| Overall Statistics |
|
Total Trades 199 Average Win 5.56% Average Loss -1.56% Compounding Annual Return 26.399% Drawdown 19.300% Expectancy 2.138 Net Profit 1988.664% Sharpe Ratio 1.408 Probabilistic Sharpe Ratio 85.732% Loss Rate 31% Win Rate 69% Profit-Loss Ratio 3.57 Alpha 0.222 Beta 0.068 Annual Standard Deviation 0.162 Annual Variance 0.026 Information Ratio 0.551 Tracking Error 0.238 Treynor Ratio 3.342 Total Fees $6267.71 |
"""
DUAL MOMENTUM IN OUT with static parameters v2.2 by Vladimir
inspired by Peter Guenther, Tentor Testivis, Dan Whitnable, Thomas Chang and T Smith.
"""
import numpy as np
class DualMomentumInOut(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2008, 1, 1)
# self.SetEndDate(2020, 11, 27)
self.cap = 100000
self.STK1 = self.AddEquity('QQQ', Resolution.Minute).Symbol
self.STK2 = self.AddEquity('FDN', Resolution.Minute).Symbol
self.BND1 = self.AddEquity('TLT', Resolution.Minute).Symbol
self.BND2 = self.AddEquity('TLH', Resolution.Minute).Symbol
self.ASSETS = [self.STK1, self.STK2, self.BND1, self.BND2]
self.XLI = self.AddEquity('XLI', Resolution.Daily).Symbol
self.XLU = self.AddEquity('XLU', Resolution.Daily).Symbol
self.SLV = self.AddEquity('SLV', Resolution.Daily).Symbol
self.GLD = self.AddEquity('GLD', Resolution.Daily).Symbol
self.PAIRS = [self.XLI, self.XLU, self.SLV, self.GLD]
self.MKT = self.AddEquity('SPY', Resolution.Daily).Symbol
self.RETURN = 85
self.WAIT_DAYS = 17
self.RET = 126
self.EXCL = 5
self.selected_bond = self.BND1
self.selected_stock = self.STK1
self.bull = 1
self.count = 0
self.outday = 0
self.spy = []
self.wt = {}
self.real_wt = {}
self.SetWarmUp(self.RET)
self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen('SPY', 100),
self.calculate_signal)
self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen('SPY', 120),
self.trade_out)
self.Schedule.On(self.DateRules.WeekEnd(), self.TimeRules.AfterMarketOpen('SPY', 120),
self.trade_in)
self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.BeforeMarketClose('SPY', 0),
self.record_vars)
def returns(self, symbol, period, excl):
prices = self.History(symbol, period + excl, Resolution.Daily).close
return prices[-excl] / prices[0]
def calculate_signal(self):
P = self.History(self.PAIRS, self.RETURN + 1, Resolution.Daily)['close'].unstack(level = 0).dropna()
if (len(P.columns) < 2):
return
diff_iu = (P[self.XLI].iloc[-1] / P[self.XLI].iloc[0]) - (P[self.XLU].iloc[-1] / P[self.XLU].iloc[0])
diff_sg = (P[self.SLV].iloc[-1] / P[self.SLV].iloc[0]) - (P[self.GLD].iloc[-1] / P[self.GLD].iloc[0])
exit = (diff_iu < 0 and diff_sg < 0)
if exit:
self.bull = 0;
self.outday = self.count;
if (self.count >= self.outday + self.WAIT_DAYS):
self.bull = 1
self.count += 1
if self.returns(self.BND1, self.RET, self.EXCL) < self.returns(self.BND2, self.RET, self.EXCL):
self.selected_bond = self.BND2
elif self.returns(self.BND1, self.RET, self.EXCL) > self.returns(self.BND2, self.RET, self.EXCL):
self.selected_bond = self.BND1
if self.returns(self.STK1, self.RET, self.EXCL) < self.returns(self.STK2, self.RET, self.EXCL):
self.selected_stock = self.STK2
elif self.returns(self.STK1, self.RET, self.EXCL) > self.returns(self.STK2, self.RET, self.EXCL):
self.selected_stock = self.STK1
def trade_out(self):
if not self.bull:
for sec in self.ASSETS:
self.wt[sec] = 0.99 if sec is self.selected_bond else 0 if sec is self.selected_bond else 0
self.trade()
def trade_in(self):
if self.bull:
for sec in self.ASSETS:
self.wt[sec] = 0.99 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 record_vars(self):
hist = self.History([self.MKT], 2, Resolution.Daily)['close'].unstack(level= 0).dropna()
self.spy.append(hist[self.MKT].iloc[-1])
spy_perf = self.spy[-1] / self.spy[0] * self.cap
self.Plot("Strategy Equity", "SPY", spy_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))