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 -6.8 Tracking Error 0.624 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 |
class RollingWindowAlgorithm(QCAlgorithm): 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(2021,2,1) #Set Start Date self.SetEndDate(2021,4,21) #Set End Date self.SetCash(25000) #Set Strategy Cash self.SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash) self.AddCrypto("BTCUSD", Resolution.Minute) # Subscribe to minutely QuoteBars in Initialize(self) # Creates a Rolling Window indicator to keep the 2 QuoteBar self.window = RollingWindow[QuoteBar](2) # For other security types, use QuoteBar # Creates an indicator and adds to a rolling window when it is updated self.SMA("BTCUSD", 50).Updated += self.SmaUpdated self.smaWin = RollingWindow[IndicatorDataPoint](50) self.SetBenchmark("BTCUSD") self.SetWarmUp(50) def SmaUpdated(self, sender, updated): '''Adds updated values to rolling window''' self.smaWin.Add(updated) def OnData(self, data): '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.''' # Add Quotebar in rollling window if data.QuoteBars.ContainsKey("BTCUSD"): # Add EURUSD QuoteBar in rolling window self.window.Add(data.QuoteBars['BTCUSD']) # Wait for windows to be ready. if not (self.window.IsReady and self.smaWin.IsReady): return def OnEndOfDay(self): self.Plot("Window", "Count", self.window.Count)