| Overall Statistics |
|
Total Trades 22 Average Win 1.79% Average Loss -6.00% Compounding Annual Return -100.000% Drawdown 74.700% Expectancy -0.900 Net Profit -53.780% Sharpe Ratio -0.383 Probabilistic Sharpe Ratio 18.846% Loss Rate 92% Win Rate 8% Profit-Loss Ratio 0.30 Alpha -0.827 Beta 0.863 Annual Standard Deviation 2.608 Annual Variance 6.803 Information Ratio -0.308 Tracking Error 2.599 Treynor Ratio -1.156 Total Fees $62.90 Estimated Strategy Capacity $130000000.00 Lowest Capacity Asset CL XYME7AM671S1 |
# CrudeOilWTI TrueRange
from datetime import timedelta
from collections import deque
class LogicalBrownKoala(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2022, 4, 15)
self.SetCash(100000)
future = self.AddFuture(Futures.Energies.CrudeOilWTI, Resolution.Minute)
future.SetFilter(timedelta(10), timedelta(180))
self.slow_sma = None
self.slow_sma_period = 25
self.fast_sma = None
self.fast_sma_period = 12
self.CCIPeriod = 30
self.CCIupperBound = 100
self.CCIlowerBound = -100
self.volume_sma_period = 30
self.consolidator_by_symbol = {}
def OnData(self, slice):
stop_time_start = self.Time.replace(hour=15, minute=00)
stop_time_end = self.Time.replace(hour=16, minute=30)
if self.Time > stop_time_end or self.Time < stop_time_start:
return
for chain in slice.FutureChains.Values:
contracts = chain.Contracts
if len(contracts) == 0:
continue
sorted_by_oi_contracts = sorted(contracts.Values, key=lambda k: k.OpenInterest, reverse=True)
popular_contract = sorted_by_oi_contracts[0]
if popular_contract.Symbol not in self.consolidator_by_symbol:
Consolidator = TradeBarConsolidator(timedelta(minutes=3))
self.consolidator_by_symbol[popular_contract.Symbol] = Consolidator
self.slow_sma = LinearWeightedMovingAverage(self.slow_sma_period)
self.RegisterIndicator(popular_contract.Symbol, self.slow_sma, Consolidator)
self.fast_sma = LinearWeightedMovingAverage(self.fast_sma_period)
self.RegisterIndicator(popular_contract.Symbol, self.fast_sma, Consolidator)
self.volume_sma = LinearWeightedMovingAverage(self.fast_sma_period)
self.RegisterIndicator(popular_contract.Symbol, self.volume_sma, Consolidator, Field.Volume)
self.cci = self.CCI(popular_contract.Symbol, self.CCIPeriod, MovingAverageType.Simple, Resolution.Daily)
self.RegisterIndicator(popular_contract.Symbol, self.cci, Consolidator)
self.true_range = True_Range("TrueRange", 2)
self.RegisterIndicator(popular_contract.Symbol, self.true_range, Consolidator)
self.Plot("Indicator", "TrueRange", self.true_range.Current.Value)
'''
self.Plot("Indicator", "SMA slow", self.slow_sma.Current.Value)
self.Plot("Indicator", "SMA fast", self.fast_sma.Current.Value)
self.Plot("Indicator 2", "SMA Volume", self.volume_sma.Current.Value)
self.Plot("CCI", "CCI value", self.cci.Current.Value)
'''
if self.slow_sma.Current.Value > self.fast_sma.Current.Value:
self.SetHoldings(popular_contract.Symbol, 1)
class True_Range(PythonIndicator):
def __init__(self, name, period):
self.Name = name
self.Value = None
self.period = period
self.WarmUpPeriod = period
self.Time = datetime.min
self.queue_close = deque(maxlen=period)
self.queueTime = deque(maxlen=period)
def Update(self, input):
self.queue_close.appendleft(input.Close)
self.queueTime.appendleft(input.EndTime)
self.Time = input.EndTime
count = len(self.queue_close)
if self.queue_close[0] > input.High:
TH = self.queue_close[0]
else:
TH = input.High
if self.queue_close[0] < input.Low:
TL = self.queue_close[0]
else:
TL = input.Low
self.Value = TH - TL
self.IsReady == self.queue_close.maxlen
return self.IsReady