Trend Following Trading Strategies for Currencies

1import numpy as np
2from AlgorithmImports import *
3from math import sqrt
4from numpy import exp
5class TrendFollowingTradingStrategiesforCurrencies(QCAlgorithm):
6def Initialize(self):
7 self.SetStartDate(2000, 1, 1)
8 self.SetCash(100000)
9 
10 self.symbols = [
11                 "CME_AD1", # Australian Dollar Futures, Continuous Contract #1
12                 "CME_BP1", # British Pound Futures, Continuous Contract #1
13                 "CME_CD1", # Canadian Dollar Futures, Continuous Contract #1
14                 "CME_EC1", # Euro FX Futures, Continuous Contract #1
15                 "CME_JY1", # Japanese Yen Futures, Continuous Contract #1
16                 "CME_MP1", # Mexican Peso Futures, Continuous Contract #1
17                 "CME_NE1", # New Zealand Dollar Futures, Continuous Contract #1
18                 "CME_SF1", # Swiss Franc Futures, Continuous Contract #1
19                 ]
20 
21 self.period = 12 * 21
22 self.SetWarmUp(self.period)
23 
24 self.leverage = 5
25 # Daily price data.
26 self.data = {}
27 
28 # EMA pairs.
29 self.ema_8_24 = {}
30 self.ema_16_48 = {}
31 self.ema_32_96 = {}
32 
33 self.Settings.MinAbsolutePortfolioTargetPercentage = 1e-30
34 for symbol in self.symbols:
35     data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
36     data.SetFeeModel(CustomFeeModel())
37     data.SetLeverage(self.leverage * 2)
38     
39     self.data[symbol] = RollingWindow[float](self.period)
40
41     self.ema_8_24[symbol] = [self.EMA(symbol, 8, Resolution.Daily), self.EMA(symbol, 24, Resolution.Daily)]
42     self.ema_16_48[symbol] = [self.EMA(symbol, 16, Resolution.Daily), self.EMA(symbol, 48, Resolution.Daily)]
43     self.ema_32_96[symbol] = [self.EMA(symbol, 32, Resolution.Daily), self.EMA(symbol, 96, Resolution.Daily)]
44     
45def OnData(self, data):
46 # Store daily price data.
47 for symbol in self.symbols:
48     if symbol in data and data[symbol]:
49         price = data[symbol].Value
50         self.data[symbol].Add(price)
51 
52 if self.IsWarmingUp: return
53 signal = {}
54 for symbol in self.symbols:
55     if self.securities[symbol].get_last_data() and self.time.date() > QuantpediaFutures.get_last_update_date()[symbol]:
56         self.liquidate(symbol)
57         continue
58     # Daily data is ready.
59     if not self.data[symbol].IsReady:
60         continue
61 
62     # First signal.
63     # Source paper equation 5, page 5.
64     x1 = self.ema_8_24[symbol][0].Current.Value - self.ema_8_24[symbol][1].Current.Value
65     x2 = self.ema_16_48[symbol][0].Current.Value - self.ema_16_48[symbol][1].Current.Value
66     x3 = self.ema_32_96[symbol][0].Current.Value - self.ema_32_96[symbol][1].Current.Value
67     
68     x = np.array([x1, x2, x3])
69     prices = [x for x in self.data[symbol]]
70     price_std_short = np.std(prices[:3 * 21])
71     price_std_long = np.std(prices)
72     
73     # Normalization.
74     # Source paper equation 6, page 6
75     y = x / price_std_short
76     
77     # Normalization #2.
78     # Source paper equation 7, page 6
79     z = y / price_std_long
80     
81     # Response function.
82     u = (z * exp((-z**2) / 4)) / (sqrt(2) * exp(-1/2))
83     signal[symbol] = sum(1/len(z) * u)
84 
85 if len(signal) == 0:
86     self.Liquidate()
87     return
88             
89 # Trade execution
90 for symbol, weight in signal.items():
91     w = (1/len(signal)) * (self.leverage * weight)
92     self.SetHoldings(symbol, w)
93     
94# Custom fee model
95class CustomFeeModel(FeeModel):
96def GetOrderFee(self, parameters):
97 fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
98 return OrderFee(CashAmount(fee, "USD"))
99# Quantpedia data
100# NOTE: IMPORTANT: Data order must be ascending (datewise)
101class QuantpediaFutures(PythonData):
102_last_update_date:Dict[Symbol, datetime.date] = {}
103@staticmethod
104def get_last_update_date() -> Dict[Symbol, datetime.date]:
105return QuantpediaFutures._last_update_date
106def GetSource(self, config, date, isLiveMode):
107 return SubscriptionDataSource("data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)
108def Reader(self, config, line, date, isLiveMode):
109 data = QuantpediaFutures()
110 data.Symbol = config.Symbol
111 
112 if not line[0].isdigit(): return None
113 split = line.split(';')
114 
115 data.Time = datetime.strptime(split[0], "%d.%m.%Y") + timedelta(days=1)
116 data['settle'] = float(split[1])
117 data.Value = float(split[1])
118 if config.Symbol.Value not in QuantpediaFutures._last_update_date:
119     QuantpediaFutures._last_update_date[config.Symbol.Value] = datetime(1,1,1).date()
120 if data.Time.date() > QuantpediaFutures._last_update_date[config.Symbol.Value]:
121     QuantpediaFutures._last_update_date[config.Symbol.Value] = data.Time.date()
122 return data