Overall Statistics |
Total Trades
19852
Average Win
0.16%
Average Loss
-0.15%
Compounding Annual Return
7.888%
Drawdown
26.900%
Expectancy
0.098
Net Profit
323.568%
Sharpe Ratio
0.766
Loss Rate
47%
Win Rate
53%
Profit-Loss Ratio
1.07
Alpha
0.087
Beta
-0.129
Annual Standard Deviation
0.103
Annual Variance
0.011
Information Ratio
0.07
Tracking Error
0.233
Treynor Ratio
-0.61
Total Fees
$0.00
|
# https://quantpedia.com/strategies/time-series-momentum-effect/ from datetime import datetime import numpy as np from collections import deque import math class Time_Series_Momentum(QCAlgorithm): def Initialize(self): self.SetStartDate(2000, 1, 1) self.SetEndDate(2019, 1, 1) self.SetCash(100000) self.symbols = ["CME_S1", # Soybean Futures, Continuous Contract "CME_W1", # Wheat Futures, Continuous Contract "CME_SM1", # Soybean Meal Futures, Continuous Contract "CME_BO1", # Soybean Oil Futures, Continuous Contract "CME_C1", # Corn Futures, Continuous Contract "CME_O1", # Oats Futures, Continuous Contract "CME_LC1", # Live Cattle Futures, Continuous Contract "CME_FC1", # Feeder Cattle Futures, Continuous Contract "CME_LN1", # Lean Hog Futures, Continuous Contract "CME_GC1", # Gold Futures, Continuous Contract "CME_SI1", # Silver Futures, Continuous Contract "CME_PL1", # Platinum Futures, Continuous Contract "CME_CL1", # Crude Oil Futures, Continuous Contract "CME_HG1", # Copper Futures, Continuous Contract "CME_LB1", # Random Length Lumber Futures, Continuous Contract "CME_NG1", # Natural Gas (Henry Hub) Physical Futures, Continuous Contract "CME_PA1", # Palladium Futures, Continuous Contract "CME_RR1", # Rough Rice Futures, Continuous Contract "ICE_CC1", # Cocoa Futures, Continuous Contract "ICE_CT1", # Cotton No. 2 Futures, Continuous Contract "ICE_KC1", # Coffee C Futures, Continuous Contract "ICE_O1", # Heating Oil Futures, Continuous Contract "ICE_OJ1", # Orange Juice Futures, Continuous Contract "ICE_SB1" # Sugar No. 11 Futures, Continuous Contract "CME_AD1", # Australian Dollar Futures, Continuous Contract #1 "CME_BP1", # British Pound Futures, Continuous Contract #1 "CME_CD1", # Canadian Dollar Futures, Continuous Contract #1 "CME_EC1", # Euro FX Futures, Continuous Contract #1 "CME_JY1", # Japanese Yen Futures, Continuous Contract #1 "CME_MP1", # Mexican Peso Futures, Continuous Contract #1 "CME_SF1", # Swiss Franc Futures, Continuous Contract #1 "ICE_DX1", # US Dollar Index Futures, Continuous Contract #1 "CME_NQ1", # E-mini NASDAQ 100 Futures, Continuous Contract #1 "EUREX_FDAX1", # DAX Futures, Continuous Contract #1 "CME_ES1", # E-mini S&P 500 Futures, Continuous Contract #1 "EUREX_FSMI1", # SMI Futures, Continuous Contract #1 "EUREX_FSTX1", # STOXX Europe 50 Index Futures, Continuous Contract #1 "LIFFE_FCE1", # CAC40 Index Futures, Continuous Contract #1 "LIFFE_Z1", # FTSE 100 Index Futures, Continuous Contract #1 "SGX_NK1", # SGX Nikkei 225 Index Futures, Continuous Contract #1 "CME_TY1", # 10 Yr Note Futures, Continuous Contract #1 "CME_FV1", # 5 Yr Note Futures, Continuous Contract #1 "CME_TU1", # 2 Yr Note Futures, Continuous Contract #1 "EUREX_FGBL1", # Euro-Bund (10Y) Futures, Continuous Contract #1 "EUREX_FGBM1", # Euro-Bobl Futures, Continuous Contract #1 "EUREX_FGBS1", # Euro-Schatz Futures, Continuous Contract #1 "SGX_JB1", # SGX 10-Year Mini Japanese Government Bond Futures "LIFFE_R1" # Long Gilt Futures, Continuous Contract #1 ] self.lookup_period = 12*21 self.data = {} self.SetWarmUp(self.lookup_period) # True -> Quantpedia data # False -> Quandl free data self.use_quantpedia_data = True if not self.use_quantpedia_data: self.symbols = ['CHRIS/' + x for x in self.symbols] self.leverage = 4.0 for symbol in self.symbols: data = None if self.use_quantpedia_data: data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily) else: data = self.AddData(QuandlFutures, symbol, Resolution.Daily) data.SetLeverage(self.leverage) self.data[symbol] = deque(maxlen=self.lookup_period) self.Schedule.On(self.DateRules.MonthStart(self.symbols[0]), self.TimeRules.AfterMarketOpen(self.symbols[0]), self.Rebalance) def OnData(self, data): for symbol in self.symbols: if self.Securities.ContainsKey(symbol): price = self.Securities[symbol].Price if price != 0: self.data[symbol].append(price) def Rebalance(self): if self.IsWarmingUp: return # Return sorting returns = {} volatility = {} for symbol in self.symbols: if len(self.data[symbol]) == self.data[symbol].maxlen: prices = [x for x in self.data[symbol]] returns[symbol] = self.Return(prices) prices = prices[-60:] volatility[symbol] = self.Volatility(prices) #else: return if len(returns) == 0: return long = [x[0] for x in returns.items() if x[1] > 0] short = [x[0] for x in returns.items() if x[1] < 0] # Volatility weighting total_vol = sum([1/volatility[x] for x in long + short]) if total_vol == 0: return weight = {} for symbol in long + short: vol = volatility[symbol] if vol != 0: weight[symbol] = (1.0 / vol) / total_vol else: weight[symbol] = 0 self.Liquidate() for symbol in long: self.SetHoldings(symbol, self.leverage*weight[symbol]) for symbol in short: self.SetHoldings(symbol, -self.leverage*weight[symbol]) def Return(self, history): return (history[-1] - history[0]) / history[0] def Volatility(self, history): prices = np.array(history) returns = (prices[1:]-prices[:-1])/prices[:-1] return np.std(returns) # Quantpedia data class QuantpediaFutures(PythonData): def GetSource(self, config, date, isLiveMode): return SubscriptionDataSource("http://data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv) def Reader(self, config, line, date, isLiveMode): data = QuantpediaFutures() data.Symbol = config.Symbol try: if not line[0].isdigit(): return None split = line.split(';') data.Time = datetime.strptime(split[0], "%d.%m.%Y") + timedelta(days=1) data['settle'] = float(split[1]) data.Value = float(split[1]) except: return None return data # Quandl free data class QuandlFutures(PythonQuandl): def __init__(self): self.ValueColumnName = "settle"