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 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.consolidator2symbol = {}
        
    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
            consolidator = TradeBarConsolidator(Resolution.Hour)
            self.consolidator2symbol[consolidator] = symbol
            consolidator.DataConsolidated += self.HourBarHandler
            algorithm.SubscriptionManager.AddConsolidator(symbol, consolidator)
            
    def HourBarHandler(self, sender, updated):
        symbol = self.consolidator2symbol[sender]
        close = updated.Close
        self.algo.Plot('Custom', symbol.Value + " close: ", str(close))