货币期货的隔夜-日内每周反转策略

1from AlgorithmImports import *
2class OvernightIntradayWeeklyReversalCurrency(QCAlgorithm):
3def Initialize(self):
4 self.SetStartDate(2000, 1, 1)
5 self.SetCash(100000)
6 
7 self.symbols = [
8                 "CME_AD1", # Australian Dollar Futures, Continuous Contract #1
9                 "CME_BP1", # British Pound Futures, Continuous Contract #1
10                 "CME_CD1", # Canadian Dollar Futures, Continuous Contract #1
11                 "CME_EC1", # Euro FX Futures, Continuous Contract #1
12                 "CME_JY1", # Japanese Yen Futures, Continuous Contract #1
13                 "CME_MP1", # Mexican Peso Futures, Continuous Contract #1
14                 "CME_NE1", # New Zealand Dollar Futures, Continuous Contract #1
15                 "CME_SF1"  # Swiss Franc Futures, Continuous Contract #1
16                 ]
17 
18 self.friday_close = {}
19 self.leverage = 1
20 
21 for symbol in self.symbols:
22     data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
23     data.SetFeeModel(CustomFeeModel())
24     data.SetLeverage(5)
25     self.friday_close[symbol] = 0
26     
27def OnData(self, data):
28 # Saturday -> Friday close available
29 if self.Time.date().weekday() == 5:
30     for symbol in self.symbols:
31         if symbol in data and data[symbol]:
32             price = data[symbol].Value
33             if price != 0:
34                 self.friday_close[symbol] = price
35             
36     self.Liquidate()
37 # Tuesday -> Monday close available
38 elif self.Time.date().weekday() == 1:
39     returns = {}
40     
41     for symbol in self.symbols:
42         # Check if data is still coming.
43         if self.securities[symbol].get_last_data() and self.time.date() > QuantpediaFutures.get_last_update_date()[symbol]:
44             self.liquidate(symbol)
45             continue
46         if symbol in data and data[symbol]:
47             price = data[symbol].Value
48             if price != 0 and symbol in self.friday_close and self.friday_close[symbol] != 0:
49                 returns[symbol] = price / self.friday_close[symbol] - 1
50     
51     self.friday_close.clear()
52     if len(returns) == 0: 
53         return
54     
55     ret_mean = np.mean([x[1] for x in returns.items()])
56     
57     weight = {}
58     N = len(returns)
59     for symbol in returns:
60         weight[symbol] = -(1/N) * (returns[symbol] - ret_mean) * 100
61
62     for symbol in weight:
63         self.SetHoldings(symbol, self.leverage * weight[symbol])
64# Quantpedia data.
65# NOTE: IMPORTANT: Data order must be ascending (datewise)
66class QuantpediaFutures(PythonData):
67_last_update_date:Dict[Symbol, datetime.date] = {}
68@staticmethod
69def get_last_update_date() -> Dict[Symbol, datetime.date]:
70return QuantpediaFutures._last_update_date
71def GetSource(self, config, date, isLiveMode):
72 return SubscriptionDataSource("data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)
73def Reader(self, config, line, date, isLiveMode):
74 data = QuantpediaFutures()
75 data.Symbol = config.Symbol
76 
77 if not line[0].isdigit(): return None
78 split = line.split(';')
79 
80 data.Time = datetime.strptime(split[0], "%d.%m.%Y") + timedelta(days=1)
81 data['back_adjusted'] = float(split[1])
82 data['spliced'] = float(split[2])
83 data.Value = float(split[1])
84 if config.Symbol.Value not in QuantpediaFutures._last_update_date:
85     QuantpediaFutures._last_update_date[config.Symbol.Value] = datetime(1,1,1).date()
86 if data.Time.date() > QuantpediaFutures._last_update_date[config.Symbol.Value]:
87     QuantpediaFutures._last_update_date[config.Symbol.Value] = data.Time.date()
88     
89 return data
90# Custom fee model.
91class CustomFeeModel(FeeModel):
92def GetOrderFee(self, parameters):
93 fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
94 return OrderFee(CashAmount(fee, "USD"))