Overall Statistics |
Total Trades 35 Average Win 4.57% Average Loss -1.04% Compounding Annual Return 11.095% Drawdown 14.000% Expectancy 3.132 Net Profit 86.542% Sharpe Ratio 0.89 Probabilistic Sharpe Ratio 38.566% Loss Rate 24% Win Rate 76% Profit-Loss Ratio 4.40 Alpha 0.095 Beta -0.03 Annual Standard Deviation 0.103 Annual Variance 0.011 Information Ratio -0.009 Tracking Error 0.16 Treynor Ratio -3.091 Total Fees $92.07 |
from QuantConnect.Data.Custom.TradingEconomics import * class TradingEconomicsInterestRateAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2013, 11, 1) self.SetEndDate(2019, 10, 3); self.SetCash(100000) self.AddEquity("AGG", Resolution.Hour) self.AddEquity("SPY", Resolution.Hour) self.interestRate = self.AddData(TradingEconomicsCalendar, TradingEconomics.Calendar.UnitedStates.InterestRate).Symbol # Request 365 days of interest rate history with the TradingEconomicsCalendar custom data Symbol. # We should expect no historical data because 2013-11-01 is before the absolute first point of data history = self.History(TradingEconomicsCalendar, self.interestRate, 365, Resolution.Daily) # Count the number of items we get from our history request (should be zero) self.Debug(f"We got {len(history)} items from our history request") def OnData(self, data): # Make sure we have an interest rate calendar event if not data.ContainsKey(self.interestRate): return announcement = data[self.interestRate] # Confirm its a FED Rate Decision if announcement.Event != "Fed Interest Rate Decision": return # In the event of a rate increase, rebalance 50% to Bonds. interestRateDecreased = announcement.Actual <= announcement.Previous if interestRateDecreased: self.SetHoldings("SPY", 1) self.SetHoldings("AGG", 0) else: self.SetHoldings("SPY", 0.5) self.SetHoldings("AGG", 0.5)