| Overall Statistics |
|
Total Trades 1026 Average Win 0.21% Average Loss -0.18% Compounding Annual Return -46.471% Drawdown 13.500% Expectancy -0.035 Net Profit -5.169% Sharpe Ratio -0.345 Probabilistic Sharpe Ratio 33.114% Loss Rate 56% Win Rate 44% Profit-Loss Ratio 1.19 Alpha -0.518 Beta 1.451 Annual Standard Deviation 0.31 Annual Variance 0.096 Information Ratio -1.335 Tracking Error 0.293 Treynor Ratio -0.074 Total Fees $1289.72 Estimated Strategy Capacity $8700000.00 Lowest Capacity Asset CURO WQ6CRD6VV1ID |
class WellDressedSkyBlueSardine(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 12, 1)
self.SetEndDate(2020, 12, 31)
self.SetCash(100000)
self.AddUniverse(self.CoarseFilter, self.FineFilter)
self.UniverseSettings.Resolution = Resolution.Hour
self.Data = {}
def CoarseFilter(self, coarse):
sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
return [x.Symbol for x in sortedByDollarVolume if x.Price > 10
and x.HasFundamentalData][:200]
def FineFilter(self, fine):
sortedByPE = sorted(fine, key=lambda x: x.MarketCap)
return [x.Symbol for x in sortedByPE if x.MarketCap > 0][:10]
def OnSecuritiesChanged(self, changes):
# close positions in removed securities
for x in changes.RemovedSecurities:
self.Liquidate()
if x.Symbol in self.Data:
del self.Data[x.Symbol]
# can't open positions here since data might not be added correctly yet
for x in changes.AddedSecurities:
self.Data[x.Symbol] = SymbolData(self, x.Symbol)
def OnData(self, data):
SCTR = {}
for symboldata in self.Data.values():
if symboldata.IsReady():
self.Debug(f'{symboldata.symbol}\'s SCTR = {symboldata.SCTR()} in {self.Time}')
SCTR[symboldata.symbol] = symboldata.SCTR()
[self.SetHoldings(symbol, sctr/sum(list(SCTR.values()))) for symbol, sctr in SCTR.items()]
class SymbolData:
def __init__(self, algo, symbol):
self.symbol = symbol
self.EMA200 = algo.EMA(symbol, 200, Resolution.Daily)
self.EMA50 = algo.EMA(symbol, 50, Resolution.Daily)
self.ROC125 = algo.ROC(symbol, 125, Resolution.Daily)
self.ROC20 = algo.ROC(symbol, 20, Resolution.Daily)
self.PPO = algo.PPO(symbol, 12, 26, MovingAverageType.Exponential, Resolution.Daily)
self.RSI14 = algo.RSI(symbol, 14, MovingAverageType.Simple, Resolution.Daily)
self.PPOWindow = RollingWindow[float](3)
history = algo.History(symbol, 200, Resolution.Daily)
for index, bar in history.loc[symbol].iterrows():
self.EMA200.Update(index, bar.close)
self.EMA50.Update(index, bar.close)
self.ROC125.Update(index, bar.close)
self.ROC20.Update(index, bar.close)
self.PPO.Update(index, bar.close)
self.RSI14.Update(index, bar.close)
self.PPOWindow.Add(self.PPO.Current.Value)
def SCTR(self):
return self.EMA200.Current.Value*0.3 + self.EMA50.Current.Value*0.15 + self.ROC125.Current.Value*0.3 + self.ROC20.Current.Value*0.15 \
+ (self.PPOWindow[0] - self.PPOWindow[2])/(3*self.PPOWindow[2]) *0.05 + self.RSI14.Current.Value*0.05
def IsReady(self):
return self.EMA200.IsReady and self.EMA50.IsReady \
and self.ROC125.IsReady and self.ROC20.IsReady\
and self.PPO.IsReady and self.RSI14.IsReady