| Overall Statistics |
|
Total Trades 279 Average Win 2.38% Average Loss -0.94% Compounding Annual Return 113.862% Drawdown 29.900% Expectancy 0.823 Net Profit 128.601% Sharpe Ratio 1.536 Probabilistic Sharpe Ratio 51.108% Loss Rate 48% Win Rate 52% Profit-Loss Ratio 2.52 Alpha 1.196 Beta -0.166 Annual Standard Deviation 0.763 Annual Variance 0.582 Information Ratio 1.325 Tracking Error 0.774 Treynor Ratio -7.055 Total Fees $437.02 Estimated Strategy Capacity $670000000.00 Lowest Capacity Asset NVDA RHM8UTD8DT2D |
from datetime import timedelta
class EMAMomentumUniverse(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2021, 1, 1)
self.SetEndDate(2022, 2, 1)
self.SetCash(100000)
self.UniverseSettings.Resolution = Resolution.Daily
self.AddUniverse(self.CoarseSelectionFunction)
self.averages = { }
def CoarseSelectionFunction(self, _input):
selected = []
universe = sorted(_input, key=lambda c: c.DollarVolume, reverse=True)
universe = [c for c in universe if c.Price > 10][:100]
for coarse in universe:
symbol = coarse.Symbol
if symbol not in self.averages:
self.averages[symbol] = SelectionData(self)
history = self.History(symbol, 1, Resolution.Daily)
self.averages[symbol].update(history)
if self.averages[symbol].is_ready():
selected.append(symbol)
self.Debug(f"Selected: [{','.join(map(str, selected[:5]))}]")
return selected[:5]
def OnSecuritiesChanged(self, changes):
for security in changes.RemovedSecurities:
self.Liquidate(security.Symbol)
for security in changes.AddedSecurities:
self.SetHoldings(security.Symbol, 0.20)
class SelectionData():
def __init__(self, algo):
self.obv = OnBalanceVolume()
self.algo = algo
def is_ready(self):
return self.obv.IsReady
def update(self, history):
for bar in history.itertuples():
self.algo.Debug(f"Bar: {bar}")
try:
tradeBar = TradeBar(bar.Index[1] - timedelta(days=1), bar.Index[0], bar.open, bar.high, bar.low, bar.close, bar.volume, timedelta(days=1))
self.obv.Update(tradeBar)
except AttributeError:
self.algo.Debug("No volume!")