Market Breadth in Global Equities

1from AlgorithmImports import *
2from pandas.core.frame import DataFrame
3class MarketBreadthInGlobalEquities(QCAlgorithm):
4def Initialize(self):
5self.SetStartDate(2000, 1, 1)
6self.SetCash(100000)
7
8etf_tickers: List[Tuple[str, str]] = [
9    # (CountryId, ticker)
10    ("AUS", "EWA"), # iShares MSCI Australia Index ETF
11    ("BRA", "EWZ"),  # iShares MSCI Brazil Index ETF
12    ("CAN", "EWC"),  # iShares MSCI Canada Index ETF
13    ("CHN", "FXI"),  # iShares China Large-Cap ETF
14    ("FRA", "EWQ"),  # iShares MSCI France Index ETF
15    ("DEU", "EWG"),  # iShares MSCI Germany ETF
16    ("HKG", "EWH"),  # iShares MSCI Hong Kong Index ETF
17    ("JPN", "EWJ"),  # iShares MSCI Japan Index ETF
18    ("MEX", "EWW"),  # iShares MSCI Mexico Inv. Mt. Idx
19    ("NLD", "EWN"),  # iShares MSCI Netherlands Index ETF
20    ("SGP", "EWS"),  # iShares MSCI Singapore Index ETF
21    ("KOR", "EWY"),  # iShares MSCI South Korea ETF
22    ("CHE", "EWL"),  # iShares MSCI Switzerland Index ETF
23    ("GBR", "EWU"),  # iShares MSCI United Kingdom Index ETF
24    ("USA", "SPY"),  # SPDR S&P 500 ETF
25    ("IRL", "EIRL"),  # iShares MSCI Ireland ETF
26    ("ISR", "EIS"),  # iShares MSCI Israel ETF    
27]
28
29self.data: Dict[Symbol, SymbolData] = {}
30self.etf_by_country: Dict[str, Symbol] = {}
31
32self.long: Dict[Symbol] = []
33self.short: Dict[Symbol] = []
34
35self.period: int = 2 * 12 * 21 # 2 years of daily closes
36self.count_to_invest: int = 2 # We go 2 etfs long and 2 etfs short, because our universe consists of country ETF from 17 countries.
37self.leverage: int = 3
38
39for country_id, ticker in etf_tickers:
40    security: Security = self.AddEquity(ticker, Resolution.Daily)
41    security.SetFeeModel(CustomFeeModel())
42    security.SetLeverage(self.leverage)
43    
44    self.etf_by_country[country_id] = security.Symbol
45    
46market: Symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
47
48self.selection_flag: bool = False
49self.UniverseSettings.Resolution = Resolution.Daily
50self.Settings.MinimumOrderMarginPortfolioPercentage = 0.
51self.AddUniverse(self.FundamentalSelectionFunction)
52self.Schedule.On(self.DateRules.MonthStart(market), self.TimeRules.AfterMarketOpen(market), self.Selection)
53self.settings.daily_precise_end_time = False
54def FundamentalSelectionFunction(self, fundamental: List[Fundamental]) -> List[Symbol]:
55for stock in fundamental:
56    symbol: Symbol = stock.Symbol
57    
58    if symbol in self.data:
59        self.data[symbol].update(stock.AdjustedPrice)
60
61if not self.selection_flag:
62    return Universe.Unchanged
63
64selected: List[Fundamental] = [x for x in fundamental if x.HasFundamentalData and x.CompanyReference.BusinessCountryID in self.etf_by_country]
65
66country_stocks: Dict[str, CountryStocks] = {}
67for stock in selected:
68    symbol: Symbol = stock.Symbol
69    if symbol not in self.data:
70        self.data[symbol] = SymbolData(self.period)
71        history: DataFrame = self.History(symbol, self.period, Resolution.Daily)
72        if history.empty:
73            self.Log(f"Not enough data for {symbol} yet")
74            continue
75        closes: pd.Series = history.loc[symbol].close
76        for time, close in closes.items():
77            self.data[symbol].update(close)
78    
79    if self.data[symbol].is_ready():
80        country_id: str = stock.CompanyReference.BusinessCountryID
81        performance: float = self.data[symbol].performance()
82    
83        if country_id not in country_stocks:
84            country_stocks[country_id] = CountryStocks()
85        
86        if performance > 0.:
87            country_stocks[country_id].increase_rising()
88        else:
89            country_stocks[country_id].increase_falling()
90        
91if len(country_stocks) == 0:
92    return Universe.Unchanged
93    
94sorted_by_market_breadth: List[str] = [x[0] for x in sorted(country_stocks.items(), key=lambda item: item[1].market_breadth())]
95
96self.long = [self.etf_by_country[country_id] for country_id in sorted_by_market_breadth[-self.count_to_invest:]]
97self.short = [self.etf_by_country[country_id] for country_id in sorted_by_market_breadth[:self.count_to_invest]]
98    
99return self.long + self.short
100
101def OnData(self, data: Slice) -> None:
102if not self.selection_flag:
103    return
104self.selection_flag = False
105
106# order execution
107targets:List[PortfolioTarget] = []
108for i, portfolio in enumerate([self.long, self.short]):
109    for symbol in portfolio:
110        if symbol in data and data[symbol]:
111            targets.append(PortfolioTarget(symbol, ((-1) ** i) / len(portfolio)))
112
113self.SetHoldings(targets, True)
114self.long.clear()
115self.short.clear()
116
117def Selection(self) -> None:
118self.selection_flag = True
119
120class SymbolData():
121def __init__(self, period: int):
122self._closes:RollingWindow = RollingWindow[float](period)
123
124def update(self, close: float) -> None:
125self._closes.Add(close)
126
127def is_ready(self) -> bool:
128return self._closes.IsReady
129
130def performance(self) -> float:
131return self._closes[0] / self._closes[self._closes.Count - 1] - 1
132
133class CountryStocks():
134def __init__(self):
135self._rising_stocks_count: int = 0
136self._falling_stocks_count: int = 0
137
138def increase_rising(self) -> None:
139self._rising_stocks_count += 1
140
141def increase_falling(self) -> None:
142self._falling_stocks_count += 1
143
144def market_breadth(self) -> float:
145result: float = (self._rising_stocks_count - self._falling_stocks_count) / (self._rising_stocks_count + self._falling_stocks_count)
146return result 
147
148# Custom fee model.
149class CustomFeeModel(FeeModel):
150def GetOrderFee(self, parameters):
151fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
152return OrderFee(CashAmount(fee, "USD"))