Overall Statistics
Total Trades
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
Sharpe Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
-2.033
Tracking Error
0.103
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
from clr import AddReference
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Algorithm.Framework")
AddReference("QuantConnect.Indicators")
AddReference("QuantConnect.Logging")
AddReference("QuantConnect.Common")

from QuantConnect import *
from QuantConnect.Indicators import *
from QuantConnect.Logging import Log
from QuantConnect.Algorithm import *
from QuantConnect.Algorithm.Framework import *
from QuantConnect.Algorithm.Framework.Alphas import *
class MuscularFluorescentYellowRabbit(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2021, 1, 1)
        self.SetEndDate(2021, 11, 15)
        # self.SetAccountCurrency("USDT")
        self.SetCash(100000) 
        self.resolution = Resolution.Hour
        self.UniverseSettings.Resolution = self.resolution
        self.UniverseSettings.Leverage = 3
        self.SetTimeZone(TimeZones.Utc)
        self.AddCrypto('BTCUSDT', self.resolution, Market.Binance)
        self.SetBrokerageModel(BrokerageName.QuantConnectBrokerage, AccountType.Margin)
        
        self.itr = 0
    def HourBarHandler(self, sender, bar):
        self.consolidated_bars[bar.Symbol] = bar
        
    def OnData(self, data):
        ''' OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
            Arguments:
                data: Slice object keyed by symbol containing the stock data
        '''
        self.SetHoldings('BTCUSDT', -0.1)