| Overall Statistics |
|
Total Orders 152 Average Win 9.81% Average Loss -6.12% Compounding Annual Return 22.091% Drawdown 39.300% Expectancy 0.548 Net Profit 635.943% Sharpe Ratio 0.67 Sortino Ratio 0.77 Probabilistic Sharpe Ratio 10.910% Loss Rate 41% Win Rate 59% Profit-Loss Ratio 1.60 Alpha 0.086 Beta 1.071 Annual Standard Deviation 0.248 Annual Variance 0.062 Information Ratio 0.47 Tracking Error 0.194 Treynor Ratio 0.155 Total Fees $243.98 Estimated Strategy Capacity $22000000.00 Lowest Capacity Asset CAT R735QTJ8XC9X Portfolio Turnover 2.75% |
from AlgorithmImports import *
class GrowthStocksAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2014, 1, 1) # Set Start Date
self.SetEndDate(2024, 1, 1) # Set End Date
self.SetCash(10000) # Set Strategy Cash
self.UniverseSettings.Resolution = Resolution.Daily
self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
self.Schedule.On(self.DateRules.MonthStart(), self.TimeRules.At(10, 0), self.RebalancePortfolio)
self.changes = [] # To track added securities
def CoarseSelectionFunction(self, coarse):
filtered_coarse = [x for x in coarse if x.DollarVolume > 1e6 and x.Price > 5]
sorted_by_liquidity = sorted(filtered_coarse, key=lambda x: x.DollarVolume, reverse=True)
selected_symbols = [x.Symbol for x in sorted_by_liquidity if x.Price * x.DollarVolume / x.Price > 2e9]
return selected_symbols[:100]
def FineSelectionFunction(self, fine):
filtered_fine = [x for x in fine if x.OperationRatios.RevenueGrowth.OneYear > 0.0
and x.OperationRatios.NetIncomeGrowth.OneYear > 0.0
and x.EarningReports.BasicEPS.TwelveMonths > 0
and (x.ValuationRatios.PEGRatio > 0 and x.ValuationRatios.PEGRatio < 1.5)
and x.FinancialStatements.BalanceSheet.TotalEquity.Value > 0]
sorted_by_growth = sorted(filtered_fine, key=lambda x: x.OperationRatios.RevenueGrowth.OneYear, reverse=True)
return [x.Symbol for x in sorted_by_growth[:10]]
def RebalancePortfolio(self):
if self.changes is None or len(self.changes) == 0:
return
weight_per_security = 1.0 / len(self.changes)
for security in self.Securities.Values:
if security.Symbol in self.changes and not security.Invested:
self.SetHoldings(security.Symbol, weight_per_security)
elif security.Invested and security.Symbol not in self.changes:
self.Liquidate(security.Symbol)
self.changes = [] # Reset the changes after rebalancing
def OnSecuritiesChanged(self, changes):
self.changes = [x.Symbol for x in changes.AddedSecurities]