| Overall Statistics |
|
Total Trades 23 Average Win 6.12% Average Loss -2.85% Compounding Annual Return 29.276% Drawdown 19.400% Expectancy 1.579 Net Profit 57.528% Sharpe Ratio 1.139 Probabilistic Sharpe Ratio 52.150% Loss Rate 18% Win Rate 82% Profit-Loss Ratio 2.15 Alpha 0 Beta 0 Annual Standard Deviation 0.186 Annual Variance 0.035 Information Ratio 1.139 Tracking Error 0.186 Treynor Ratio 0 Total Fees $64.00 Estimated Strategy Capacity $1900000.00 Lowest Capacity Asset TLT SGNKIKYGE9NP |
# v2.51 Dual Momentum with Out Days by Vladimir
import numpy as np
# ----------------------------------------------------------
STOCKS = ['QQQ', 'SPY']; BONDS = ['TLT', 'IEF'];
VOLA = 126; BASE_RET = 83; RET = 252; EXCL = 21; LEV = 1.00;
# ----------------------------------------------------------
class DualMomentumWithOutDays(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 1, 1)
# self.SetEndDate(2020, 11, 27)
self.cap = 100000
self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)
self.STK1 = self.AddEquity('QQQ', Resolution.Minute).Symbol
self.STK2 = self.AddEquity('SPY', Resolution.Minute).Symbol
self.BND1 = self.AddEquity('TLT', Resolution.Minute).Symbol
self.BND2 = self.AddEquity('IEF', Resolution.Minute).Symbol
self.ASSETS = [self.STK1, self.STK2, self.BND1, self.BND2]
self.SLV = self.AddEquity('SLV', Resolution.Daily).Symbol
self.GLD = self.AddEquity('GLD', Resolution.Daily).Symbol
self.XLI = self.AddEquity('XLI', Resolution.Daily).Symbol
self.XLU = self.AddEquity('XLU', Resolution.Daily).Symbol
self.DBB = self.AddEquity('DBB', Resolution.Daily).Symbol
self.UUP = self.AddEquity('UUP', Resolution.Daily).Symbol
self.MKT = self.AddEquity('SPY', Resolution.Daily).Symbol
self.pairs = [self.SLV, self.GLD, self.XLI, self.XLU, self.DBB, self.UUP]
self.bull = 1
self.count = 0
self.outday = 0
self.wt = {}
self.real_wt = {}
self.mkt = []
self.SetWarmUp(VOLA, Resolution.Daily)
self.selected_bond = self.BND1
self.selected_stock = self.STK1
self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen('SPY', 100),
self.calculate_signal)
symbols = [self.MKT] + self.pairs
for symbol in symbols:
self.consolidator = TradeBarConsolidator(timedelta(days=1))
self.consolidator.DataConsolidated += self.consolidation_handler
self.SubscriptionManager.AddConsolidator(symbol, self.consolidator)
self.history = self.History(symbols, VOLA + 1, Resolution.Daily)
if self.history.empty or 'close' not in self.history.columns:
return
self.history = self.history['close'].unstack(level=0).dropna()
def consolidation_handler(self, sender, consolidated):
self.history.loc[consolidated.EndTime, consolidated.Symbol] = consolidated.Close
self.history = self.history.iloc[-(VOLA + 1):]
def returns(self, symbol, period, excl):
prices = self.History(symbol, TimeSpan.FromDays(period + excl), Resolution.Daily).close
return prices[-excl] / prices[0]
def calculate_signal(self):
vola = self.history[[self.MKT]].pct_change().std() * np.sqrt(252)
wait_days = int(vola * BASE_RET)
period = int((1.0 - vola) * BASE_RET)
r = self.history.pct_change(period).iloc[-1]
exit = ((r[self.SLV] < r[self.GLD]) and (r[self.XLI] < r[self.XLU]) and (r[self.DBB] < r[self.UUP]))
if exit:
self.bull = False
self.outday = self.count
if self.count >= self.outday + wait_days:
self.bull = True
self.count += 1
if self.returns(self.BND1, RET, EXCL) < self.returns(self.BND2, RET, EXCL):
self.selected_bond = self.BND2
elif self.returns(self.BND1, RET, EXCL) > self.returns(self.BND2, RET, EXCL):
self.selected_bond = self.BND1
if self.returns(self.STK1, RET, EXCL) < self.returns(self.STK2, RET, EXCL):
self.selected_stock = self.STK2
elif self.returns(self.STK1, RET, EXCL) > self.returns(self.STK2, RET, EXCL):
self.selected_stock = self.STK1
if not self.bull:
for sec in self.ASSETS:
self.wt[sec] = LEV if sec is self.selected_bond else 0 if sec is self.selected_bond else 0
self.trade()
elif self.bull:
for sec in self.ASSETS:
self.wt[sec] = LEV if sec is self.selected_stock else 0
self.trade()
def trade(self):
for sec, weight in self.wt.items():
if weight == 0 and self.Portfolio[sec].IsLong:
self.Liquidate(sec)
cond1 = weight == 0 and self.Portfolio[sec].IsLong
cond2 = weight > 0 and not self.Portfolio[sec].Invested
if cond1 or cond2:
self.SetHoldings(sec, weight)
def OnEndOfDay(self, symbol):
mkt_price = self.Securities[self.MKT].Close
self.mkt.append(mkt_price)
mkt_perf = self.mkt[-1] / self.mkt[0] * self.cap
self.Plot('Strategy Equity', 'SPY', mkt_perf)
account_leverage = self.Portfolio.TotalHoldingsValue / self.Portfolio.TotalPortfolioValue
self.Plot('Holdings', 'leverage', round(account_leverage, 1))
for sec, weight in self.wt.items():
self.real_wt[sec] = round(self.ActiveSecurities[sec].Holdings.Quantity * self.Securities[sec].Price / self.Portfolio.TotalPortfolioValue,4)
self.Plot('Holdings', self.Securities[sec].Symbol, round(self.real_wt[sec], 3))