'''An implementation of Meb Faber's base model: Global Tactical Asset Allocation model (GTAA)(5) 
Buy&Hold portfolio (monthly rebalance), as found in the paper: 
"A Quantitative Approach to Tactical Asset Allocation" published May 2006.
'''
class GlobalTacticalAssetAllocationBase(QCAlgorithm):
    def Initialize(self):
        backtestDuration = 365*10
        self.SetStartDate(datetime.now() - timedelta(backtestDuration))
        self.SetEndDate(datetime.now())
        self.SetCash(100000) 
        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)
        self.UniverseSettings.Resolution = Resolution.Daily
        symbols = [Symbol.Create(ticker, SecurityType.Equity, Market.USA) 
                    for ticker in [ "SPY", # US Large Cap ETF
                            "VEA", # Developed Foreign Stocks (TradedSince: 2007/8)ETF 
                            "IEF", # US 10Y Gov.Bonds ETF 
                            "DBC", # GSCI Commodities ETF (TradedSince: 2006/3)
                            "VNQ"  # US RealEstate ETF
                            ]]
        self.AddUniverseSelection(ManualUniverseSelectionModel(symbols))
        self.AddAlpha(ConstantAlphaModel(InsightType.Price, InsightDirection.Up, timedelta(days = backtestDuration), None, None))
        self.Settings.RebalancePortfolioOnInsightChanges = False
        self.Settings.RebalancePortfolioOnSecurityChanges = False
        self.SetPortfolioConstruction( EqualWeightingPortfolioConstructionModel(self.DateRules.MonthStart()) )
        self.SetExecution( ImmediateExecutionModel() ) 
        self.AddRiskManagement( NullRiskManagementModel() )
        
        # 1) Setting a Benchmark to plot with equity
        self.benchmarkTicker = 'SPY'
        self.SetBenchmark(self.benchmarkTicker)
        self.initBenchmarkPrice = None
    
    
    def UpdateBenchmarkValue(self):
        ''' Simulate buy and hold the Benchmark '''
        if self.initBenchmarkPrice is None:
            self.initBenchmarkCash = self.Portfolio.Cash
            self.initBenchmarkPrice = self.Benchmark.Evaluate(self.Time)
            self.benchmarkValue = self.initBenchmarkCash
        else:
            currentBenchmarkPrice = self.Benchmark.Evaluate(self.Time)
            self.benchmarkValue = (currentBenchmarkPrice / self.initBenchmarkPrice) * self.initBenchmarkCash    
            
            
    def OnData(self, data):
        # 2) simulate buy and hold the benchmark and plot its daily value as we are using daily data.
        # Otherwise schedule when to call this function!
        self.UpdateBenchmarkValue()
        self.Plot('Strategy Equity', self.benchmarkTicker, self.benchmarkValue)