Overall Statistics |
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 195.727% Drawdown 49.000% Expectancy 0 Net Profit 1507.086% Sharpe Ratio 1.264 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 1.035 Beta 0.037 Annual Standard Deviation 0.821 Annual Variance 0.673 Information Ratio 1.179 Tracking Error 0.827 Treynor Ratio 27.938 Total Fees $29.84 |
import numpy as np ### <summary> ### Basic template algorithm simply initializes the date range and cash. This is a skeleton ### framework you can use for designing an algorithm. ### </summary> class BasicTemplateAlgorithm(QCAlgorithm): '''Basic template algorithm simply initializes the date range and cash''' def Initialize(self): '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.''' self.SetStartDate(2015,5,1) #Set Start Date self.SetEndDate(2017,12,1) #Set End Date self.SetCash(10000) #Set Strategy Cash self.SetBrokerageModel(BrokerageName.GDAX) self.AddCrypto("LTCUSD", Resolution.Daily) 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 ''' if not self.Portfolio.Invested: self.SetHoldings("LTCUSD", 1)