| Overall Statistics |
|
Total Trades 492 Average Win 0.75% Average Loss -0.38% Compounding Annual Return -80.897% Drawdown 66.300% Expectancy -0.167 Net Profit -60.181% Sharpe Ratio -0.725 Probabilistic Sharpe Ratio 3.196% Loss Rate 72% Win Rate 28% Profit-Loss Ratio 1.97 Alpha -0.448 Beta 1.672 Annual Standard Deviation 0.74 Annual Variance 0.548 Information Ratio -0.72 Tracking Error 0.671 Treynor Ratio -0.321 Total Fees $0.00 Estimated Strategy Capacity $480000.00 Lowest Capacity Asset BTCUSD XJ |
from QuantConnect.Indicators import *
from AlgorithmImports import *
class BollingerMomentum(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2022, 6, 1)
self.SetCash("BTC",100)
self.ticker="BTCUSD"
self.symbol=self.AddCrypto(self.ticker, Resolution.Minute).Symbol
self.per_order_proportion=0.5
period_BB = 25
std=2
self.Bolband = self.BB(self.ticker, period_BB, std, MovingAverageType.Simple, Resolution.Hour)
self.SetRiskManagement(MaximumDrawdownPercentPerSecurity(0.01))
self.SetWarmUp(period_BB)
def OnData(self, data):
if self.IsWarmingUp != False:
return
holdings = self.Portfolio[self.ticker].Quantity
price = self.Securities[self.ticker].Close
quantity = self.CalculateOrderQuantity(self.ticker,self.per_order_proportion)
if holdings <= 0:
if price <= self.Bolband.LowerBand.Current.Value:
self.MarketOrder(self.ticker, quantity*1)
if holdings > 0:
if price >= self.Bolband.UpperBand.Current.Value:
self.LiquidateAll()
def LiquidateAll(self):
self.Liquidate()
self.Transactions.CancelOpenOrders(self.ticker)