| Overall Statistics |
|
Total Trades 157 Average Win 3.07% Average Loss -0.77% Compounding Annual Return 75.278% Drawdown 19.500% Expectancy 0.625 Net Profit 57.131% Sharpe Ratio 2.075 Probabilistic Sharpe Ratio 77.199% Loss Rate 68% Win Rate 32% Profit-Loss Ratio 4.01 Alpha 0.414 Beta 0.348 Annual Standard Deviation 0.233 Annual Variance 0.054 Information Ratio 1.189 Tracking Error 0.24 Treynor Ratio 1.387 Total Fees $0.00 Estimated Strategy Capacity $170000.00 Lowest Capacity Asset SOLUSDC 18N |
class RetrospectiveFluorescentYellowElephant(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2021, 1, 1)
#self.SetEndDate(2021,8,1)
self.SetCash('USDC',100000)
self.tickers = ["BTCUSDC", "ETHUSDC", "SOLUSDC", "DOGEUSDC", "ADAUSDC"]
self.symbols = [self.AddCrypto(ticker, Resolution.Minute, Market.Binance).Symbol for ticker in self.tickers]
self.fast = {}
self.slow = {}
for symbol in self.symbols:
self.fast[symbol] = self.SMA(symbol, 20, Resolution.Hour)
self.slow[symbol] = self.SMA(symbol, 200, Resolution.Hour)
self.SetWarmUp(200, Resolution.Hour)
self.SetTimeZone("Europe/London")
def OnData(self, data):
if self.IsWarmingUp: return
#for symbol in self.symbols:
# holdings = self.Portfolio[symbol].Quantity
#self.Plot("holdings", symbol, holdings)
for symbol in self.symbols:
if not self.fast[symbol].IsReady: continue
if not self.slow[symbol].IsReady: continue
fast = self.fast[symbol].Current.Value
slow = self.slow[symbol].Current.Value
#self.Plot(symbol, "fast", fast)
#self.Plot(symbol, "slow", slow)
if fast > slow and self.Portfolio[symbol].Quantity <= 0:
self.SetHoldings(symbol, 0.8/len(self.symbols))
elif fast < slow:
self.Liquidate(symbol)