Overall Statistics |
Total Trades 103 Average Win 4.72% Average Loss -4.13% Compounding Annual Return 7.594% Drawdown 36.700% Expectancy 0.303 Net Profit 66.942% Sharpe Ratio 0.352 Probabilistic Sharpe Ratio 1.836% Loss Rate 39% Win Rate 61% Profit-Loss Ratio 1.14 Alpha 0 Beta 0 Annual Standard Deviation 0.224 Annual Variance 0.05 Information Ratio 0.352 Tracking Error 0.224 Treynor Ratio 0 Total Fees $907.91 Estimated Strategy Capacity $7800000.00 Lowest Capacity Asset XLI RGRPZX100F39 |
#region imports from AlgorithmImports import * #endregion class VerticalNadionShield(QCAlgorithm): def Initialize(self): self.SetStartDate(2016, 1, 1) # Set Start Date self.SetEndDate(2022,12,31) # set end date self.SetCash(100000) # Set Strategy Cash self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin) self.leverage = 1 #self.equities = ["SPY", "SCZ"] #self.equities = ["SPY", "SCZ", "XLV", "XLK", "XLI", "XLU", "XLF", "XLY", "XLP", "XLB", "XLE", "PSR", "IYZ", "USO"] self.equities = ["XLV", "XLK", "XLI", "XLU", "XLF", "XLY", "XLP", "XLB", "XLE", "PSR", "IYZ", "USO"] self.equityCombinedMomentum = {} #self.bonds = ["TLT", "TIP"] self.bonds = ["TLT", "TIP", "BIL", "AGG"] self.bondCombinedMomentum = {} for equity in self.equities: self.AddEquity(equity, Resolution.Hour) self.Securities[equity].SetDataNormalizationMode(DataNormalizationMode.TotalReturn) self.equityCombinedMomentum[equity] = CombinedMomentum(self, equity) for bond in self.bonds: self.AddEquity(bond, Resolution.Hour) self.Securities[bond].SetDataNormalizationMode(DataNormalizationMode.TotalReturn) self.bondCombinedMomentum[bond] = CombinedMomentum(self, bond) self.SetWarmUp(125) def shiftAssets(self, target): if not (self.Portfolio[target].Invested): for symbol in self.Portfolio.Keys: self.Liquidate(symbol) if not self.Portfolio.Invested: self.MarketOnCloseOrder(target, self.CalculateOrderQuantity(target, 1 * self.leverage)) def getMonthLastTradingDay(self): month_last_day = DateTime(self.Time.year, self.Time.month, DateTime.DaysInMonth(self.Time.year, self.Time.month)) tradingDays = self.TradingCalendar.GetDaysByType(TradingDayType.BusinessDay, DateTime(self.Time.year, self.Time.month, 1), month_last_day) tradingDays = [day.Date.date() for day in tradingDays] return tradingDays[-1] def OnData(self, data): if self.IsWarmingUp: return if (self.Time.date() == self.getMonthLastTradingDay()) and (self.Time.hour == 15): topEquities = sorted(self.equityCombinedMomentum.items(), key=lambda x: x[1].getValue(), reverse=True) topBonds = sorted(self.bondCombinedMomentum.items(), key=lambda x: x[1].getValue(), reverse=True) if (topEquities[0][1].getValue() > 0): self.shiftAssets(topEquities[0][0]) else: self.shiftAssets(topBonds[0][0]) class CombinedMomentum(): def __init__(self, algo, symbol): self.fst = algo.MOMP(symbol, 21, Resolution.Daily) # 1 mos self.med = algo.MOMP(symbol, 63, Resolution.Daily) # 3 mos self.slw = algo.MOMP(symbol, 126, Resolution.Daily) # 6 mos def getValue(self): value = (self.fst.Current.Value + self.med.Current.Value + self.slw.Current.Value) / 3 return value