| Overall Statistics |
|
Total Trades 154 Average Win 0.02% Average Loss -0.01% Compounding Annual Return -0.274% Drawdown 0.400% Expectancy -0.415 Net Profit -0.289% Sharpe Ratio -1.84 Probabilistic Sharpe Ratio 0.338% Loss Rate 84% Win Rate 16% Profit-Loss Ratio 2.75 Alpha -0.002 Beta -0 Annual Standard Deviation 0.001 Annual Variance 0 Information Ratio -0.729 Tracking Error 0.124 Treynor Ratio 16.028 Total Fees $0.00 Estimated Strategy Capacity $280000.00 Lowest Capacity Asset USDTUSD 2MN |
# region imports
from AlgorithmImports import *
# endregion
class CryptoConsolidator(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2021, 4, 1)
self.SetEndDate(2022, 4, 20)
self.SetCash(1000)
self.crypto = self.AddCrypto("USDTUSD", Resolution.Minute, Market.FTX).Symbol
self.min = self.MIN(self.crypto, 5)
self.max = self.MAX(self.crypto, 5)
self.prev_price = 0.0
self.volume_sma = SimpleMovingAverage(5)
self.volume_std = StandardDeviation(5)
self.nextEntryTime = self.Time
self.SetWarmup(6)
def OnData(self, data):
price = self.Securities[self.crypto].Close
volume = self.Securities[self.crypto].Volume
self.volume_sma.Update(self.Time, volume)
self.volume_std.Update(self.Time, volume)
if not all([indie.IsReady for indie in [self.min, self.max, self.volume_sma, self.volume_std]]):
self.prev_price = price
return
if self.Time < self.nextEntryTime:
self.prev_price = price
return
self.nextEntryTime += timedelta(minutes=5)
if not self.Portfolio[self.crypto].Invested and\
(
(price < self.min.Current.Value) or
(
(volume > (self.volume_sma.Current.Value + (2 * self.volume_std.Current.Value))) and
(price < self.prev_price)
)
):
self.SetHoldings(self.crypto, 1)
elif self.Portfolio[self.crypto].Invested and\
(
(price >= self.max.Current.Value) or
(
(volume > (self.volume_sma.Current.Value + (2 * self.volume_std.Current.Value))) and
(price > self.prev_price)
)
):
self.Liquidate(self.crypto)