from Execution.ImmediateExecutionModel import ImmediateExecutionModel
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
#Multidimensional Tachyon Replicator
class HipsterSkyBlueCaribou(QCAlgorithm):

    def Initialize(self):
        # Set Start Date so that backtest has 5+ years of data
        self.SetStartDate(2010, 1, 1)
        #self.SetEndDate(2021, 11, 1)
        

        # No need to set End Date as the final submission will be tested
        # up until the review date

        # Set $195 Strategy Cash to trade significant AUM
        self.SetCash(200)

        # Add a relevant benchmark, with the default being SPY
        self.stock = self.AddEquity('AMZN', Resolution.Hour).Symbol
        
        self.SetBenchmark('AMZN')
      
        # Use the Alpha Streams Brokerage Model, developed in conjunction with
        # funds to model their actual fees, costs, etc.
        # Please do not add any additional reality modelling, such as Slippage, Fees, Buying Power, etc.
        self.SetBrokerageModel(AlphaStreamsBrokerageModel())

        self.SetExecution(ImmediateExecutionModel())

        self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())

        self.UniverseSettings.Resolution = Resolution.Minute
        self.SetUniverseSelection(LiquidETFUniverse())
    


    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
        '''
        self.SetHoldings(self.stock, 1) 

# Your New Python File

from Execution.ImmediateExecutionModel import ImmediateExecutionModel
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
#
#Portfolio construction
#Price–sales ratio, P/S ratio, or PSR. 
#Multidimensional Tachyon Replicator
class AlphaStreams(QCAlgorithm):

    def Initialize(self):
        # Set Start Date so that backtest has 5+ years of data
        self.SetStartDate(2012, 1, 1)
        #self.SetEndDate(2021, 11, 1)
        

        # No need to set End Date as the final submission will be tested
        # up until the review date

        # Set $195 Strategy Cash to trade 
        self.SetCash(1000)

        # Add a relevant benchmark, with the default being SPY
        self.stock = self.AddEquity('SPY', Resolution.Hour).Symbol
        
        self.SetBenchmark('SPY')
      
        # Use the Alpha Streams Brokerage Model, developed in conjunction with
        # funds to model their actual fees, costs, etc.
        # Please do not add any additional reality modelling, such as Slippage, Fees, Buying Power, etc.
        self.SetBrokerageModel(AlphaStreamsBrokerageModel())

        self.SetExecution(ImmediateExecutionModel())

        self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())

        self.UniverseSettings.Resolution = Resolution.Minute
        self.SetUniverseSelection(LiquidETFUniverse())
    


    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
        '''
        self.SetHoldings(self.stock, 1)