Overall Statistics |
Total Orders
1457
Average Win
0.96%
Average Loss
-1.24%
Compounding Annual Return
3.849%
Drawdown
65.400%
Expectancy
0.105
Start Equity
100000
End Equity
256472.47
Net Profit
156.472%
Sharpe Ratio
0.117
Sortino Ratio
0.125
Probabilistic Sharpe Ratio
0.000%
Loss Rate
38%
Win Rate
62%
Profit-Loss Ratio
0.78
Alpha
-0.019
Beta
0.904
Annual Standard Deviation
0.181
Annual Variance
0.033
Information Ratio
-0.205
Tracking Error
0.111
Treynor Ratio
0.023
Total Fees
$1642.70
Estimated Strategy Capacity
$100000.00
Lowest Capacity Asset
EZA SM0K4WNJE545
Portfolio Turnover
2.31%
|
# https://quantpedia.com/strategies/momentum-factor-effect-in-country-equity-indexes/ # # The investment universe consists of ETFs (funds) which invest in individual countries’ equity indexes. The top 5 countries with the best X – month # (where X depends on investors choice, studies show X to be best as 10-12) momentum are chosen as an investment, and portfolio is rebalanced once in a month. from AlgorithmImports import * class MomentumFactorEffectinCountryEquityIndexes(QCAlgorithm): def Initialize(self): self.SetStartDate(2000, 1, 1) self.SetCash(100000) # Daily ROC data. self.perf = {} self.period = 6 * 21 self.SetWarmUp(self.period, Resolution.Daily) self.symbols = [ "EWA", # iShares MSCI Australia Index ETF "EWO", # iShares MSCI Austria Investable Mkt Index ETF "EWK", # iShares MSCI Belgium Investable Market Index ETF "EWZ", # iShares MSCI Brazil Index ETF "EWC", # iShares MSCI Canada Index ETF "FXI", # iShares China Large-Cap ETF "EWQ", # iShares MSCI France Index ETF "EWG", # iShares MSCI Germany ETF "EWH", # iShares MSCI Hong Kong Index ETF "EWI", # iShares MSCI Italy Index ETF "EWJ", # iShares MSCI Japan Index ETF "EWM", # iShares MSCI Malaysia Index ETF "EWW", # iShares MSCI Mexico Inv. Mt. Idx "EWN", # iShares MSCI Netherlands Index ETF "EWS", # iShares MSCI Singapore Index ETF "EZA", # iShares MSCI South Africe Index ETF "EWY", # iShares MSCI South Korea ETF "EWP", # iShares MSCI Spain Index ETF "EWD", # iShares MSCI Sweden Index ETF "EWL", # iShares MSCI Switzerland Index ETF "EWT", # iShares MSCI Taiwan Index ETF "THD", # iShares MSCI Thailand Index ETF "EWU", # iShares MSCI United Kingdom Index ETF "SPY", # SPDR S&P 500 ETF ] self.traded_count = 5 for symbol in self.symbols: data = self.AddEquity(symbol, Resolution.Minute) data.SetFeeModel(CustomFeeModel()) data.SetLeverage(5) self.perf[symbol] = self.ROC(symbol, self.period, Resolution.Daily) self.recent_month = -1 def OnData(self, data): if self.IsWarmingUp: return if not (self.Time.hour == 9 and self.Time.minute == 31): return if self.Time.month == self.recent_month: return self.recent_month = self.Time.month sorted_by_momentum = sorted([x for x in self.perf.items() if x[1].IsReady and x[0] in data and data[x[0]]], key = lambda x: x[1].Current.Value, reverse = True) long = [] if len(sorted_by_momentum) >= self.traded_count: long = [x[0] for x in sorted_by_momentum[:self.traded_count]] # trade execution invested = [x.Key for x in self.Portfolio if x.Value.Invested] for symbol in invested: if symbol not in long: self.Liquidate(symbol) for symbol in long: self.SetHoldings(symbol, 1 / len(long)) # Custom fee model class CustomFeeModel(FeeModel): def GetOrderFee(self, parameters): fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005 return OrderFee(CashAmount(fee, "USD"))