def Initialize(self):
# Set requested data resolution
self.UniverseSettings.Resolution = Resolution.Minute
self.SetStartDate(2013, 10, 7) #Set Start Date
self.SetEndDate(2013, 10, 11) #Set End Date
self.SetCash(100000) #Set Strategy Cash
self.symbols = [
Symbol.Create(x, SecurityType.Equity, Market.USA)
for x in ['AIG', 'BAC', 'IBM', 'SPY']
]
self.minimum_weight = -1
self.maximum_weight = 1
# set algorithm framework models
self.SetUniverseSelection(
CoarseFundamentalUniverseSelectionModel(self.coarseSelector))
self.SetAlpha(HistoricalReturnsAlphaModel(resolution=Resolution.Daily))
self.SetPortfolioConstruction(
MeanVarianceOptimizationPortfolioConstructionModel(
optimization_method=self.maximum_sharpe_ratio))
self.SetExecution(ImmediateExecutionModel())
self.SetRiskManagement(NullRiskManagementModel())
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.'''
# Set requested data resolution
self.UniverseSettings.Resolution = Resolution.Minute
self.SetStartDate(2013,10,7) #Set Start Date
self.SetEndDate(2013,10,11) #Set End Date
self.SetCash(100000) #Set Strategy Cash
selector = PythonUtil.ToCoarseFundamentalSelector(self.coarseSelector)
self.symbols = [ Symbol.Create(x, SecurityType.Equity, Market.USA) for x in [ 'AIG', 'BAC', 'IBM', 'SPY' ] ]
self.minimum_weight = -1
self.maximum_weight = 1
# set algorithm framework models
self.UniverseSelection = CoarseFundamentalUniverseSelectionModel(selector)
self.Alpha = HistoricalReturnsAlphaModel(resolution = Resolution.Daily)
self.PortfolioConstruction = MeanVarianceOptimizationPortfolioConstructionModel(optimization_method = self.maximum_sharpe_ratio)
self.Execution = ImmediateExecutionModel()
self.RiskManagement = NullRiskManagementModel()