Halloween Effect during Low and High CAPE Months

1from AlgorithmImports import *
2from dateutil.relativedelta import relativedelta
3class HalloweenEffectCAPEMonths(QCAlgorithm):
4def initialize(self) -> None:
5 self.set_start_date(2000, 1, 1)
6 self.set_cash(100_000)
7 self._period: int = 36
8 self._traded_symbol: Symbol = self.add_equity('SPY', Resolution.Daily).symbol
9 
10 self.cape: Symbol = self.add_data(QuantpediaMonthlyData, 'SHILLER_PE_RATIO_MONTH').symbol
11 self.cape_data: RollingWindow = RollingWindow[float](self._period)
12 
13 self._rebalance_flag: bool = False
14 self._close_month: int = 0
15 self._trading_month: int = 11
16 
17 self.settings.minimum_order_margin_portfolio_percentage = 0.
18 self.settings.daily_precise_end_time = False
19 self.schedule.on(
20     self.date_rules.month_start(self._traded_symbol), 
21     self.time_rules.after_market_open(self._traded_symbol), 
22     self._rebalance
23 )
24def on_data(self, slice: Slice) -> None:
25 custom_data_last_update_date: Dict[Symbol, datetime.date] = LastDateHandler.get_last_update_date()
26 if self.securities[self.cape].get_last_data() and self.time.date() > custom_data_last_update_date[self.cape]:
27     self.liquidate()
28     return
29 
30 if self.cape in slice and slice[self.cape]:
31     cape: float = slice[self.cape].value
32     self.cape_data.add(cape)
33     
34 if slice.contains_key(self._traded_symbol) and slice[self._traded_symbol]:
35     if not self.cape_data.is_ready: return
36     
37     if self.time.month == self._close_month:
38         self.liquidate(self._traded_symbol)
39     
40     if self.time.month == self._trading_month:
41         if self._rebalance_flag:
42             self.set_holdings(self._traded_symbol, 1)
43             self._rebalance_flag = False
44def _rebalance(self) -> None:
45 self._rebalance_flag = True
46 # Trade in October in order to have September CAPE data.
47 if self.time.month != 10: return
48
49 cape_values: List[float] = list(self.cape_data)
50 cape_median: float = median(cape_values)
51 cape: float = self.cape_data[0]
52 
53 if cape < cape_median:
54     self._close_month = 10
55 else:
56     self._close_month = 4
57 
58class LastDateHandler():
59_last_update_date: Dict[Symbol, datetime.date] = {}
60
61@staticmethod
62def get_last_update_date() -> Dict[Symbol, datetime.date]:
63return LastDateHandler._last_update_date
64# Quantpedia monthly custom data.
65# NOTE: IMPORTANT: Data order must be ascending (datewise)
66class QuantpediaMonthlyData(PythonData):
67def GetSource(self, config: SubscriptionDataConfig, date: datetime, isLiveMode: bool) -> SubscriptionDataSource:
68 return SubscriptionDataSource(f'data.quantpedia.com/backtesting_data/economic/{config.Symbol.Value}.csv', SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)
69def Reader(self, config: SubscriptionDataConfig, line: str, date: datetime, isLiveMode: bool) -> BaseData:
70 data = QuantpediaMonthlyData()
71 data.Symbol = config.Symbol
72 
73 if not line[0].isdigit(): return None
74 split: str = line.split(';')
75 
76 data.Time = datetime.strptime(split[0], "%Y-%m-%d") + relativedelta(months=1)
77 data.Value = float(split[1])
78 if config.Symbol not in LastDateHandler._last_update_date:
79     LastDateHandler._last_update_date[config.Symbol] = datetime(1,1,1).date()
80 if data.Time.date() > LastDateHandler._last_update_date[config.Symbol]:
81     LastDateHandler._last_update_date[config.Symbol] = data.Time.date()
82 return data