| Overall Statistics |
|
Total Trades 255 Average Win 14.79% Average Loss -4.71% Compounding Annual Return 67.339% Drawdown 70.700% Expectancy 1.639 Net Profit 131691.248% Sharpe Ratio 1.322 Probabilistic Sharpe Ratio 59.465% Loss Rate 36% Win Rate 64% Profit-Loss Ratio 3.14 Alpha 0.569 Beta -0.136 Annual Standard Deviation 0.421 Annual Variance 0.178 Information Ratio 1.012 Tracking Error 0.462 Treynor Ratio -4.084 Total Fees $5317.12 Estimated Strategy Capacity $8100000.00 Lowest Capacity Asset TLT SGNKIKYGE9NP |
import numpy as np
# -------------------------------------------------------------------------------------------
STOCKS = ['BTCUSD','ETHUSD']; BONDS = ['TLT']; VOLA = 126; BASE_RET = 85; LEV = 0.99;
NSTOCKS=1;
MOMLOOK=15;
REBA=2;
CAPITALE=25000
# -------------------------------------------------------------------------------------------
#NO XLF, XLP iyz ---------------------- ,'XLE','XLP','IYR','VNQI','XLI','XLF','XLU','XLY','XLV','IWM',
#IYZ telecom; XLE energy;IYR us real estate VNQI global real; XLI industrials; XLF financials; XLU utilities
#XLY consumer discretionari; GDX materials; XLV healthcare e biotech; IWM small cap; PBW clean energy 'SMH','IGV','FDN'
class ROC_Comparison_IN_OUT(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2008, 1, 1)
self.cap = CAPITALE
self.SetCash(self.cap)
self.STOCKS = [self.AddCrypto(ticker, Resolution.Daily).Symbol for ticker in STOCKS]
self.mom_lookback = MOMLOOK
self.stock_selection = None
self.ret_reb_month = 0
self.rebalance_counter = 0
self.rebalance_interval = REBA
self.BONDS = [self.AddEquity(ticker, Resolution.Minute).Symbol for ticker in BONDS]
self.ASSETS = [self.STOCKS, self.BONDS]
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(timedelta(350))
self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen('SPY', 60),
self.daily_check)
self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen('SPY', 120),
self.trade)
symbols = [self.MKT] + self.pairs + self.STOCKS + self.BONDS
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[-(max(VOLA, self.mom_lookback)+1):]
def daily_check(self):
vola = self.history[[self.MKT]].iloc[-(VOLA+1):].pct_change().std() * np.sqrt(252)
wait_days = int(vola * BASE_RET)
period = int((1 - 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 = 0
self.outday = self.count
if self.count >= self.outday + wait_days:
self.bull = 1
self.count += 1
def trade(self):
### MOD Flex 27.04.2021 ###
#if self.ret_reb_month!=self.Time.month:
# self.stock_selection = self.calc_return(self.STOCKS, 1)
# self.ret_reb_month = self.Time.month
if self.rebalance_counter == 0 or self.rebalance_counter >= self.rebalance_interval:
if self.rebalance_counter == 0:
self.rebalance_counter += 1
else:
self.rebalance_counter = 1
self.stock_selection = self.calc_return(self.STOCKS, NSTOCKS)
else:
self.rebalance_counter += 1
### MOD Flex 27.04.2021 ###
for sec in self.STOCKS:
self.wt[sec] = LEV/len(self.stock_selection) if self.bull and (sec in self.stock_selection) else 0;
for sec in self.BONDS:
self.wt[sec] = 0 if self.bull else LEV/len(self.BONDS);
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 calc_return(self, stocks, num):
ret = {}
for symbol in stocks:
try:
ret[symbol] = (self.history[[symbol]].iloc[-1] / self.history[[symbol]].iloc[-(self.mom_lookback)] - 1).iloc[0]
except:
self.Debug(str(symbol))
continue
ret = sorted(ret, key = ret.get, reverse = True)[:num]
return ret
def OnEndOfDay(self):
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))