Overall Statistics |
Total Trades
1801
Average Win
0.68%
Average Loss
-1.00%
Compounding Annual Return
4.436%
Drawdown
64.700%
Expectancy
0.123
Net Profit
166.591%
Sharpe Ratio
0.261
Probabilistic Sharpe Ratio
0.001%
Loss Rate
33%
Win Rate
67%
Profit-Loss Ratio
0.68
Alpha
-0.006
Beta
0.916
Annual Standard Deviation
0.185
Annual Variance
0.034
Information Ratio
-0.096
Tracking Error
0.112
Treynor Ratio
0.053
Total Fees
$1738.37
Estimated Strategy Capacity
$1100000.00
Lowest Capacity Asset
THD U1BQSAW6XI79
|
# 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) 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 ] for symbol in self.symbols: data = self.AddEquity(symbol, Resolution.Daily) 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 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 = [x[0] for x in sorted_by_momentum[:5]] # 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"))