Front-Running S&P GSCI Index

1from AlgorithmImports import *
2from io import StringIO
3import pandas as pd
4#endregion
5class FrontRunningSAndPGSCIIndex(QCAlgorithm):
6
7def Initialize(self):
8self.SetStartDate(2010, 1, 1)
9self.SetCash(100000)
10
11self.symbols = {}
12self.trading_day = 0
13self.symbol = self.AddEquity('SPY', Resolution.Daily).Symbol
14
15csv_string_file = self.Download(f'data.quantpedia.com/backtesting_data/economic/future_comodities_RPWD.csv')
16# does not take first row as a header
17separated_file = pd.read_csv(StringIO(csv_string_file), sep=';', header=None)
18
19first_row = True   
20for row in separated_file.itertuples():
21    if first_row: # first row includes symbols of future comodities
22        first_row = False
23        for symbol in row[2:]:
24            data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
25            data.SetFeeModel(CustomFeeModel())
26            self.symbols[symbol] = {}
27    else:
28        for (value), (symbol) in zip(row[2:], self.symbols):
29            self.symbols[symbol][int(row[1])] = value # second element in row is year
30
31def OnData(self, data):
32if self.Time.month == 1:
33    if self.trading_day == 5:
34        short = {}
35        total_weight_changed = 0
36        
37        for symbol in self.symbols:
38            year = self.Time.year # get current year
39            # check if future comodity has weight for current year and year before
40            if (year in self.symbols[symbol]) and ((year - 1) in self.symbols[symbol]):
41                weight_change = float(self.symbols[symbol][year]) - float(self.symbols[symbol][year - 1])
42                if weight_change < 0: # if weight drops from last year, then go short on this future comodity
43                    total_weight_changed += (-weight_change) # calculating weight change for short weighting
44                    short[symbol] = weight_change
45        
46        if len(short) != 0:
47            for symbol, weight_change in short.items():
48                w = weight_change / total_weight_changed
49                self.SetHoldings(symbol, w) # weight_change is already minus, so this will go short
50            
51    elif self.trading_day == 10:
52        self.Liquidate()
53        
54    self.trading_day += 1
55else:
56    self.trading_day = 0
57    
58# Custom fee model
59class CustomFeeModel(FeeModel):
60def GetOrderFee(self, parameters):
61fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
62return OrderFee(CashAmount(fee, "USD"))
63
64# Quantpedia data
65# NOTE: IMPORTANT: Data order must be ascending (datewise)
66class QuantpediaFutures(PythonData):
67def GetSource(self, config, date, isLiveMode):
68return SubscriptionDataSource("data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)
69def Reader(self, config, line, date, isLiveMode):
70data = QuantpediaFutures()
71data.Symbol = config.Symbol
72
73if not line[0].isdigit(): return None
74split = line.split(';')
75
76data.Time = datetime.strptime(split[0], "%d.%m.%Y") + timedelta(days=1)
77data['settle'] = float(split[1])
78data.Value = float(split[1])
79return data