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 0 Tracking Error 0 Treynor Ratio 0 Total Fees $0.00 |
class UncoupledMultidimensionalAutosequencers(QCAlgorithm): def Initialize(self): self.SetStartDate(2019, 12, 13) # Set Start Date self.SetCash(100000) # Set Strategy Cash tickers = ["SPY", "TLT"] # Dictionary to hold Symbol Data self.symbolData = {} for ticker in tickers: # Add equity data symbol = self.AddEquity(ticker, Resolution.Daily).Symbol # Create symbol data for respective symbol self.symbolData[symbol] = SymbolData(self, symbol) class SymbolData: def __init__(self, algorithm, symbol): self.algorithm = algorithm self.symbol = symbol # Define our indicator self.adx = algorithm.ADX(symbol, 14, Resolution.Daily) # Define our rolling window to hold indicator points self.adxWindow = RollingWindow[IndicatorDataPoint](2) # Set our event handler self.adx.Updated += self.OnAdxUpdated def OnAdxUpdated(self, sender, updated): self.algorithm.Debug("ADX updated for " + self.symbol.Value + " @ value" + str(updated)) # Add updated indicator data to rolling window self.adxWindow.Add(updated)