| Overall Statistics |
|
Total Trades 1229 Average Win 0.02% Average Loss -0.02% Compounding Annual Return -2.751% Drawdown 7.800% Expectancy -0.363 Net Profit -2.766% Sharpe Ratio -0.575 Probabilistic Sharpe Ratio 4.867% Loss Rate 74% Win Rate 26% Profit-Loss Ratio 1.49 Alpha 0.001 Beta -0.107 Annual Standard Deviation 0.038 Annual Variance 0.001 Information Ratio -0.688 Tracking Error 0.337 Treynor Ratio 0.204 Total Fees $1229.42 |
# https://quantpedia.com/Screener/Details/25
from System.Drawing import Color
from Alphas.EmaCrossAlphaModel import EmaCrossAlphaModel
class SmallCapInvestmentAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 1, 8)
self.SetEndDate(2021, 1, 10)
self.SetCash(100000)
self.lastMonth = -1
self.emaLongestWindow = 200
self.UniverseSettings.MinimumTimeInUniverse = self.emaLongestWindow
self.SetWarmUp(self.emaLongestWindow)
self.coarseCount = 100
self.fineCount = 10
self.indicators = {}
self.UniverseSettings.Resolution = Resolution.Hour
self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
def CoarseSelectionFunction(self, coarse):
if self.lastMonth == self.Time.month:
return Universe.Unchanged
self.lastMonth = self.Time.month
sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
self.symbols = [ x.Symbol for x in sortedByDollarVolume[:self.coarseCount] ]
return self.symbols
def FineSelectionFunction(self, fine):
sortedByPeRatio = sorted(fine, key=lambda x: x.ValuationRatios.PERatio, reverse=True)
self.symbols = [ x.Symbol for x in sortedByPeRatio[:self.fineCount] ]
return self.symbols
def OnData(self, data):
for symbol in self.symbols:
if not data.ContainsKey(symbol):
continue
if data[symbol] is None:
continue
self.indicators[symbol].update_value(self.Time, data[symbol].Price)
if self.IsWarmingUp: continue
sym_price = data[symbol].Price
longestEMA = self.indicators[symbol].get_longestEMA()
if longestEMA != 0.0:
if longestEMA > sym_price:
self.SetHoldings(symbol, -0.01)
else:
self.Liquidate(symbol)
def OnSecuritiesChanged(self, changes):
for security in changes.AddedSecurities:
symbol = security.Symbol
self.indicators[symbol] = SymbolData(symbol, self, self.emaLongestWindow)
for security in changes.RemovedSecurities:
symbol = security.Symbol
if self.Portfolio[symbol].Invested:
self.Liquidate(symbol, 'Removed from Universe')
# clean up
del self.indicators[security.Symbol]
class SymbolData(object):
def __init__(self, symbol, context, window):
self.symbol = symbol
self.window = window
self.indicator = context.EMA(symbol, self.window)
self.longestEMA = 0.0
def update_bar(self, bar):
self.indicator.Update(bar)
def update_value(self, time, value):
self.indicator.Update(time, value)
def get_longestEMA(self):
return self.indicator.Current.Value