Enhanced Returns of LGBT CEOs

1from AlgorithmImports import *
2import data_tools
3# endregion
4
5class EnhancedReturnsOfLGBTCEOs(QCAlgorithm):
6
7def Initialize(self):
8self.SetStartDate(2000, 1, 1)
9self.SetCash(100000)
10
11self.equally_weighted_flag:bool = False     # False - VW; True - EW
12
13self.leverage:int = 5
14
15self.universe:list[str] = []
16self.selected_symbols:list[Symbol] = []     # currently actively traded stocks
17self.market_cap:dict[Symbol, float] = {}
18
19self.market_symbol:Symbol = self.AddEquity('SPY', Resolution.Daily).Symbol
20
21self.LGBT_CEO_symbol:Symbol = self.AddData(data_tools.QuantpediaLGBT, 'LGBT_CEO', Resolution.Daily).Symbol
22
23self.selection_flag:bool = False
24self.UniverseSettings.Resolution = Resolution.Daily
25self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)       
26
27def OnSecuritiesChanged(self, changes):
28for security in changes.AddedSecurities:
29    security.SetFeeModel(data_tools.CustomFeeModel())
30    security.SetLeverage(self.leverage)
31
32def CoarseSelectionFunction(self, coarse):
33if not self.selection_flag:
34    return Universe.Unchanged
35
36selected_symbols:list[Symbol] = [equity.Symbol for equity in coarse if equity.Symbol.Value in self.universe]
37
38return selected_symbols
39
40def FineSelectionFunction(self, fine):
41if self.equally_weighted_flag:
42    self.selected_symbols = list(map(lambda stock: stock.Symbol, fine))
43
44    return self.selected_symbols
45else:
46    self.market_cap.clear()
47
48    for stock in fine:
49        market_cap:float = stock.MarketCap
50
51        if market_cap == 0:
52            continue
53
54        symbol:Symbol = stock.Symbol
55        self.market_cap[symbol] = market_cap
56
57    return list(self.market_cap.keys())
58
59def OnData(self, data: Slice):
60if self.selection_flag:
61    # rebalance whole active selection
62    if self.equally_weighted_flag:
63        length:int = len(self.selected_symbols)
64
65        for symbol in self.selected_symbols:
66            self.SetHoldings(symbol, 1 / length)
67    else:
68        total_cap:float = sum([x[1] for x in self.market_cap.items()])
69
70        for symbol, market_cap in self.market_cap.items():
71            self.SetHoldings(symbol, market_cap / total_cap)
72
73    self.selection_flag = False
74
75if self.LGBT_CEO_symbol in data and data[self.LGBT_CEO_symbol]:
76    stocks:list = data[self.LGBT_CEO_symbol].GetProperty('stocks')
77
78    for stock in stocks:
79        ticker:str = stock['ticker']
80        status:str = stock['status']
81
82        if status == 'start':
83            self.universe.append(ticker)
84        elif status == 'end' and ticker in self.universe:
85            self.universe.remove(ticker)
86            self.Liquidate(ticker)
87
88    # rebalance once the new data comes in
89    self.selection_flag = True