Option Factor Momentum

1from AlgorithmImports import *
2from pandas.core.frame import DataFrame
3from typing import List, Dict
4#endregion
5
6class MultiRiskPremiaStrategy(QCAlgorithm):
7
8def Initialize(self):
9 self.SetStartDate(2010, 1, 1)
10 self.SetCash(100000)
11
12 self.period:int = 12 * 21
13 self.leverage:int = 3
14 self.quantile:int = 5
15
16 self.data:Dict[str, float] = {}
17
18 self.equity_ids:List[str] = [
19     '173',    # Volatility Term Structure Predicts Option Returns
20     '20',     # Volatility Risk Premium Effect
21     '216',    # Active Collar Strategy
22     '233',    # Using Straddles to Trade on Earnings Announcements
23     '237',    # Dispersion Trading
24     '257',    # Cloning Hedge Fund Indexes
25     '280',    # Trading the VIX Futures Roll and Volatility Premiums with VIX Options
26     '329',    # Portfolio Hedging Using VIX Options
27     '335',    # Cross-Sectional One-Month Equity ATM Straddle Trading Strategy
28     '336',    # Cross-Sectional Six-Month Equity ATM Straddle Trading Strategy
29     '337',    # Cross-Sectional Six- Minus One-Month Equity ATM Straddle Calendar Trading Strategy
30     '338',    # Timing of Option Returns
31     '347',    # Mispricing of Equity Options With Different Time To Maturity
32     '349',    # Trading Options During Expiration Weekends
33     '402',    # International Volatility Arbitrage
34     '405',    # Using VIX to Time Options Writing
35     '41',     # Turn of the Month in Equity Indexes
36     '481',    # Holding Artificial VIX in a Portfolio
37     '511',    # Cheap Options Are Expensive
38     '599',    # Barbell Strategy
39     '604',    # Reversal on Straddles
40     '605',    # Momentum on Straddles
41     '627',    # Hedging Portfolio
42     '63',     # Trendfollowing Combined with Volatility Premium 
43     '72',     # Combined Mean Reversion and Momentum in Foreign Exchange Markets
44     '786',    # Option Trading and Returns versus the 52-Week High
45     '787',    # Option Trading and Returns versus the 52-Week Low
46     '855',    # Avoid Equity Bear Markets with a Market Timing Strategy
47 ]
48
49 for equity_id in self.equity_ids:
50     data:Security = self.AddData(QuantpediaEquity, equity_id, Resolution.Daily)
51     data.SetLeverage(self.leverage)
52     data.SetFeeModel(CustomFeeModel())
53
54     self.data[equity_id] = self.ROC(equity_id, self.period, Resolution.Daily)
55
56 self.SetWarmUp(self.period)
57 self.Settings.MinimumOrderMarginPortfolioPercentage = 0.
58
59 self.recent_month:int = -1
60
61def OnData(self, data: Slice) -> None:
62 if self.IsWarmingUp:
63     return
64 if self.Time.month == self.recent_month:
65     return
66 self.recent_month = self.Time.month
67
68 _last_update_date:Dict[str, datetime.date] = QuantpediaEquity.get_last_update_date()
69 
70 # calculate performance
71 performance:Dict[str, float] = { x : self.data[x].Current.Value for x in self.data \
72             if self.data[x].IsReady and \
73             x in data and data[x] and \
74             _last_update_date[x] > self.Time.date() }
75
76 long:List[str] = []
77 short:List[str] = []
78 
79 # performance sorting
80 if len(performance) >= self.quantile:
81     sorted_by_perf:List[str] = sorted(performance.items(), key = lambda x: x[1], reverse = True)
82     quantile:int = int(len(sorted_by_perf) / self.quantile)
83     long = [x[0] for x in sorted_by_perf[:quantile]]
84     short = [x[0] for x in sorted_by_perf[-quantile:]]
85
86 # trade execution
87 invested:List[str] = [x.Key.Value for x in self.Portfolio if x.Value.Invested]
88 for symbol in invested:
89     if symbol not in long + short:
90         self.Liquidate(symbol)
91 
92 for symbol in long:
93     self.SetHoldings(symbol, 1 / len(long))
94 for symbol in short:
95     self.SetHoldings(symbol, -1 / len(short))
96 
97# Quantpedia strategy equity curve data.
98# NOTE: IMPORTANT: Data order must be ascending (datewise)
99class QuantpediaEquity(PythonData):
100def GetSource(self, config:SubscriptionDataConfig, date:datetime, isLiveMode:bool) -> SubscriptionDataSource:
101 return SubscriptionDataSource(f"data.quantpedia.com/backtesting_data/equity/quantpedia_strategies/925_related/{config.Symbol.Value}.csv", SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)
102
103_last_update_date:Dict[str, datetime.date] = {}
104
105@staticmethod
106def get_last_update_date() -> Dict[str, datetime.date]:
107return QuantpediaEquity._last_update_date
108
109def Reader(self, config: SubscriptionDataConfig, line: str, date: datetime, isLive: bool) -> BaseData:
110 data:config = QuantpediaEquity()
111 data.Symbol = config.Symbol
112 
113 if not line[0].isdigit(): return None
114 split:List[str] = line.split(';')
115 
116 data.Time = datetime.strptime(split[0], "%Y-%m-%d") + timedelta(days=1)
117 data['close'] = float(split[1])
118 data.Value = float(split[1])
119 
120 # store last update date
121 if config.Symbol.Value not in QuantpediaEquity._last_update_date:
122     QuantpediaEquity._last_update_date[config.Symbol.Value] = datetime(1,1,1).date()
123
124 if data.Time.date() > QuantpediaEquity._last_update_date[config.Symbol.Value]:
125     QuantpediaEquity._last_update_date[config.Symbol.Value] = data.Time.date()
126 
127 return data
128 
129# Custom fee model.
130class CustomFeeModel(FeeModel):
131def GetOrderFee(self, parameters):
132 fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
133 return OrderFee(CashAmount(fee, "USD"))