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CoinAPI

Binance Crypto Future Price Data

Introduction

The Binance Crypto Future Price Data by CoinAPI is for Crypto-currency futures price and volume data points. The data covers 421 Cryptocurrency pairs, starts in August 2020, and is delivered on any frequency from tick to daily. This dataset is created by monitoring the trading activity on Binance.

The Binance Crypto Future Margin Rate Data dataset provides margin interest data to model margin costs.

For more information about the Binance Crypto Future Price Data dataset, including CLI commands and pricing, see the dataset listing.

About the Provider

CoinAPI was founded by Artur Pietrzyk in 2016 with the goal of providing real-time and historical cryptocurrency market data, collected from hundreds of exchanges. CoinAPI provides access to Cryptocurrencies for traders, market makers, and developers building third-party applications.

Getting Started

The following snippet demonstrates how to request data from the Binance Crypto Future Price dataset:

def initialize(self) -> None:
    self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)
    self.set_brokerage_model(BrokerageName.BINANCE_COIN_FUTURES, AccountType.MARGIN)

    self.crypto_future_symbol = self.add_crypto_future("BTCBUSD", Resolution.MINUTE).symbol

private Symbol _cryptoFutureSymbol;

public override void Initialize
{
    SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);
    SetBrokerageModel(BrokerageName.BinanceCoinFutures, AccountType.Margin);

    // perpetual futures does not have a filter function
    _cryptoFutureSymbol = AddCryptoFuture("BTCBUSD", Resolution.Minute).Symbol;
}

Data Summary

The following table describes the dataset properties:

PropertyValue
Start DateAugust 2020
Asset Coverage421 Crypto Futures Pairs
Data DensityDense
ResolutionTick, Second, Minute, Hourly, & Daily
TimezoneUTC
Market HoursAlways Open

Requesting Data

To add Binance Crypto Future Price data to your algorithm, call the AddCryptoFutureadd_crypto_future method. Save a reference to the Crypto Future Symbol so you can access the data later in your algorithm.

class CoinAPIDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2020, 6, 1)
        self.set_end_date(2021, 6, 1)

        # Set Account Currency to Binance Stable Coin for USD
        self.set_account_currency("BUSD")
        self.set_cash(100000)

        self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)
        self.set_brokerage_model(BrokerageName.BINANCE_COIN_FUTURES, AccountType.MARGIN)
        
        crypto_future = self.add_crypto_future("BTCBUSD", Resolution.MINUTE)
        # perpetual futures does not have a filter function
        self.btcbusd = crypto_future.symbol
public class CoinAPIDataAlgorithm : QCAlgorithm
{
    private Symbol _symbol ;
    
    public override void Initialize()
    {
        SetStartDate(2020, 6, 1);
        SetEndDate(2021, 6, 1);

        // Set Account Currency to Binance Stable Coin for USD
        SetAccountCurrency("BUSD");
        SetCash(100000);

        SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);
        SetBrokerageModel(BrokerageName.BinanceCoinFutures, AccountType.Margin);
        
        var cryptoFuture = AddCryptoFuture("BTCBUSD", Resolution.Minute);
        // perpetual futures does not have a filter function
        _symbol = cryptoFuture.Symbol;
    }
}

For more information about creating Crypto Future subscriptions, see Requesting Data.

Accessing Data

To get the current Binance Crypto Future Price data, index the Barsbars, QuoteBarsquote_bars, or Ticksticks properties of the current Slice with the Crypto 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.

def on_data(self, slice: Slice) -> None:
    if self.btcbusd in slice.bars:
        trade_bar = slice.bars[self.btcbusd]
        self.log(f"{self.btcbusd} close at {slice.time}: {trade_bar.close}")

    if self.btcbusd in slice.quote_bars:
        quote_bar = slice.quote_bars[self.btcbusd]
        self.log(f"{self.btcbusd} bid at {slice.time}: {quote_bar.bid.close}")

    if self.btcbusd in slice.ticks:
        ticks = slice.ticks[self.btcbusd]
        for tick in ticks:
            self.log(f"{self.btcbusd} price at {slice.time}: {tick.price}")
public override void OnData(Slice slice)
{
    if (slice.Bars.ContainsKey(_symbol))
    {
        var tradeBar = slice.Bars[_symbol];
        Log($"{_symbol} price at {slice.Time}: {tradeBar.Close}");
    }

    if (slice.QuoteBars.ContainsKey(_symbol))
    {
        var quoteBar = slice.QuoteBars[_symbol];
        Log($"{_symbol} bid at {slice.Time}: {quoteBar.Bid.Close}");
    }

    if (slice.Ticks.ContainsKey(_symbol))
    {
        var ticks = slice.Ticks[_symbol];
        foreach (var tick in ticks)
        {
            Log($"{_symbol} price at {slice.Time}: {tick.Price}");
        }
    }
}

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

def on_data(self, slice: Slice) -> None:
    for symbol, trade_bar in slice.bars.items():
        self.log(f"{symbol} close at {slice.time}: {trade_bar.close}")

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

    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)
{
    foreach (var kvp in slice.Bars)
    {
        var symbol = kvp.Key;
        var tradeBar = kvp.Value;
        Log($"{symbol} price at {slice.Time}: {tradeBar.Close}");
    }

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

    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 Crypto Future data, see Handling Data.

Historical Data

To get historical Binance Crypto Future Price data, call the Historyhistory method with the Crypto Future Symbol. If there is no data in the period you request, the history result is empty.

# DataFrame
history_df = self.history(self.btcbusd, 100, Resolution.DAILY)

# TradeBar objects
history_trade_bars = self.history[TradeBar](self.btcbusd, 100, Resolution.MINUTE)

# QuoteBar objects
history_quote_bars = self.history[QuoteBar](self.btcbusd, 100, Resolution.MINUTE)

# Tick objects
history_ticks = self.history[Tick](self.btcbusd, timedelta(seconds=10), Resolution.TICK)
// TradeBar objects 
var historyTradeBars = History(_symbol, 100, Resolution.Daily);

// QuoteBar objects 
var historyQuoteBars = History<QuoteBar>(_symbol, 100, Resolution.Minute);

// Tick objects 
var historyTicks = History<Tick>(_symbol, TimeSpan.FromSeconds(10), Resolution.Tick);

For more information about historical data, see History Requests.

Remove Subscriptions

To unsubscribe from a Crypto Future contract that you added with the AddCryptoFutureadd_crypto_future method, call the RemoveSecurityremove_security method.

self.remove_security(self.btcbusd)
RemoveSecurity(_symbol);

The RemoveSecurityremove_security method cancels your open orders for the security and liquidates your Crypto Future holdings.

Supported Assets

The following table shows the available Crypto Future pairs:

Example Applications

The Binance Crypto Future Price dataset enables you to accurately design strategies for Cryptocurrencies with term structure. Examples include the following strategies:

  • Horizontal/Diagonal arbitrage with the underlying cryptocurrencies
  • Trade Contango/Backwardation predictions
  • Hedge for illiquid cryptocurrencies

Classic Algorithm Example

The following example algorithm buys BTCBUSD perpetual future contract if the last day's close price was close to ask close price than bid close price, sells short of that in opposite, through the Binance exchange:

from AlgorithmImports import *

class BinanceCryptoFutureDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2022, 10, 1)
        self.set_end_date(2022, 10, 10)
        # Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
        self.set_cash("BUSD", 100000)
        # Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
        self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)

        # Requesting data, we only trade on BTCBUSD Future in Binance Future exchange
        crypto_future = self.add_crypto_future("BTCBUSD", Resolution.DAILY)
        # perpetual futures does not have a filter function
        self.btcbusd = crypto_future.symbol

        # Historical data
        history = self.history(self.btcbusd, 10, Resolution.DAILY)
        self.debug(f"We got {len(history)} from our history request for {self.btcbusd}")

    def on_data(self, slice: Slice) -> None:
        # Trade only based on updated price data
        if not slice.bars.contains_key(self.btcbusd) or not slice.quote_bars.contains_key(self.btcbusd):
            return
        
        quote = slice.quote_bars[self.btcbusd]
        price = slice.bars[self.btcbusd].price

        # Scalp-trade the bid-ask spread based on the supply-demand strength
        if price - quote.bid.close > quote.ask.close - price:
            self.set_holdings(self.btcbusd, -1)
        else:
            self.set_holdings(self.btcbusd, 1)
public class BinanceCryptoFutureDataAlgorithm : QCAlgorithm
{
    public Symbol _symbol;

    public override void Initialize()
    {
        SetStartDate(2022, 1, 1);
        SetEndDate(2023, 1, 1);
        // Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
        SetCash("BUSD", 100000);
        // Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
        SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);

        // Requesting data, we only trade on BTCBUSD Future in Binance Future exchange
        var cryptoFuture = AddCryptoFuture("BTCBUSD", Resolution.Daily);
        // perpetual futures does not have a filter function
        _symbol = cryptoFuture.Symbol;

        // Historical data
        var history = History(_symbol, 10, Resolution.Daily);
        Debug($"We got {history.Count()} from our history request for {_symbol}");
    }

    public override void OnData(Slice slice)
    {
        // Trade only based on updated price data
        if (!slice.Bars.ContainsKey(_symbol) || !slice.QuoteBars.TryGet(_symbol, out var quote))
        {
            return;
        }
        var price = slice.Bars[_symbol].Price;
        
        // Scalp-trade the bid-ask spread based on the supply-demand strength
        if (price - quote.Bid.Close > quote.Ask.Close - price)
        {
            SetHoldings(_symbol, -1m);
        }
        else
        {
            SetHoldings(_symbol, 1m);
        }
    }
}

Framework Algorithm Example

The following example algorithm hold a 100% long BTCBUSD future portfolio if the last day's close price was close to ask close price than bid close price, while hold short of that in opposite, through the Binance exchange using the algorithm framework implementation:

from AlgorithmImports import *

class BinanceCryptoFutureDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2022, 10, 1)
        self.set_end_date(2022, 10, 10)
        # Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
        self.set_cash("BUSD", 100000)
        # Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
        self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)

        self.universe_settings.resolution = Resolution.DAILY
        self.universe_settings.leverage = 2
        # We only trade on BTCBUSD Future in Binance Future exchange
        symbols = Symbol.create("BTCBUSD", SecurityType.CRYPTO_FUTURE, Market.BINANCE)
        self.add_universe_selection(ManualUniverseSelectionModel(symbols))
        # Custom alpha model to emit insights based on the Crypto Future price data
        self.add_alpha(CryptoFutureAlphaModel())
        # Equally invest to evenly dissipate the capital concentration risk of inidividual crypto pair
        self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel())
        self.set_execution(ImmediateExecutionModel())

class CryptoFutureAlphaModel(AlphaModel):

    def __init__(self) -> None:
        self.symbols = []

    def update(self, algorithm: QCAlgorithm, slice: Slice) -> List[Insight]:
        insights = []

        for symbol in self.symbols:
            # Trade only based on updated price data
            if not slice.bars.contains_key(symbol) or not slice.quote_bars.contains_key(symbol):
                continue

            quote = slice.quote_bars[symbol]
            price = slice.bars[symbol].price
            
            # Scalp-trade the bid-ask spread based on the supply-demand strength
            if price - quote.bid.close > quote.ask.close - price:
                insights.append(Insight.price(symbol, timedelta(1), InsightDirection.DOWN))
            else:
                insights.append(Insight.price(symbol, timedelta(1), InsightDirection.UP))
            
        return insights

    def on_securities_changed(self, algorithm: QCAlgorithm, changes: SecurityChanges) -> None:
        for security in changes.added_securities:
            symbol = security.symbol
            self.symbols.append(symbol)

            # Historical data
            history = algorithm.history(symbol, 10, Resolution.DAILY)
            algorithm.debug(f"We got {len(history)} from our history request for {symbol}")

        for security in changes.removed_securities:
            symbol = security.symbol
            if symbol in self.symbols:
                self.symbols.remove(symbol)
public class BinanceCryptoFutureDataAlgorithm : QCAlgorithm
{
    public Symbol _symbol;

    public override void Initialize()
    {
        SetStartDate(2022, 10, 1);
        SetEndDate(2022, 10, 10);
        // Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
        SetCash("BUSD", 100000);
        // Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
        SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);

        UniverseSettings.Resolution = Resolution.Daily;
        UniverseSettings.Leverage = 2;
        // We only trade on BTCBUSD Future in Binance Future exchange
        var symbols = new List{
            QuantConnect.Symbol.Create("BTCBUSD", SecurityType.CryptoFuture, Market.Binance)
        };
        AddUniverseSelection(new ManualUniverseSelectionModel(symbols));
        // Custom alpha model to emit insights based on the Crypto Future price data
        AddAlpha(new CryptoFutureAlphaModel());
        // Equally invest to evenly dissipate the capital concentration risk of inidividual crypto pair
        SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
        SetExecution(new ImmediateExecutionModel());
    }
}

public class CryptoFutureAlphaModel : AlphaModel
{
    private List _symbols = new();

    public override List Update(QCAlgorithm algorithm, Slice slice)
    {
        var insights = new List();

        foreach (var symbol in _symbols)
        {
            // Trade only based on updated price data
            if (!slice.Bars.ContainsKey(symbol) || !slice.QuoteBars.TryGet(symbol, out var quote))
            {
                continue;
            }
            var price = slice.Bars[symbol].Price;
            
            // Scalp-trade the bid-ask spread based on the supply-demand strength
            if (price - quote.Bid.Close > quote.Ask.Close - price)
            {
                insights.Add(
                    Insight.Price(symbol, TimeSpan.FromDays(1), InsightDirection.Down)
                );
            }
            else
            {
                insights.Add(
                    Insight.Price(symbol, TimeSpan.FromDays(1), InsightDirection.Up)
                );
            }
        }
        
        return insights;
    }

    public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
    {
        foreach (var security in changes.AddedSecurities)
        {
            var symbol = security.Symbol;
            _symbols.Add(symbol);

            // Historical data
            var history = algorithm.History(symbol, 10, Resolution.Daily);
            algorithm.Debug($"We got {history.Count()} from our history request for {symbol}");
        }

        foreach (var security in changes.RemovedSecurities)
        {
            _symbols.Remove(security.Symbol);
        }
    }
}

Data Point Attributes

The Binance Crypto Future Price dataset provides TradeBar, QuoteBar, and Tick objects.

TradeBar Attributes

TradeBar objects have the following attributes:

QuoteBar Attributes

QuoteBar objects have the following attributes:

Tick Attributes

Tick objects have the following attributes:

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