Combined Value and Profitability in US and Chinese Equities

1from AlgorithmImports import *
2from data_tools import CustomFeeModel, ChineseStocks, ChineseIncomeStatement, SymbolData, FamaFrench, ChineseBalanceSheet
3from typing import List, Dict
4# endregion
5
6class CombinedValueandProfitabilityinUSandChineseEquities(QCAlgorithm):
7
8def Initialize(self):
9self.SetStartDate(2015, 1, 1)   # Chinese data starts in 2015
10self.SetCash(100000)
11
12self.leverage:int = 5
13self.chinese_portfolio_weight:float = 0.5
14
15self.us_portfolio_part_weight:float = 0.25
16
17self.recent_month:int = -1
18
19self.min_stocks:int = 7
20
21self.percent_stocks_to_trade:float = 0.3
22
23self.data:Dict[Symbol, SymbolData] = {}
24
25self.top_size_symbol_count:int = 100
26ticker_file_str:str = self.Download('data.quantpedia.com/backtesting_data/equity/chinese_stocks/large_cap_500.csv')
27tickers:List[str] = ticker_file_str.split('\r\n')[:self.top_size_symbol_count]
28
29for t in tickers:
30    data = self.AddData(ChineseStocks, t, Resolution.Daily)
31    data.SetFeeModel(CustomFeeModel())
32    data.SetLeverage(self.leverage)
33
34    stock_symbol:Symbol = data.Symbol
35    data = self.AddData(ChineseIncomeStatement, t, Resolution.Daily)
36    income_statement_symbol:Symbol = data.Symbol
37
38    data = self.AddData(ChineseBalanceSheet, t, Resolution.Daily)
39    balance_sheet_symbol:Symbol = data.Symbol
40
41    self.data[stock_symbol] = SymbolData(income_statement_symbol, balance_sheet_symbol)
42
43data = self.AddData(FamaFrench, 'fama_french_6_book_to_market_daily_price', Resolution.Daily)
44data.SetFeeModel(CustomFeeModel())
45self.HML = data.Symbol
46
47data = self.AddData(FamaFrench, 'fama_french_6_profitability_daily_price', Resolution.Daily)
48data.SetFeeModel(CustomFeeModel())
49self.RMW = data.Symbol
50
51def OnData(self, data: Slice):
52curr_date:datetime.date = self.Time.date()
53
54# store daily data
55for symbol, symbol_data in self.data.items():
56    income_statement_symbol:Symbol = symbol_data.get_income_statement_symbol()
57    balance_sheet_symbol:Symbol = symbol_data.get_balance_sheet_symbol()
58
59    if data.ContainsKey(symbol):
60        price_data:Dict[str, str] = data[symbol].GetProperty('price_data')
61        # valid price data
62        if data[symbol].Value != 0. and price_data:
63            mc:float = float(price_data['marketValue'])
64            symbol_data.set_market_equity(mc)
65
66    if data.ContainsKey(income_statement_symbol):
67        # update operating, gross and net profit from income statement
68        operating_profit:float = float(data[income_statement_symbol].GetProperty('operating_profit'))
69        gross_profit:float = float(data[income_statement_symbol].GetProperty('gross_profit'))
70        net_profit:float = float(data[income_statement_symbol].GetProperty('net_profit'))
71
72        symbol_data.set_operating_profit(operating_profit)
73        symbol_data.set_gross_profit(gross_profit)
74        symbol_data.set_net_profit(net_profit)
75
76    if data.ContainsKey(balance_sheet_symbol):
77        # update total assets and total liabilities from balance sheet
78        total_assets:float = float(data[balance_sheet_symbol].GetProperty('total_assets'))
79        total_liabilities:float = float(data[balance_sheet_symbol].GetProperty('total_liabilities'))
80
81        symbol_data.set_total_assets(total_assets)
82        symbol_data.set_total_liabilities(total_liabilities)
83
84# rebalance monthly
85if self.recent_month == self.Time.month:
86    return
87self.recent_month = self.Time.month
88
89symbols_with_measures:List[Symbol] = []
90measures:Dict[str, Dict[Symbol, float]] = {
91    'OP_to_ME': {},
92    'GP_to_ME': {},
93    'NP_to_ME': {},
94    'GP_to_TA': {},
95    'OP_to_BE': {},
96    'NP_to_BE': {},
97}
98
99for symbol, symbol_data in self.data.items():
100    if not symbol_data.is_ready() or symbol not in data or not data[symbol] or \
101        data[symbol].Value == 0 or not self.Securities[symbol].IsTradable:
102        continue
103    
104    # calculate required mesaures
105    measures['OP_to_ME'][symbol] = symbol_data.get_operating_profit_to_market_equity()
106    measures['GP_to_ME'][symbol] = symbol_data.get_gross_profit_to_market_equity()
107    measures['NP_to_ME'][symbol] = symbol_data.get_net_profit_to_market_equity()
108    measures['GP_to_TA'][symbol] = symbol_data.get_gross_profit_to_total_assets()
109    measures['OP_to_BE'][symbol] = symbol_data.get_operating_profit_to_book_equity()
110    measures['NP_to_BE'][symbol] = symbol_data.get_net_profit_to_book_equity()
111
112    symbols_with_measures.append(symbol)
113
114# make sure there are enough stocks with measures for selection
115if len(symbols_with_measures) < self.min_stocks:
116    self.Liquidate()
117    return
118
119# sort dictionary of measures by measure values
120measures_sorted:List[List[Symbol]] = []
121for _, value_by_symbol in measures.items():
122    sorted_measure:List[Symbol] = [x[0] for x in sorted(value_by_symbol.items(), key=lambda item: item[1])]
123    measures_sorted.append(sorted_measure)
124
125# calculate total rank based on stock orders in sorted measures
126total_rank:Dict[Symbol, float] = {}
127for symbol in symbols_with_measures:
128    rank:int = sum(list(map(lambda sorted_measure: sorted_measure.index(symbol), measures_sorted)))
129
130    total_rank[symbol] = rank
131
132# sort by rank select long and trade
133sorted_by_rank:List[Symbol] = [x[0] for x in sorted(total_rank.items(), key=lambda item: item[1])]
134
135long_leg:List[Symbol] = sorted_by_rank[-int(len(sorted_by_rank) * self.percent_stocks_to_trade):]
136
137# trade execution
138invested:List[Symbol] = [x.Key for x in self.Portfolio if x.Value.Invested and x.Key not in [self.HML, self.RMW]]
139for symbol in invested:
140    if symbol not in long_leg:
141        self.Liquidate(symbol)
142
143long_length:int = len(long_leg)
144for symbol in long_leg:
145    self.SetHoldings(symbol, (1 / long_length) * self.chinese_portfolio_weight)
146
147if not self.Securities[self.HML].Invested:
148    self.SetHoldings(self.HML, self.us_portfolio_part_weight)
149
150if not self.Securities[self.RMW].Invested:
151    self.SetHoldings(self.RMW, self.us_portfolio_part_weight)