials.Y10TreasuryNoteFutures.Financials.Y_10_TREASURY_NOTE: 10Y U.S. Treasury Note Futures (CBOT: ZN)
  • Futures.Financials.Y2TreasuryNoteFutures.Financials.Y_2_TREASURY_NOTE: 2Y U.S. Treasury Note Futures (CBOT: ZT)
  • Futures.Financials.Y30TreasuryBondFutures.Financials.Y_30_TREASURY_BOND: 30Y U.S. Treasury Bond Futures (CBOT: ZB)
  • Futures.Financials.Y5TreasuryNoteFutures.Financials.Y_5_TREASURY_NOTE: 5Y U.S. Treasury Note Futures (CBOT: ZF)
  • Futures.Forestry.LumberFutures.Forestry.LUMBER: Lumber Futures (CME: LBR)
  • Futures.Forestry.RandomLengthLumberFutures.Forestry.RANDOM_LENGTH_LUMBER: Random Length Lumber Futures (CME: LBS)
  • Futures.Grains.BlackSeaCornFinanciallySettledPlattsFutures.Grains.BLACK_SEA_CORN_FINANCIALLY_SETTLED_PLATTS: Black Sea Corn Financially Settled (Platts) Futures (CBOT: BCF)
  • Futures.Grains.BlackSeaWheatFinanciallySettledPlattsFutures.Grains.BLACK_SEA_WHEAT_FINANCIALLY_SETTLED_PLATTS: Black Sea Wheat Financially Settled (Platts) Futures (CBOT: BWF)
  • Futures.Grains.CornFutures.Grains.CORN: Corn Futures (CBOT: ZC)
  • Futures.Grains.HRWWheatFutures.Grains.HRW_WHEAT: KC HRW Wheat Futures (CBOT: KE)
  • Futures.Grains.OatsFutures.Grains.OATS: Oats Futures (CBOT: ZO)
  • Futures.Grains.SoybeansFutures.Grains.SOYBEANS: Soybeans Futures (CBOT: ZS)
  • Futures.Grains.SoybeanMealFutures.Grains.SOYBEAN_MEAL: Soybean Meal Futures (CBOT: ZM)
  • Futures.Grains.SoybeanOilFutures.Grains.SOYBEAN_OIL: Soybean Oil Futures (CBOT: ZL)
  • Futures.Grains.WheatFutures.Grains.WHEAT: Default wheat contract is SRWWheat (CBOT: ZW)
  • Futures.Indices.BloombergCommodityIndexFutures.Indices.BLOOMBERG_COMMODITY_INDEX: Bloomberg Commodity Index Futures (CBOT: AW)
  • Futures.Indices.Dow30EMiniFutures.Indices.DOW_30_E_MINI: E-mini Dow Indu 30 Futures (CBOT: YM)
  • Futures.Indices.DowJonesRealEstateFutures.Indices.DOW_JONES_REAL_ESTATE: (CME: RX)
  • Futures.Indices.FTSEEmergingEminiFutures.Indices.FTSE_EMERGING_EMINI: E-mini FTSE Emerging Index Futures (CME: EI)
  • Futures.Indices.MicroDow30EMiniFutures.Indices.MICRO_DOW_30_E_MINI: Micro E-mini Dow Jones Industrial Average Index Futures (CBOT: MYM)
  • Futures.Indices.MicroNASDAQ100EMiniFutures.Indices.MICRO_NASDAQ_100_E_MINI: Micro E-mini Nasdaq-100 Index Futures (CME: MNQ)
  • Futures.Indices.MicroRussell2000EMiniFutures.Indices.MICRO_RUSSELL_2000_E_MINI: Micro E-mini Russell 2000 Index Futures (CME: M2K)
  • Futures.Indices.MicroSP500EMiniFutures.Indices.MICRO_SP_500_E_MINI: Micro E-mini S&P 500 Index Futures (CME: MES)
  • Futures.Indices.NASDAQ100BiotechnologyEMiniFutures.Indices.NASDAQ_100_BIOTECHNOLOGY_E_MINI: E-mini Nasdaq-100 Biotechnology Index Futures (CME: BIO)
  • Futures.Indices.NASDAQ100EMiniFutures.Indices.NASDAQ_100_E_MINI: E-mini NASDAQ 100 Futures (CME: NQ)
  • Futures.Indices.Nikkei225DollarFutures.Indices.NIKKEI_225_DOLLAR: Nikkei-225 Dollar Futures (CME: NKD)
  • Futures.Indices.Nikkei225YenCMEFutures.Indices.NIKKEI_225_YEN_CME: Nikkei-225 Yen denominated Futures on CME (CME: NIY)
  • Futures.Indices.Russell1000EMiniFutures.Indices.RUSSELL_1000_E_MINI: (CME: RS1)
  • Futures.Indices.Russell2000EMiniFutures.Indices.RUSSELL_2000_E_MINI: E-mini Russell 2000 Futures (CME: RTY)
  • Futures.Indices.SPGSCICommodityFutures.Indices.SPGSCI_COMMODITY: S&P-GSCI Commodity Index Futures (CME: GD)
  • Futures.Indices.SP400MidCapEminiFutures.Indices.SP_400_MID_CAP_EMINI: E-mini S&P MidCap 400 Futures (CME: EMD)
  • Futures.Indices.SP500AnnualDividendIndexFutures.Indices.SP_500_ANNUAL_DIVIDEND_INDEX: (CME: SDA)
  • Futures.Indices.SP500EMiniFutures.Indices.SP_500_E_MINI: E-mini S&P 500 Futures (CME: ES)
  • Futures.Indices.TOPIXYEN: (CME: TPY)
  • Futures.Indices.USDDenominatedIbovespaFutures.Indices.USD_DENOMINATED_IBOVESPA: USD-Denominated Ibovespa Index Futures (CME: IBV)
  • Futures.Indices.VIX: CBOE Volatility Index Futures (CFE: VX)
  • Futures.Meats.FeederCattleFutures.Meats.FEEDER_CATTLE: Feeder Cattle Futures (CME: GF)
  • Futures.Meats.LeanHogsFutures.Meats.LEAN_HOGS: Lean Hogs Futures (CME: HE)
  • Futures.Meats.LiveCattleFutures.Meats.LIVE_CATTLE: Live Cattle Futures (CME: LE)
  • Futures.Metals.AluminiumEuropeanPremiumDutyPaidMetalBulletinFutures.Metals.ALUMINIUM_EUROPEAN_PREMIUM_DUTY_PAID_METAL_BULLETIN: Aluminium European Premium Duty-Paid (Metal Bulletin) Futures (COMEX: EDP)
  • Futures.Metals.AluminumMWUSTransactionPremiumPlatts25MTFutures.Metals.ALUMINUM_MWUS_TRANSACTION_PREMIUM_PLATTS_25_MT: Aluminum MW U.S. Transaction Premium Platts (25MT) Futures (COMEX: AUP)
  • Futures.Metals.CopperFutures.Metals.COPPER: Copper Futures (COMEX: HG)
  • Futures.Metals.GoldFutures.Metals.GOLD: Gold Futures (COMEX: GC)
  • Futures.Metals.MicroGoldFutures.Metals.MICRO_GOLD: Micro Gold Futures (COMEX: MGC)
  • Futures.Metals.MicroGoldTASFutures.Metals.MICRO_GOLD_TAS: Micro Gold TAS Futures (COMEX: MGT)
  • Futures.Metals.MicroPalladiumFutures.Metals.MICRO_PALLADIUM: Micro Palladium Futures (NYMEX: PAM)
  • Futures.Metals.MicroSilverFutures.Metals.MICRO_SILVER: Micro Silver Futures (COMEX: SIL)
  • Futures.Metals.PalladiumFutures.Metals.PALLADIUM: Palladium Futures (NYMEX: PA)
  • Futures.Metals.PlatinumFutures.Metals.PLATINUM: Platinum Futures (NYMEX: PL)
  • Futures.Metals.SilverFutures.Metals.SILVER: Silver Futures (COMEX: SI)
  • Futures.Metals.USMidwestDomesticHotRolledCoilSteelCRUIndexFutures.Metals.US_MIDWEST_DOMESTIC_HOT_ROLLED_COIL_STEEL_CRU_INDEX: U.S. Midwest Domestic Hot-Rolled Coil Steel (CRU) Index Futures (NYMEX: HRC)
  • Futures.Softs.Sugar11Futures.Softs.SUGAR_11: Sugar #11 Futures ICE (ICE: SB)
  • Futures.Softs.Sugar11CMEFutures.Softs.SUGAR_11_CME: Sugar #11 Futures CME (NYMEX: YO)

 

Requesting Data

To add US Futures data to your algorithm, call the AddFutureadd_future method. Save a reference to the Future so you can access the data later in your algorithm.

Select Language: 
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
        # Request Gold Future data
        future = self.add_future(Futures.Metals.GOLD) 
        # Set filter to obtain the contracts expire within 90 days
        future.set_filter(0, 90)
        self.future_symbol = future.symbol
namespace QuantConnect
{
    public class USFuturesDataAlgorithm : QCAlgorithm
    {
        private Symbol _futureSymbol;
        
        public override void Initialize()
        {
            SetStartDate(2013, 12, 20);
            SetEndDate(2014, 2, 20);
            SetCash(1000000);
            UniverseSettings.Asynchronous = true;
            // Request Gold Future data
            var future = AddFuture(Futures.Metals.Gold);
            // Set filter to obtain the contracts expire within 90 days
            future.SetFilter(0, 90);
            _futureSymbol = future.Symbol;
        }
    }
}

For more information about creating Future subscriptions, see Requesting Data or Futures Universes.

Accessing Data

To get the current US Futures data, index the Barsbars, QuoteBarsquote_bars, or Ticksticks properties of the current Slice with the Future Symbol. Slice objects deliver unique events to your algorithm as they happen, but the Slice may not contain data for your security at every time step. To avoid issues, check if the Slice contains the data you want before you index it.

Select Language: 
def on_data(self, slice: Slice) -> None:
    # Access data: TradeBar data
    if self.future_symbol in slice.bars:
        trade_bar = slice.bars[self.future_symbol]
        self.log(f"{self.future_symbol} close at {slice.time}: {trade_bar.close}")

    # Access data: QuoteBar data
    if self.future_symbol in slice.quote_bars:
        quote_bar = slice.quote_bars[self.future_symbol]
        self.log(f"{self.future_symbol} bid at {slice.time}: {quote_bar.bid.close}")

    # Access data: Ticks data
    if self.future_symbol in slice.ticks:
        ticks = slice.ticks[self.future_symbol]
        for tick in ticks:
            self.log(f"{self.future_symbol} price at {slice.time}: {tick.price}")
public override void OnData(Slice slice)
{
    // Access data: TradeBar data
    if (slice.Bars.TryGetValue(_futureSymbol, out var tradeBar))
    {
        Log($"{_futureSymbol} price at {slice.Time}: {tradeBar.Close}");
    }

    // Access data: QuoteBar data
    if (slice.QuoteBars.TryGetValue(_futureSymbol, out var quoteBar))
    {
        Log($"{_futureSymbol} bid at {slice.Time}: {quoteBar.Bid.Close}");
    }

    // Access data: Ticks data
    if (slice.Ticks.TryGetValue(_futureSymbol, out var ticks))
    {
        foreach (var tick in ticks)
        {
            Log($"{_futureSymbol} price at {slice.Time}: {tick.Price}");
        }
    }
}

You can also iterate through all of the data objects in the current Slice.

Select Language: 
def on_data(self, slice: Slice) -> None:
    # Iterate all TradeBar received
    for symbol, trade_bar in slice.bars.items():
        self.log(f"{symbol} close at {slice.time}: {trade_bar.close}")

    # Iterate all QuoteBar received
    for symbol, quote_bar in slice.quote_bars.items():
        self.log(f"{symbol} bid at {slice.time}: {quote_bar.bid.close}")

    # Iterate all Ticks received
    for symbol, ticks in slice.ticks.items():
        for tick in ticks:
            self.log(f"{symbol} price at {slice.time}: {tick.price}")
public override void OnData(Slice slice)
{
    // Iterate all TradeBar received
    foreach (var kvp in slice.Bars)
    {
        var symbol = kvp.Key;
        var tradeBar = kvp.Value;
        Log($"{symbol} price at {slice.Time}: {tradeBar.Close}");
    }

    // Iterate all QuoteBar received
    foreach (var kvp in slice.QuoteBars)
    {
        var symbol = kvp.Key;
        var quoteBar = kvp.Value;
        Log($"{symbol} bid at {slice.Time}: {quoteBar.Bid.Close}");
    }

    // Iterate all Ticks received
    foreach (var kvp in slice.Ticks)
    {
        var symbol = kvp.Key;
        var ticks = kvp.Value;
        foreach (var tick in ticks)
        {
            Log($"{symbol} price at {slice.Time}: {tick.Price}");
        }
    }
}

For more information about accessing US Futures data, see Handling Data.

Historical Data

You can get historical US Futures data in an algorithm and the Research Environment.

Historical Data In Algorithms

To get historical US Futures data in an algorithm, call the Historyhistory method with the canonical Futures Symbol or a Futures contract Symbol. If there is no data in the period you request, the history result is empty.

Select Language: 
# DataFrame objects
contract_history_df = self.history(contract.symbol, 100, Resolution.MINUTE)
continuous_history_df = self.history(self.future_symbol,
    start=self.time - timedelta(days=15), 
    end=self.time, 
    resolution=Resolution.MINUTE, 
    fill_forward=False, 
    extended_market_hours=False,
    data_mapping_mode=DataMappingMode.OPEN_INTEREST, 
    data_normalization_mode=DataNormalizationMode.RAW, 
    contract_depth_offset=0)

# TradeBar objects
contract_history_trade_bars = self.history[TradeBar](contract.symbol, 100, Resolution.MINUTE)
continous_history_trade_bars = self.history[TradeBar](self.future_symbol, 100, Resolution.MINUTE)

# QuoteBar objects
contract_history_quote_bars = self.history[QuoteBar](contract.symbol, 100, Resolution.MINUTE)
continous_history_quote_bars = self.history[QuoteBar](self.future_symbol, 100, Resolution.MINUTE)

# Tick objects
contract_history_ticks = self.history[Tick](contract.symbol, timedelta(seconds=10), Resolution.TICK)
continous_history_ticks = self.history[Tick](self.future_symbol, timedelta(seconds=10), Resolution.TICK)
// TradeBar objects
var contractHistoryTradeBars = History(contract.Symbol, 100, Resolution.Minute);
var continuousHistoryTradeBars = History(
    symbols: new[] {_futureSymbol}, 
    start: Time - TimeSpan.FromDays(15),
    end: Time,
    resolution: Resolution.Minute,
    fillForward: false,
    extendedMarketHours: false,
    dataMappingMode: DataMappingMode.OpenInterest,
    dataNormalizationMode: DataNormalizationMode.Raw,
    contractDepthOffset: 0);

// QuoteBar objects
var contractHistoryQuoteBars = History<QuoteBar>(contract.Symbol, 100, Resolution.Minute);
var continuousHistoryQuoteBars = History<QuoteBar>(_futureSymbol, 100, Resolution.Minute);

// Tick objects
var contractHistoryTicks = History<Tick>(contract.Symbol, TimeSpan.FromSeconds(10), Resolution.Tick);
var continuousHistoryTicks = History<Tick>(_futureSymbol, TimeSpan.FromSeconds(10), Resolution.Tick);

For more information about historical data in algorithms, see History Requests. For more information about the price adjustments for continuous contracts, see Continous Contracts.

Historical Data In Research

To get historical US Futures data in the Research Environment for an entire Futures chain, call the FutureHistoryfuture_history method with the canonical Future Symbol.

Select Language: 
qb = QuantBook()
future = qb.add_future(Futures.Metals.GOLD) 
future.set_filter(0, 90)
history = qb.future_history(future.symbol, datetime(2020, 6, 1), datetime(2020, 6, 5))
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.Metals.Gold);
future.SetFilter(0, 90);
var history = qb.FutureHistory(future.Symbol, new DateTime(2020, 6, 1), new DateTime(2020, 6, 5));
    
var contracts = history.SelectMany(x => x.OptionChains.SelectMany(y => y.Value.Contracts.Keys)).Distinct().ToList();
var expiries = contracts.Select(x => x.ID.Date).Distinct().ToList();

To get historical data for a single US Futures contract or the continuous Futures contract, call the Historyhistory method like you would in an algorithm but on the QuantBook object. For more information about historical data in the Research Environment, see Futures.

Data Point Attributes

The US Futures dataset provides FuturesChain, Future, and OpenInterest objects. To configure the continuous Future settings, use the DataNormalizationMode and DataMappingMode enumerations.

DataNormalizationMode Values

The DataNormalizationMode enumeration has the following values:

DataNormalizationMode
    No modifications to the asset price at all. For Equities, dividends are paid in cash and splits are applied directly to your portfolio quantity. (0)
  • RAW: DataNormalizationMode
    • Splits and dividends are backward-adjusted into the price of the asset. The price today is identical to the current market price. (1)
  • ADJUSTED: DataNormalizationMode
    • Equity splits are applied to the price adjustment but dividends are paid in cash to your portfolio. This normalization mode allows you to manage dividend payments (e.g. reinvestment) while still giving a smooth time series of prices for indicators. (2)
  • SPLIT_ADJUSTED: DataNormalizationMode
    • Equity splits are applied to the price adjustment and the value of all future dividend payments is added to the initial asset price. (3)
  • TOTAL_RETURN: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The first contract has the true price. Factor 0. (4)
  • FORWARD_PANAMA_CANAL: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The last contract has the true price. Factor 0. (5)
  • BACKWARDS_PANAMA_CANAL: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, multiplying the prices by their ratio. The last contract has the true price. Factor 1. (6)
  • BACKWARDS_RATIO: DataNormalizationMode
    • Splits and dividends are adjusted into the prices in a given date. Only for history requests. (7)
  • SCALED_RAW: DataNormalizationMode
    No modifications to the asset price at all. For Equities, dividends are paid in cash and splits are applied directly to your portfolio quantity. (0)
  • Raw: DataNormalizationMode
    • Splits and dividends are backward-adjusted into the price of the asset. The price today is identical to the current market price. (1)
  • Adjusted: DataNormalizationMode
    • Equity splits are applied to the price adjustment but dividends are paid in cash to your portfolio. This normalization mode allows you to manage dividend payments (e.g. reinvestment) while still giving a smooth time series of prices for indicators. (2)
  • SplitAdjusted: DataNormalizationMode
    • Equity splits are applied to the price adjustment and the value of all future dividend payments is added to the initial asset price. (3)
  • TotalReturn: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The first contract has the true price. Factor 0. (4)
  • ForwardPanamaCanal: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, adding a factor based on the difference of their prices. The last contract has the true price. Factor 0. (5)
  • BackwardsPanamaCanal: DataNormalizationMode
    • Eliminates price jumps between two consecutive contracts, multiplying the prices by their ratio. The last contract has the true price. Factor 1. (6)
  • BackwardsRatio: DataNormalizationMode
    • Splits and dividends are adjusted into the prices in a given date. Only for history requests. (7)
  • ScaledRaw: DataNormalizationMode

DataMappingMode Values

The DataMappingMode enumeration has the following values:

DataMappingMode
    The contract maps on the previous day of expiration of the front month (0)
  • LAST_TRADING_DAY: DataMappingMode
    • The contract maps on the first date of the delivery month of the front month. If the contract expires prior to this date, then it rolls on the contract's last trading date instead (1)
  • FIRST_DAY_MONTH: DataMappingMode
    • The contract maps when the following back month contract has a higher open interest that the current front month (2)
  • OPEN_INTEREST: DataMappingMode
    • The contract maps when any of the back month contracts of the next year have a higher volume that the current front month (3)
  • OPEN_INTEREST_ANNUAL: DataMappingMode
    The contract maps on the previous day of expiration of the front month (0)
  • LastTradingDay: DataMappingMode
    • The contract maps on the first date of the delivery month of the front month. If the contract expires prior to this date, then it rolls on the contract's last trading date instead (1)
  • FirstDayMonth: DataMappingMode
    • The contract maps when the following back month contract has a higher open interest that the current front month (2)
  • OpenInterest: DataMappingMode
    • The contract maps when any of the back month contracts of the next year have a higher volume that the current front month (3)
  • OpenInterestAnnual: DataMappingMode

Future Attributes

Future objects have the following attributes:

Future
    Gets or sets whether or not this security should be considered tradable
  • is_tradable: bool
    • Returns true if this is the future chain security, false if it is a specific future contract
  • is_future_chain: bool
    • Returns true if this is a specific future contract security, false if it is the future chain security
  • is_future_contract: bool
    • Gets the expiration date
  • expiry: DateTime
    • Specifies if futures contract has physical or cash settlement on settlement
  • settlement_type: SettlementType
    • Gets or sets the underlying security object.
  • underlying: Security
    • Gets or sets the currently mapped symbol for the security
  • mapped: Symbol
    • Gets or sets the contract filter
  • contract_filter: IDerivativeSecurityFilter<Symbol>
    • This securities QuantConnect.Interfaces.IShortableProvider
  • shortable_provider: IShortableProvider
    • Gets all the subscriptions for this security
  • subscriptions: List<SubscriptionDataConfig>
    • QuantConnect.Securities.Security.Symbol for the asset.
  • symbol: Symbol
    • Gets the Cash object used for converting the quote currency to the account currency
  • quote_currency: Cash
    • Gets the symbol properties for this security
  • symbol_properties: SymbolProperties
    • Type of the security.
  • type: SecurityType
    • There has been at least one datapoint since our algorithm started running for us to determine price.
  • has_data: bool
    • True if the security has been delisted from exchanges and is no longer tradable
  • is_delisted: bool
    • Data cache for the security to store previous price information.
  • cache: SecurityCache
    • Holdings class contains the portfolio, cash and processes order fills.
  • holdings: SecurityHolding
    • Exchange class contains the market opening hours, along with pre-post market hours.
  • exchange: SecurityExchange
    • Fee model used to compute order fees for this security
  • fee_model: IFeeModel
    • Fill model used to produce fill events for this security
  • fill_model: IFillModel
    • Slippage model use to compute slippage of market orders
  • slippage_model: ISlippageModel
    • Gets the portfolio model used by this security
  • portfolio_model: ISecurityPortfolioModel
    • Gets the buying power model used for this security
  • buying_power_model: IBuyingPowerModel
    • Gets the buying power model used for this security, an alias for QuantConnect.Securities.Security.BuyingPowerModel
  • margin_model: IBuyingPowerModel
    • Gets or sets the margin interest rate model
  • margin_interest_rate_model: IMarginInterestRateModel
    • Gets the settlement model used for this security
  • settlement_model: ISettlementModel
    • Gets the volatility model used for this security
  • volatility_model: IVolatilityModel
    • Customizable data filter to filter outlier ticks before they are passed into user event handlers. By default all ticks are passed into the user algorithms.
  • data_filter: ISecurityDataFilter
    • Customizable price variation model used to define the minimum price variation of this security. By default minimum price variation is a constant find in the symbol-properties-database.
  • price_variation_model: IPriceVariationModel
    • Provides dynamic access to data in the cache
  • data: object
    • Read only property that checks if we currently own stock in the company.
  • hold_stock: bool
    • Alias for HoldStock - Do we have any of this security
  • invested: bool
    • Local time for this market
  • local_time: DateTime
    • Get the current value of the security.
  • price: decimal
    • Leverage for this Security.
  • leverage: decimal
    • If this uses tradebar data, return the most recent high.
  • high: decimal
    • If this uses tradebar data, return the most recent low.
  • low: decimal
    • If this uses tradebar data, return the most recent close.
  • close: decimal
    • If this uses tradebar data, return the most recent open.
  • open: decimal
    • Access to the volume of the equity today
  • volume: decimal
    • Gets the most recent bid price if available
  • bid_price: decimal
    • Gets the most recent bid size if available
  • bid_size: decimal
    • Gets the most recent ask price if available
  • ask_price: decimal
    • Gets the most recent ask size if available
  • ask_size: decimal
    • Access to the open interest of the security today
  • open_interest: int
    • Gets the fundamental data associated with the security if there is any, otherwise null.
  • fundamentals: Fundamental
    • Gets or sets the specified custom property through the indexer. This is a wrapper around the QuantConnect.Securities.Security.Get``1(System.String) and QuantConnect.Securities.Security.Add(System.String,System.Object) methods.
  • item: object
    • The default time of day for settlement
  • DEFAULT_SETTLEMENT_TIME: TimeSpan
    • The default number of days required to settle a futures sale
  • DEFAULT_SETTLEMENT_DAYS: Int32
    Gets or sets whether or not this security should be considered tradable
  • IsTradable: bool
    • Returns true if this is the future chain security, false if it is a specific future contract
  • IsFutureChain: bool
    • Returns true if this is a specific future contract security, false if it is the future chain security
  • IsFutureContract: bool
    • Gets the expiration date
  • Expiry: DateTime
    • Specifies if futures contract has physical or cash settlement on settlement
  • SettlementType: SettlementType
    • Gets or sets the underlying security object.
  • Underlying: Security
    • Gets or sets the currently mapped symbol for the security
  • Mapped: Symbol
    • Gets or sets the contract filter
  • ContractFilter: IDerivativeSecurityFilter<Symbol>
    • This securities QuantConnect.Interfaces.IShortableProvider
  • ShortableProvider: IShortableProvider
    • Gets all the subscriptions for this security
  • Subscriptions: List<SubscriptionDataConfig>
    • QuantConnect.Securities.Security.Symbol for the asset.
  • Symbol: Symbol
    • Gets the Cash object used for converting the quote currency to the account currency
  • QuoteCurrency: Cash
    • Gets the symbol properties for this security
  • SymbolProperties: SymbolProperties
    • Type of the security.
  • Type: SecurityType
    • There has been at least one datapoint since our algorithm started running for us to determine price.
  • HasData: bool
    • True if the security has been delisted from exchanges and is no longer tradable
  • IsDelisted: bool
    • Data cache for the security to store previous price information.
  • Cache: SecurityCache
    • Holdings class contains the portfolio, cash and processes order fills.
  • Holdings: SecurityHolding
    • Exchange class contains the market opening hours, along with pre-post market hours.
  • Exchange: SecurityExchange
    • Fee model used to compute order fees for this security
  • FeeModel: IFeeModel
    • Fill model used to produce fill events for this security
  • FillModel: IFillModel
    • Slippage model use to compute slippage of market orders
  • SlippageModel: ISlippageModel
    • Gets the portfolio model used by this security
  • PortfolioModel: ISecurityPortfolioModel
    • Gets the buying power model used for this security
  • BuyingPowerModel: IBuyingPowerModel
    • Gets the buying power model used for this security, an alias for QuantConnect.Securities.Security.BuyingPowerModel
  • MarginModel: IBuyingPowerModel
    • Gets or sets the margin interest rate model
  • MarginInterestRateModel: IMarginInterestRateModel
    • Gets the settlement model used for this security
  • SettlementModel: ISettlementModel
    • Gets the volatility model used for this security
  • VolatilityModel: IVolatilityModel
    • Customizable data filter to filter outlier ticks before they are passed into user event handlers. By default all ticks are passed into the user algorithms.
  • DataFilter: ISecurityDataFilter
    • Customizable price variation model used to define the minimum price variation of this security. By default minimum price variation is a constant find in the symbol-properties-database.
  • PriceVariationModel: IPriceVariationModel
    • Provides dynamic access to data in the cache
  • Data: object
    • Read only property that checks if we currently own stock in the company.
  • HoldStock: bool
    • Alias for HoldStock - Do we have any of this security
  • Invested: bool
    • Local time for this market
  • LocalTime: DateTime
    • Get the current value of the security.
  • Price: decimal
    • Leverage for this Security.
  • Leverage: decimal
    • If this uses tradebar data, return the most recent high.
  • High: decimal
    • If this uses tradebar data, return the most recent low.
  • Low: decimal
    • If this uses tradebar data, return the most recent close.
  • Close: decimal
    • If this uses tradebar data, return the most recent open.
  • Open: decimal
    • Access to the volume of the equity today
  • Volume: decimal
    • Gets the most recent bid price if available
  • BidPrice: decimal
    • Gets the most recent bid size if available
  • BidSize: decimal
    • Gets the most recent ask price if available
  • AskPrice: decimal
    • Gets the most recent ask size if available
  • AskSize: decimal
    • Access to the open interest of the security today
  • OpenInterest: int
    • Gets the fundamental data associated with the security if there is any, otherwise null.
  • Fundamentals: Fundamental
    • Gets or sets the specified custom property through the indexer. This is a wrapper around the QuantConnect.Securities.Security.Get``1(System.String) and QuantConnect.Securities.Security.Add(System.String,System.Object) methods.
  • [System.String]: object
    • The default time of day for settlement
  • DefaultSettlementTime: TimeSpan
    • The default number of days required to settle a futures sale
  • DefaultSettlementDays: Int32

FuturesChain Attributes

FuturesChain objects have the following attributes:

FuturesChain
    Gets the most recent trade information for the underlying. This may be a QuantConnect.Data.Market.Tick or a QuantConnect.Data.Market.TradeBar
  • underlying: BaseData
    • Gets all ticks for every futures contract in this chain, keyed by symbol
  • ticks: Ticks
    • Gets all trade bars for every futures contract in this chain, keyed by symbol
  • trade_bars: TradeBars
    • Gets all quote bars for every futures contract in this chain, keyed by symbol
  • quote_bars: QuoteBars
    • Gets all contracts in the chain, keyed by symbol
  • contracts: FuturesContracts
    • Gets the set of symbols that passed the QuantConnect.Securities.Future.Future.ContractFilter
  • filtered_contracts: HashSet<Symbol>
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • data_type: MarketDataType
    • True if this is a fill forward piece of data
  • is_fill_forward: bool
    • Current time marker of this data packet.
  • time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • end_time: DateTime
    • Symbol representation for underlying Security
  • symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • price: decimal
    Gets the most recent trade information for the underlying. This may be a QuantConnect.Data.Market.Tick or a QuantConnect.Data.Market.TradeBar
  • Underlying: BaseData
    • Gets all ticks for every futures contract in this chain, keyed by symbol
  • Ticks: Ticks
    • Gets all trade bars for every futures contract in this chain, keyed by symbol
  • TradeBars: TradeBars
    • Gets all quote bars for every futures contract in this chain, keyed by symbol
  • QuoteBars: QuoteBars
    • Gets all contracts in the chain, keyed by symbol
  • Contracts: FuturesContracts
    • Gets the set of symbols that passed the QuantConnect.Securities.Future.Future.ContractFilter
  • FilteredContracts: HashSet<Symbol>
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • DataType: MarketDataType
    • True if this is a fill forward piece of data
  • IsFillForward: bool
    • Current time marker of this data packet.
  • Time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • EndTime: DateTime
    • Symbol representation for underlying Security
  • Symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • Value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • Price: decimal

OpenInterest Attributes

OpenInterest objects have the following attributes:

OpenInterest
    Type of the Tick: Trade or Quote.
  • tick_type: TickType
    • Quantity exchanged in a trade.
  • quantity: decimal
    • Exchange code this tick came from QuantConnect.Exchanges
  • exchange_code: string
    • Exchange name this tick came from QuantConnect.Exchanges
  • exchange: string
    • Sale condition for the tick.
  • sale_condition: string
    • For performance parsed sale condition for the tick.
  • parsed_sale_condition: UInt32
    • Bool whether this is a suspicious tick
  • suspicious: bool
    • Bid Price for Tick
  • bid_price: decimal
    • Asking price for the Tick quote.
  • ask_price: decimal
    • Alias for "Value" - the last sale for this asset.
  • last_price: decimal
    • Size of bid quote.
  • bid_size: decimal
    • Size of ask quote.
  • ask_size: decimal
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • data_type: MarketDataType
    • True if this is a fill forward piece of data
  • is_fill_forward: bool
    • Current time marker of this data packet.
  • time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • end_time: DateTime
    • Symbol representation for underlying Security
  • symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • price: decimal
    Type of the Tick: Trade or Quote.
  • TickType: TickType
    • Quantity exchanged in a trade.
  • Quantity: decimal
    • Exchange code this tick came from QuantConnect.Exchanges
  • ExchangeCode: string
    • Exchange name this tick came from QuantConnect.Exchanges
  • Exchange: string
    • Sale condition for the tick.
  • SaleCondition: string
    • For performance parsed sale condition for the tick.
  • ParsedSaleCondition: UInt32
    • Bool whether this is a suspicious tick
  • Suspicious: bool
    • Bid Price for Tick
  • BidPrice: decimal
    • Asking price for the Tick quote.
  • AskPrice: decimal
    • Alias for "Value" - the last sale for this asset.
  • LastPrice: decimal
    • Size of bid quote.
  • BidSize: decimal
    • Size of ask quote.
  • AskSize: decimal
    • Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.
  • DataType: MarketDataType
    • True if this is a fill forward piece of data
  • IsFillForward: bool
    • Current time marker of this data packet.
  • Time: DateTime
    • The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered
  • EndTime: DateTime
    • Symbol representation for underlying Security
  • Symbol: Symbol
    • Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.
  • Value: decimal
    • As this is a backtesting platform we'll provide an alias of value as price.
  • Price: decimal

 

Classic Algorithm Example

The following example algorithm buys the Mini Gold Futures contract with the greatest open interest and sells the Micro Gold Futures contract with the greatest open interest. When the open interest of a different contract exceeds the open interest of a contract in the portfolio, the algorithm rebalances the portfolio.

Select Language: 
from AlgorithmImports import *
from QuantConnect.DataSource import *

class USFuturesDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_cash(1000000)
        # Setting the continuous contract mapping criteria for both Gold and Micro Gold contracts, since we want to order the highest liquidity contracts
        self.set_security_initializer(lambda security: FuncSecuritySeeder(self.get_last_known_prices).seed_security(security))
        self.gold = self.add_future(Futures.Metals.GOLD,
            extended_market_hours=True,
            data_mapping_mode=DataMappingMode.OPEN_INTEREST,
            data_normalization_mode=DataNormalizationMode.BACKWARDS_RATIO,
            contract_depth_offset=0)
        self.micro_gold = self.add_future(Futures.Metals.MICRO_GOLD,
            extended_market_hours=True,
            data_mapping_mode=DataMappingMode.OPEN_INTEREST,
            data_normalization_mode=DataNormalizationMode.BACKWARDS_RATIO,
            contract_depth_offset=0)
        # The contract multiplier is cached in the Security symbol_properties property from the symbol properties database
        self.gold_multiplier = self.gold.symbol_properties.contract_multiplier
        self.micro_gold_multiplier = self.micro_gold.symbol_properties.contract_multiplier

    def on_data(self, slice: Slice) -> None:
        # Make sure to calculate the order size by the most updated price data of both contracts
        if not self.portfolio.invested and self.gold.symbol in slice.bars and self.micro_gold.symbol in slice.bars:
            # Calculate the order size for $500k
            # Get the quotient after dividing the contract multiplier since the order size must be whole number
            gold_quantity = 500000 / slice.bars[self.gold.symbol].close // self.gold_multiplier
            micro_gold_quantity = 500000 / slice.bars[self.micro_gold.symbol].close // self.micro_gold_multiplier

            self.market_order(self.gold.mapped, gold_quantity)
            self.market_order(self.micro_gold.mapped, micro_gold_quantity)
                
    def on_securities_changed(self, changes: SecurityChanges) -> None:
        for security in changes.added_securities:
            # Historical data
            history = self.history(security.symbol, 10, Resolution.MINUTE)
            self.debug(f"We got {len(history)} from our history request for {security.symbol}")
using QuantConnect.DataSource;

namespace QuantConnect
{
    public class USFuturesDataAlgorithm : QCAlgorithm
    {
        private Future _gold, _microGold;
        private decimal _goldMulitplier, _microGoldMulitplier;

        public override void Initialize()
        {
            SetCash(1000000);
            // Setting the continuous contract mapping criteria for both Gold and Micro Gold contracts, since we want to order the highest liquidity contracts
            _gold = AddFuture(Futures.Metals.Gold,
                extendedMarketHours: true,
                dataMappingMode: DataMappingMode.OpenInterest,
                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
                contractDepthOffset: 0);
            _microGold = AddFuture(Futures.Metals.MicroGold,
               extendedMarketHours: true,
                dataMappingMode: DataMappingMode.OpenInterest,
                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
                contractDepthOffset: 0);
            // The contract multiplier is cached in the Security SymbolProperties property from the symbol properties database
            _goldMulitplier = _gold.SymbolProperties.ContractMultiplier;
            _microGoldMulitplier = _microGold.SymbolProperties.ContractMultiplier;
        }

        public override void OnData(Slice slice)
        {
            // Make sure to calculate the order size by the most updated price data of both contracts
            if (!Portfolio.Invested && slice.Bars.ContainsKey(_gold.Symbol) && slice.Bars.ContainsKey(_microGold.Symbol))
            {
                // Calculate the order size for $500k
                // Get the quotient after dividing the contract multiplier since the order size must be whole number
                var goldQuantity = Math.Floor(500000m / slice.Bars[_gold.Symbol].Close / _goldMulitplier);
                var microGoldQuantity = Math.Floor(500000m / slice.Bars[_microGold.Symbol].Close / _microGoldMulitplier);

                MarketOrder(_gold.Mapped, goldQuantity);
                MarketOrder(_microGold.Mapped, microGoldQuantity);
            }
        }
        
        public override void OnSecuritiesChanged(SecurityChanges changes)
        {
            foreach (var security in changes.AddedSecurities)
            {
                // Historical data
                var history = History(security.Symbol, 100, Resolution.Minute);
                Debug($"We got {history.Count()} from our history request for {security.Symbol}");
            }
        }
    }
}

Framework Algorithm Example

The following example algorithm buys the front-month Mini Gold Futures contract and sells the front-month Micro Gold Futures contract. When the front-month contract changes, the algorithm rebalances the portfolio.

Select Language: 
from AlgorithmImports import *
from QuantConnect.DataSource import *
from Selection.FutureUniverseSelectionModel import FutureUniverseSelectionModel

class USFuturesDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:

        self.set_start_date(2013, 12, 20) 
        self.set_end_date(2014, 2, 20)
        self.set_cash(100000)
        self.universe_settings.asynchronous = True
        # Set up an universe selection model that selects the front month contract
        self.set_universe_selection(FrontMonthFutureUniverseSelectionModel())
        self.add_alpha(ConstantFuturesAlphaModel())
        # A portfolio construction model that only order a single share per insight signal
        self.set_portfolio_construction(SingleSharePortfolioConstructionModel())
        
class FrontMonthFutureUniverseSelectionModel(FutureUniverseSelectionModel):
    def __init__(self,) -> None:
        # Daily updating with select_future_chain_symbols function
        super().__init__(timedelta(1), self.select_future_chain_symbols)

    def select_future_chain_symbols(self, utcTime: datetime) -> List[Symbol]:
        # Select gold and micro gold contracts for the strategy need
        future_pairs = [
            (Futures.Metals.GOLD, Market.COMEX),
            (Futures.Metals.MICRO_GOLD, Market.COMEX)
        ]
        return [Symbol.create(pair[0], SecurityType.FUTURE, pair[1]) for pair in future_pairs]

    def filter(self, filter: FutureFilterUniverse) -> FutureFilterUniverse:
        # Filter only front month contract for liquidity and most informed information
        return filter.front_month().only_apply_filter_at_market_open()

class ConstantFuturesAlphaModel(AlphaModel):
    # Long gold and short micro gold in this strategy
    long_symbol = Symbol.create(Futures.Metals.GOLD, SecurityType.FUTURE, Market.COMEX)
    short_symbol = Symbol.create(Futures.Metals.MICRO_GOLD, SecurityType.FUTURE, Market.COMEX)
        
    def update(self, algorithm: QCAlgorithm, slice: Slice) -> List[Insight]:
        if algorithm.portfolio.invested:
            return []
        
        insights = []
        # For both gold and micro gold, select the front month contract (only contract) in the chain
        for kvp in slice.future_chains:
            chain = [contract for contract in kvp.Value]
            contract = chain[0]
            
            # Long gold and short micro gold as planned
            if kvp.Key == self.long_symbol:
                insights.append(Insight.price(contract.symbol, contract.expiry + timedelta(days=1), InsightDirection.UP))
            elif kvp.Key == self.short_symbol:
                insights.append(Insight.price(contract.symbol, contract.expiry + timedelta(days=1), InsightDirection.DOWN))
        
        return insights
        
    def on_securities_changed(self, algorithm: QCAlgorithm, changes: SecurityChanges) -> None:
        for security in changes.added_securities:
            # Historical data
            history = algorithm.history(security.symbol, 10, Resolution.MINUTE)
            algorithm.debug(f"We got {len(history)} from our history request for {security.symbol}")

class SingleSharePortfolioConstructionModel(PortfolioConstructionModel):
    def create_targets(self, algorithm: QCAlgorithm, insights: List[Insight]) -> List[PortfolioTarget]:
        targets = []
        for insight in insights:
            if algorithm.securities[insight.symbol].is_tradable:
                # Single share only using integer portfolio target
                targets.append(PortfolioTarget(insight.symbol, insight.direction))
        return targets
using QuantConnect.DataSource;

namespace QuantConnect
{
    public class USFuturesDataAlgorithm : QCAlgorithm
    {        
        public override void Initialize()
        {
            SetStartDate(2013, 12, 20);
            SetEndDate(2014, 2, 20);
            SetCash(1000000);
            UniverseSettings.Asynchronous = true;
            // Set up an universe selection model that selects the front month contract
            SetUniverseSelection(new FrontMonthFutureUniverseSelectionModel());
            SetAlpha(new ConstantFuturesAlphaModel());
            // A portfolio construction model that only order a single share per insight signal
            SetPortfolioConstruction(new SingleSharePortfolioConstructionModel());
        }
    }
        
    class FrontMonthFutureUniverseSelectionModel : FutureUniverseSelectionModel
    {
        // Daily updating with select_future_chain_symbols function
        public FrontMonthFutureUniverseSelectionModel()
            : base(TimeSpan.FromDays(1), SelectFutureChainSymbols) {}

        private static IEnumerable<Symbol> SelectFutureChainSymbols(DateTime utcTime)
        {
            //Select gold and micro gold contracts for the strategy need
            return new List<Symbol> {
                QuantConnect.Symbol.Create(Futures.Metals.Gold, SecurityType.Future, Market.COMEX),
                QuantConnect.Symbol.Create(Futures.Metals.MicroGold, SecurityType.Future, Market.COMEX)
            };
        }

        protected override FutureFilterUniverse Filter(FutureFilterUniverse filter)
        {
            // Filter only front month contract for liquidity and most informed information
            return filter.FrontMonth().OnlyApplyFilterAtMarketOpen();
        }
    }


    class ConstantFuturesAlphaModel : AlphaModel
    {
        // Long gold and short micro gold in this strategy
        private Symbol 
            _longSymbol = QuantConnect.Symbol.Create(Futures.Metals.Gold, SecurityType.Future, Market.COMEX), 
            _shortSymbol = QuantConnect.Symbol.Create(Futures.Metals.MicroGold, SecurityType.Future, Market.COMEX);
        
        public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice slice)
        {
            var insights = new List<Insight>();

            if (algorithm.Portfolio.Invested)
            {
                return insights;
            }
            
            // For both gold and micro gold, select the front month contract (only contract) in the chain
            foreach (var kvp in slice.FutureChains)
            {
                var symbol = kvp.Key;
                var chain = kvp.Value;
                var contract = chain.First();
                
                // Long gold and short micro gold as planned
                if (symbol == _longSymbol)
                {
                    insights.Add(Insight.Price(contract.Symbol, contract.Expiry + TimeSpan.FromDays(1), InsightDirection.Up));
                }
                else if (symbol == _shortSymbol)
                {
                    insights.Add(Insight.Price(contract.Symbol, contract.Expiry + TimeSpan.FromDays(1), InsightDirection.Down));
                }
            }

            return insights;
        }
        
        public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
        {
            foreach (var security in changes.AddedSecurities)
            {
                // Historical data
                var history = algorithm.History(security.Symbol, 100, Resolution.Minute);
                algorithm.Debug($"We got {history.Count()} from our history request for {security.Symbol}");
            }
        }
    }
        
        
    class SingleSharePortfolioConstructionModel : PortfolioConstructionModel
    {
        public override IEnumerable<PortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
        {
            var targets = new List<PortfolioTarget>();
            foreach (var insight in insights)
            {
                if (algorithm.Securities[insight.Symbol].IsTradable)
                {
                    // Single share only using integer portfolio target
                    targets.Add(new PortfolioTarget(insight.Symbol, (int) insight.Direction));
                }
            }
            return targets;
        }
    }
}

 

Licensing Available

Cloud Usage

Cloud Usage

US Futures 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

US Futures 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 5 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 "US Futures" `
	--data-type "bulk" `
	--resolution "second" `
	--start "20240401" `
	--end "20250401"

Pricing | Provider offers 16 licensing options

The QuantConnect-AlgoSeek partnership provides free access to US Futures market data in QuantConnect Cloud. This dataset depends on the US Futures Security Master dataset because the US Futures Security Master dataset contains information on symbol changes.

Cloud Access

Free access to the most popular US Futures in QuantConnect Cloud for backtest and research.

  • Tick to minute resolution data
  • Universe selection on Future chains
  • Uncorrelated asset class

PRICE

Free

Documentation

Tick Download

US Future Tick resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day.

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

PRICE

6 QCC/file

cli button LEAN CLI

Second Download

US Futures Second resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day.

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

PRICE

5 QCC/file

cli button LEAN CLI

Minute Download

US Futures Minute resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day.

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

PRICE

5 QCC/file

cli button LEAN CLI

Hour Download

US Futures Hourly resolution archives in LEAN format for on premise backtesting and research. One file per ticker.

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

PRICE

500 QCC/file

cli button LEAN CLI

Daily Download

US Futures Daily resolution archives in LEAN format for on premise backtesting and research. One file per ticker.

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

PRICE

500 QCC/file

cli button LEAN CLI

Bulk Daily Updates

Bulk download the latest daily data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$720/yr

cli button LEAN CLI

Bulk Tick Updates

Bulk download the latest tick data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$1,200/yr

cli button LEAN CLI

Bulk Second Updates

Bulk download the latest second data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$1,200/yr

cli button LEAN CLI

Bulk Minute Updates

Bulk download the latest minute data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$1,200/yr

cli button LEAN CLI

Bulk Hour Updates

Bulk download the latest hourly data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$1,440/yr

cli button LEAN CLI

Bulk Daily Download

Bulk download all the daily data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$12,000

Subscribe

Bulk Hour Download

Bulk download all the hourly data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$14,400

Subscribe

Bulk Tick Download

Bulk download all the tick data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$30,000

Subscribe

Bulk Second Download

Bulk download all the second data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$30,000

Subscribe

Bulk Minute Download

Bulk download all the minute data

  • Download all Futures contracts
  • Bulk price discount
  • CLI ready

PRICE

$30,000

Subscribe

User Reviews

What people are saying about this

No Reviews Yet

This product has not received any reviews yet, be the first to post one!

Pricing

Provider offers 16 licensing options

View Pricing

Starting Date

  • May 2009

Coverage

  • 162 Most Liquid Futures

Delivery Methods

  • Download
  • Cloud

About the Provider

Support

Tickets and Seats

  • create new ticket create new ticket Create New Ticket
  • organization ticket organization ticket Organization Tickets
  • spport seat spport seat Support Seats

Support

Begin Your QuantConnect Journey

Algorithm Lab is your playground for developing and refining trading algorithms with QuantConnect. Utilize advanced tools, historical data, and robust backtesting to enhance your trading strategies. Transform your ideas into actionable insights and optimize your trading approach with ease.

Sign Up for Free

Already have an account Log In.