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 -2.783 Tracking Error 0.157 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
class SymbolData: def __init__(self,algorithm,symbol): self.symbol = symbol self.algo = algorithm self.rsi = RelativeStrengthIndex(10, MovingAverageType.Simple) self.ema = ExponentialMovingAverage(15) consolidator = TradeBarConsolidator(Resolution.Hour) self.algo.SubscriptionManager.AddConsolidator(self.symbol, consolidator) self.algo.RegisterIndicator(self.symbol, self.rsi, consolidator) self.algo.RegisterIndicator(self.symbol, self.ema, consolidator) class ResistanceMultidimensionalCompensator(QCAlgorithm): def Initialize(self): self.SetStartDate(2020, 6, 25) # Set Start Date self.SetCash(100000) # Set Strategy Cash self.AddEquity("SPY", Resolution.Minute) self.AddAlpha(MyAlphaModel()) 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("SPY", 1) class MyAlphaModel(AlphaModel): def __init__(self): self.algo = None self.Symbol_Data = {} def Update(self, algorithm, data): insights = [] return insights def OnSecuritiesChanged(self, algorithm, changes): if self.algo is None: self.algo = algorithm for security in changes.AddedSecurities: symbol = security.Symbol if symbol not in self.Symbol_Data: self.Symbol_Data[symbol] = SymbolData(algorithm,symbol) def HourBarHandler(self, sender, updated): symbol = self.consolidator2symbol[sender] close = updated.Close self.algo.Plot('Custom', symbol.Value + " close: ", str(close)) self.rw.Add(updated) self.updated = True