Ray Dalio's All Weather Strategy - Algorithm Quantconnect

all-weather-strategy.py

from datetime import datetime
from collections import *

### <summary>
### All Weather Strategy (Ray Dalio) w/ annual rebalance. Run on QuantConnect www.quantconnect.com
### #http://www.lazyportfolioetf.com/allocation/ray-dalio-all-weather/
### </summary>>


class AllWeatherStrategy(QCAlgorithm):
    
    def Initialize(self):
        self.SetStartDate(2011, 1, 1)  
        self.SetEndDate(2019, 1, 31)
        self.SetCash(100000) 
        self.monthCounter = 0
        # Country index ETFs according to https://seekingalpha.com/etfs-and-funds/etf-tables/countries
        self.etfs = [
            (self.AddEquity('SPY', Resolution.Daily).Symbol,0.0),
            (self.AddEquity('VTI', Resolution.Daily).Symbol,0.3), #Vanguard Total Stock Market ETF
            (self.AddEquity('TLT', Resolution.Daily).Symbol,0.4), # iShares 20+ Year Treasury ETF (TLT)
            (self.AddEquity('IEF', Resolution.Daily).Symbol,0.15),  #iShares 7 – 10 Year Treasury ETF (IEF)
            (self.AddEquity('GLD', Resolution.Daily).Symbol,0.075), #SPDR Gold Shares ETF (GLD),  #SPDR Gold Shares (GLD)  
            (self.AddEquity('DBC', Resolution.Daily).Symbol,0.075) # PowerShares DB Commodity Index Tracking Fund (DBC)"
            ]
        self.Schedule.On(self.DateRules.MonthStart(self.etfs[0][0]), self.TimeRules.AfterMarketOpen(self.etfs[0][0]), self.Rebalance)
        self.leverage = 1.5
        self.monthCounter = 1
        # Set Benchmark
        self.SetBenchmark("SPY")
        # Variable to hold the last calculated benchmark value
        self.lastBenchmarkValue = None
        # Our inital benchmark value scaled to match our portfolio
        self.BenchmarkPerformance = self.Portfolio.TotalPortfolioValue
        
    def OnData(self, data):
       
        benchmark = self.Securities["SPY"].Close
        # Calculate the performance of our benchmark and update our benchmark value for plotting
        if self.lastBenchmarkValue is not None:
           self.BenchmarkPerformance = self.BenchmarkPerformance * (benchmark/self.lastBenchmarkValue)
        # store today's benchmark close price for use tomorrow
        self.lastBenchmarkValue = benchmark
        # make our plots
        self.Plot("Strategy vs Benchmark", "Portfolio Value", self.Portfolio.TotalPortfolioValue)
        self.Plot("Strategy vs Benchmark", "Benchmark", self.BenchmarkPerformance)
     
    def Rebalance(self):
        if self.monthCounter is 12:
            self.SetHoldings([PortfolioTarget(etf,target*self.leverage) for etf,target in self.etfs])
            self.monthCounter = 1
            
        else:
            self.monthCounter = self.monthCounter+1