Timing Commodity Factor Portfolios

1from collections import deque
2from AlgorithmImports import *
3import numpy as np
4class TimingCommodityFactor(QCAlgorithm):
5def Initialize(self):
6 self.SetStartDate(2002, 1, 1)
7 self.SetCash(100000)
8 self.symbols = [
9     "CME_S1",   # Soybean Futures, Continuous Contract
10     "CME_W1",   # Wheat Futures, Continuous Contract
11     "CME_SM1",  # Soybean Meal Futures, Continuous Contract
12     "CME_BO1",  # Soybean Oil Futures, Continuous Contract
13     "CME_C1",   # Corn Futures, Continuous Contract
14     "CME_O1",   # Oats Futures, Continuous Contract
15     "CME_LC1",  # Live Cattle Futures, Continuous Contract
16     "CME_FC1",  # Feeder Cattle Futures, Continuous Contract
17     "CME_LN1",  # Lean Hog Futures, Continuous Contract
18     "CME_GC1",  # Gold Futures, Continuous Contract
19     "CME_SI1",  # Silver Futures, Continuous Contract
20     "CME_PL1",  # Platinum Futures, Continuous Contract
21     "CME_CL1",  # Crude Oil Futures, Continuous Contract
22     "CME_HG1",  # Copper Futures, Continuous Contract
23     "CME_LB1",  # Random Length Lumber Futures, Continuous Contract
24     # "CME_NG1",  # Natural Gas (Henry Hub) Physical Futures, Continuous Contract
25     "CME_PA1",  # Palladium Futures, Continuous Contract 
26     "CME_RR1",  # Rough Rice Futures, Continuous Contract
27     "CME_DA1",  # Class III Milk Futures
28     "ICE_RS1",  # Canola Futures, Continuous Contract
29     "ICE_GO1",  # Gas Oil Futures, Continuous Contract
30     "CME_RB2",  # Gasoline Futures, Continuous Contract
31     "CME_KW2",  # Wheat Kansas, Continuous Contract
32     "ICE_WT1",  # WTI Crude Futures, Continuous Contract
33                 
34     "ICE_CC1",  # Cocoa Futures, Continuous Contract 
35     "ICE_CT1",  # Cotton No. 2 Futures, Continuous Contract
36     "ICE_KC1",  # Coffee C Futures, Continuous Contract
37     "ICE_O1",   # Heating Oil Futures, Continuous Contract
38     "ICE_OJ1",  # Orange Juice Futures, Continuous Contract
39     "ICE_SB1",  # Sugar No. 11 Futures, Continuous Contract
40 ]
41 self.data = {}
42 self.top = {}
43 self.low = {}
44 
45 ret_period = 120
46 vol_period = 60
47 ma_period = 5
48 
49 self.SetWarmUp(max(ret_period, vol_period, ma_period))
50 
51 for symbol in self.symbols:
52     data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
53     data.SetLeverage(5)
54     data.SetFeeModel(CustomFeeModel())
55     
56     ma = self.SMA(symbol, ma_period, Resolution.Daily)
57     self.data[symbol] = SymbolData(symbol, ret_period, vol_period, ma)
58 self.Schedule.On(self.DateRules.MonthStart(self.symbols[0]), self.TimeRules.At(0, 0), self.Rebalance)
59def OnData(self, data):
60 last_update_date = {}
61 for symbol in self.data:
62     # data is still coming
63     if self.securities[symbol].get_last_data() and self.time.date() > QuantpediaFutures.get_last_update_date()[symbol]:
64         self.liquidate(symbol)
65         self.data[symbol].History.clear()
66         continue
67     symbol_obj = self.Symbol(symbol)
68     if symbol_obj in data.Keys:
69         if data[symbol_obj]:
70             price = data[symbol_obj].Value
71             self.data[symbol].Update(price)
72             last_update_date[symbol] = self.Time.date()
73 
74 if self.IsWarmingUp: return
75
76 sma_top = list(data for data in self.top if data[1].IsReady() and data[1].Price > data[1].MA.Current.Value and data[0] in last_update_date)
77 sma_low = list(data for data in self.low if data[1].IsReady() and data[1].Price < data[1].MA.Current.Value and data[0] in last_update_date)
78 for data in sma_top:
79     symbol = data[0]
80     symbol_data = data[1]
81     
82     if not self.Portfolio[symbol].IsLong:
83         if symbol_data.Price > symbol_data.MA.Current.Value:
84             if symbol_data.Weight != 0:
85                 self.SetHoldings(symbol, symbol_data.Weight)
86     elif self.Portfolio[symbol].IsLong:
87         if symbol_data.Price <= symbol_data.MA.Current.Value:
88             self.Liquidate(symbol)
89
90 for data in sma_low:
91     symbol = data[0]
92     symbol_data = data[1]
93     if not self.Portfolio[symbol].IsShort:
94         if symbol_data.Price < symbol_data.MA.Current.Value:
95             if symbol_data.Weight != 0:
96                 self.SetHoldings(symbol, symbol_data.Weight)
97     elif self.Portfolio[symbol].IsShort:
98         if symbol_data.Price >= symbol_data.MA.Current.Value:
99             self.Liquidate(symbol)       
100def Rebalance(self):
101 if self.IsWarmingUp: return
102 self.Liquidate()
103 sorted_by_ret = sorted([d for d in self.data.items() if d[1].IsReady()], key=lambda x: x[1].Return(), reverse = True)
104 self.top = sorted_by_ret[:int(1/3 * len(sorted_by_ret))]
105 self.low = sorted_by_ret[-int(1/3 * len(sorted_by_ret)):]
106 
107 # Weighting
108 total_vol = sum((1.0/data[1].Volatility()) for data in self.top if data[1].IsReady()) + sum((1.0/data[1].Volatility()) for data in self.low if data[1].IsReady())
109 for data in self.top + self.low:
110     if data[1].IsReady():
111         vol = data[1].Volatility()
112         data[1].Weight = (1.0 / vol) / total_vol
113class SymbolData:
114def __init__(self, symbol, ret_lookback, vol_lookback, ma):
115 self.Symbol = symbol
116 self.History = deque(maxlen=max(ret_lookback, vol_lookback))
117 self.Price = 0.0
118 self.MA = ma
119 self.Weight = 0
120 
121 self.ret_lookback = ret_lookback
122 self.vol_lookback = vol_lookback
123def IsReady(self):
124 return len(self.History) == self.History.maxlen
125 
126def Update(self, value):
127 self.Price = float(value)
128 self.History.append(float(value))
129def Return(self):
130 prices = np.array(self.History)[-self.ret_lookback:]
131 return (prices[-1]-prices[0])/prices[0]
132def Volatility(self):
133 prices = np.array(self.History)[-self.vol_lookback:]
134 returns = (prices[1:]-prices[:-1])/prices[:-1]
135 return np.std(returns)
136# Quantpedia data.
137# NOTE: IMPORTANT: Data order must be ascending (datewise)
138class QuantpediaFutures(PythonData):
139_last_update_date:Dict[Symbol, datetime.date] = {}
140@staticmethod
141def get_last_update_date() -> Dict[Symbol, datetime.date]:
142return QuantpediaFutures._last_update_date
143def GetSource(self, config, date, isLiveMode):
144 return SubscriptionDataSource("data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)
145def Reader(self, config, line, date, isLiveMode):
146 data = QuantpediaFutures()
147 data.Symbol = config.Symbol
148 
149 if not line[0].isdigit(): return None
150 split = line.split(';')
151 
152 data.Time = datetime.strptime(split[0], "%d.%m.%Y") + timedelta(days=1)
153 data['back_adjusted'] = float(split[1])
154 data['spliced'] = float(split[2])
155 data.Value = float(split[1])
156 if config.Symbol.Value not in QuantpediaFutures._last_update_date:
157     QuantpediaFutures._last_update_date[config.Symbol.Value] = datetime(1,1,1).date()
158 if data.Time.date() > QuantpediaFutures._last_update_date[config.Symbol.Value]:
159     QuantpediaFutures._last_update_date[config.Symbol.Value] = data.Time.date()
160 return data
161# Custom fee model.
162class CustomFeeModel(FeeModel):
163def GetOrderFee(self, parameters):
164 fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
165 return OrderFee(CashAmount(fee, "USD"))