Overall Statistics |
Total Trades 167 Average Win 13.40% Average Loss -3.50% Compounding Annual Return 58.010% Drawdown 41.000% Expectancy 2.196 Net Profit 43687.741% Sharpe Ratio 1.562 Probabilistic Sharpe Ratio 85.084% Loss Rate 34% Win Rate 66% Profit-Loss Ratio 3.82 Alpha 0.531 Beta 0.159 Annual Standard Deviation 0.351 Annual Variance 0.123 Information Ratio 1.161 Tracking Error 0.383 Treynor Ratio 3.449 Total Fees $22580.79 Estimated Strategy Capacity $170000.00 |
''' Intersection of ROC comparison using OUT_DAY approach by Vladimir v1.1 (diversified static lists) inspired by Peter Guenther, Tentor Testivis, Dan Whitnable, Thomas Chang. ''' import numpy as np # ------------------------------------------------------------------------------------------- STOCKS = ['QQQ','MSFT','NFLX','AMZN','TSLA']; BONDS = ['TLT','TLH']; VOLA = 126; BASE_RET = 85; LEV = 0.99; # ------------------------------------------------------------------------------------------- class ROC_Comparison_IN_OUT(QCAlgorithm): def Initialize(self): self.SetStartDate(2008, 1, 1) # self.SetEndDate(2021, 1, 1) self.cap = 100000 self.STOCKS = [self.AddEquity('QQQ', Resolution.Minute).Symbol, self.AddEquity('MSFT', Resolution.Minute).Symbol, self.AddEquity('NFLX', Resolution.Minute).Symbol, self.AddEquity('AMZN', Resolution.Minute).Symbol, self.AddEquity('TSLA', Resolution.Minute).Symbol] self.mom_lookback = 6*21 self.stock_selection = None self.ret_reb_month = 0 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((1.0 - 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 = 0 self.outday = self.count if self.count >= self.outday + wait_days: self.bull = 1 self.count += 1 def trade(self): if self.ret_reb_month!=self.Time.month: self.stock_selection = self.calc_return(self.STOCKS, 1) self.ret_reb_month = self.Time.month 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))