Overall Statistics |
Total Trades
985
Average Win
0.63%
Average Loss
-0.72%
Compounding Annual Return
-6.664%
Drawdown
58.600%
Expectancy
-0.205
Net Profit
-51.531%
Sharpe Ratio
-0.565
Loss Rate
58%
Win Rate
42%
Profit-Loss Ratio
0.88
Alpha
-0.049
Beta
-0.619
Annual Standard Deviation
0.108
Annual Variance
0.012
Information Ratio
-0.744
Tracking Error
0.108
Treynor Ratio
0.099
Total Fees
$0.00
|
# https://quantpedia.com/Screener/Details/21 # The futures data is non-adjusted price based on spot-month continuous contract calculations. # Raw data from ICE and CM from QuantConnect.Python import PythonQuandl from datetime import timedelta class CommidityMomentumEffect(QCAlgorithm): def Initialize(self): self.SetStartDate(2008,1, 1) self.SetEndDate(2018, 7, 1) self.SetCash(25000) self.cme_symbols = ["CHRIS/CME_S1", # Soybean Futures, Continuous Contract #1 "CHRIS/CME_W1", # Wheat Futures, Continuous Contract #1 "CHRIS/CME_SM1", # Soybean Meal Futures, Continuous Contract #1 "CHRIS/CME_BO1", # Soybean Oil Futures, Continuous Contract #1 "CHRIS/CME_C1", # Corn Futures, Continuous Contract #1 "CHRIS/CME_O1", # Oats Futures, Continuous Contract #1 "CHRIS/CME_LC1", # Live Cattle Futures, Continuous Contract #1 "CHRIS/CME_FC1", # Feeder Cattle Futures, Continuous Contract #1 "CHRIS/CME_LN1", # Lean Hog Futures, Continuous Contract #1 "CHRIS/CME_GC1", # Gold Futures, Continuous Contract #1 "CHRIS/CME_SI1", # Silver Futures, Continuous Contract #1 "CHRIS/CME_PL1", # Platinum Futures, Continuous Contract #1 ] self.ice_symbols = ["CHRIS/ICE_B1", # Brent Crude Futures, Continuous Contract "CHRIS/ICE_O1", # Heating Oil Futures, Continuous Contract #1 "CHRIS/ICE_M1", # UK Natural Gas Futures, Continuous Contract #1 "CHRIS/ICE_CT1", # Cotton No. 2 Futures, Continuous Contract "CHRIS/ICE_OJ1", # Orange Juice Futures, Continuous Contract "CHRIS/ICE_KC1", # Coffee C Futures, Continuous Contract "CHRIS/ICE_CC1", # Cocoa Futures, Continuous Contract "CHRIS/ICE_G1", # Gas Oil Futures, Continuous Contract "CHRIS/ICE_RS1", # Canola Futures, Continuous Contract ] period = 252 self.symbols = self.cme_symbols + self.ice_symbols self.roc = {} for symbol in self.symbols: self.AddData(QuandlFutures, symbol, Resolution.Daily) self.roc[symbol] = RateOfChange(period) hist = self.History([symbol], 400, Resolution.Daily).loc[symbol] for i in hist.itertuples(): self.roc[symbol].Update(i.Index, i.settle) # Rebalance the portfolio every month self.Schedule.On(self.DateRules.MonthStart("CHRIS/CME_S1"), self.TimeRules.AfterMarketOpen("CHRIS/CME_S1"), self.Rebalance) def OnData(self, data): # Update the indicator value every day for symbol in self.symbols: if data.ContainsKey(symbol) and self.roc[symbol].IsReady: self.roc[symbol].Update(self.Time, data[symbol].Settle) def Rebalance(self): # sorted futures by 12-month return reversely self.sorted_roc = sorted(self.roc, key = lambda x: self.roc[x].Current.Value, reverse=True) number_futures = int(0.25*len(self.sorted_roc)) if number_futures == 0: number_futures = int(0.4*len(self.sorted_roc)) self.long = self.sorted_roc[:number_futures] self.short = self.sorted_roc[-number_futures:] for kvp in self.Portfolio: security_hold = kvp.Value # liquidate the futures which is no longer in the trading list if security_hold.Invested and (security_hold.Symbol.Value not in (self.long+self.short)): self.Liquidate(security_hold.Symbol) for long in self.long: self.SetHoldings(long, 0.5/number_futures) for short in self.short: self.SetHoldings(short, -0.5/number_futures) class QuandlFutures(PythonQuandl): def __init__(self): self.ValueColumnName = "settle"