| Overall Statistics |
|
Total Orders 1369 Average Win 0.88% Average Loss -1.17% Compounding Annual Return 4.876% Drawdown 60.300% Expectancy 0.139 Start Equity 100000 End Equity 289209.90 Net Profit 189.210% Sharpe Ratio 0.16 Sortino Ratio 0.167 Probabilistic Sharpe Ratio 0.002% Loss Rate 35% Win Rate 65% Profit-Loss Ratio 0.76 Alpha -0.015 Beta 0.808 Annual Standard Deviation 0.174 Annual Variance 0.03 Information Ratio -0.202 Tracking Error 0.122 Treynor Ratio 0.034 Total Fees $9204.68 Estimated Strategy Capacity $90000.00 Lowest Capacity Asset ARGT UULB4CASSRXH Portfolio Turnover 1.93% |
#region imports
from AlgorithmImports import *
#endregion
# https://quantpedia.com/Screener/Details/15
class CountryEquityIndexesMomentumAlgorithm(QCAlgorithm):
def initialize(self):
self.set_start_date(2002, 1, 1)
self.set_cash(100000)
# create a dictionary to store momentum percent indicators for all symbols
self._data = {}
period = 6*21
# choose ten sector ETFs
symbols = ["EWJ", # iShares MSCI Japan Index ETF
"EZU", # iShares MSCI Eurozone ETF
"EFNL", # iShares MSCI Finland Capped Investable Market Index ETF
"EWW", # iShares MSCI Mexico Inv. Mt. Idx
"ERUS", # iShares MSCI Russia ETF
"IVV", # iShares S&P 500 Index
"ICOL", # Consumer Discretionary Select Sector SPDR Fund
"AAXJ", # iShares MSCI All Country Asia ex Japan Index ETF
"AUD", # Australia Bond Index Fund
"EWQ", # iShares MSCI France Index ETF
"BUND", # Pimco Germany Bond Index Fund
"EWH", # iShares MSCI Hong Kong Index ETF
"EPI", # WisdomTree India Earnings ETF
"EIDO" # iShares MSCI Indonesia Investable Market Index ETF
"EWI", # iShares MSCI Italy Index ETF
"GAF", # SPDR S&P Emerging Middle East & Africa ETF
"ENZL", # iShares MSCI New Zealand Investable Market Index Fund
"NORW" # Global X FTSE Norway 30 ETF
"EWY", # iShares MSCI South Korea Index ETF
"EWP", # iShares MSCI Spain Index ETF
"EWD", # iShares MSCI Sweden Index ETF
"EWL", # iShares MSCI Switzerland Index ETF
"GXC", # SPDR S&P China ETF
"EWC", # iShares MSCI Canada Index ETF
"EWZ", # iShares MSCI Brazil Index ETF
"ARGT", # Global X FTSE Argentina 20 ETF
"AND", # Global X FTSE Andean 40 ETF
"AIA", # iShares S&P Asia 50 Index ETF
"EWO", # iShares MSCI Austria Investable Mkt Index ETF
"EWK", # iShares MSCI Belgium Investable Market Index ETF
"BRAQ", # Global X Brazil Consumer ETF
"ECH", # iShares MSCI Chile Investable Market Index ETF
"CHIB", # Global X China Technology ETF
"EGPT", # Market Vectors Egypt Index ETF
"ADRU"] # BLDRS Europe 100 ADR Index ETF
# warm up the MOMP indicator
self.set_warm_up(period)
for symbol in symbols:
self.add_equity(symbol, Resolution.DAILY)
self._data[symbol] = self.momp(symbol, period, Resolution.DAILY)
# shcedule the function to fire at the month start
self.schedule.on(self.date_rules.month_start("IVV"), self.time_rules.after_market_open("IVV"), self._rebalance)
def _rebalance(self):
if self.is_warming_up:
return
data = {k: v for k, v in self._data.items() if v.is_ready}
top = pd.Series(data).sort_values(ascending=False)[:5]
self.set_holdings([PortfolioTarget(symbol, 1/len(top)) for symbol in top.index], True)