| Overall Statistics |
|
Total Trades 50 Average Win 3.55% Average Loss -3.55% Compounding Annual Return 29.016% Drawdown 51.700% Expectancy 0.642 Net Profit 155.326% Sharpe Ratio 0.914 Probabilistic Sharpe Ratio 33.881% Loss Rate 18% Win Rate 82% Profit-Loss Ratio 1.00 Alpha 0.302 Beta -0.09 Annual Standard Deviation 0.335 Annual Variance 0.112 Information Ratio 0.875 Tracking Error 0.403 Treynor Ratio -3.412 Total Fees $595.22 |
class SiegfriedsRework(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2000, 1, 1)
self.SetEndDate(2003, 9, 4)
self.SetCash(100000)
self.UniverseSettings.Resolution = Resolution.Daily
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel(lambda time: None))
# self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel(lambda time: Expiry.EndOfMonth(time)))
self.Settings.RebalancePortfolioOnInsightChanges = False
self.Settings.RebalancePortfolioOnSecurityChanges = True
self.SetUniverseSelection(FineFundamentalUniverseSelectionModel(self.SelectCoarse, self.SelectFine))
self.spy = self.AddEquity("SPY", Resolution.Daily).Symbol
self.SetBenchmark("SPY") # NOT SURE WHAT THIS DOES
self.Schedule.On(self.DateRules.MonthStart("SPY"), self.TimeRules.AfterMarketOpen("SPY", 120), self.Rebalance)
self.num_symb_coarse = 8000
self.min_market_cap = 5
self.min_roic = 0.7
self.max_roic = 20 # max ROIC at purcahse only. if stock has roic intially below this threshold, but rises while in holdings, stock won't be liquidated
self.min_volume = 200000 # minimum trading volume
self.max_peg = 100 # max peg at purcahse only. if stock has peg intially below this threshold, but rises while in holdings, stock won't be liquidated
self.new_symbols = []
self.invested_stocks = []
self.monthly_rebalance = False
self.recently_rebalanced = False
##### Universe Selection, OnSecuritiesChanged, OnData are all called midnight
# coarse/fine universe selection runs everyday at midnight
def SelectCoarse(self, coarse):
if self.monthly_rebalance == False:
self.recently_rebalanced = False
return Universe.Unchanged # if selectcoarse returns universe.unchanged, selectfine is not called
self.recently_rebalanced = True
self.monthly_rebalance = False
filtered_coarse = [x for x in coarse if x.HasFundamentalData] # removing ETFs, ETNs
sorted_coarse = sorted(filtered_coarse, key=lambda k:k.DollarVolume, reverse=True)
min_vol_coarse = [x for x in sorted_coarse if x.DollarVolume > self.min_volume]
top_liquid_coarse = min_vol_coarse[:self.num_symb_coarse]
return [i.Symbol for i in top_liquid_coarse if i.Symbol.Value != 'PDLI']
def SelectFine(self, fine):
filtered_fine = [x for x in fine if x.CompanyReference.CountryId == "USA"
and x.AssetClassification.MorningstarSectorCode != MorningstarSectorCode.Energy
and x.AssetClassification.MorningstarSectorCode != MorningstarSectorCode.FinancialServices
and x.MarketCap/1000000 > self.min_market_cap
and x.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths > 0
and x.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/x.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths > self.min_roic
and x.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/x.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths < self.max_roic
and x.ValuationRatios.NormalizedPEGatio > 0
and x.ValuationRatios.NormalizedPEGatio < self.max_peg]
sorted_fine = sorted(filtered_fine, key=lambda x:x.ValuationRatios.NormalizedPEGatio, reverse = False)
quartile = 1 if len(sorted_fine)/4 <= 0 else int(round((len(sorted_fine)/4)))
bottom_quartile = sorted_fine[:quartile]
# self.Debug(f"filtered_fine: {[str(i.Symbol) for i in filtered_fine]}")
self.new_symbols = [i.Symbol for i in bottom_quartile]
# self.Debug(f"chosen_fine: {[str(i) for i in self.new_symbols]}")
for symbol in self.new_symbols:
if symbol not in self.invested_stocks:
self.invested_stocks.append(symbol) # add new securities to watchlist
# self.Debug(f" new symbols: {[str(i) for i in self.new_symbols]}")
# self.Debug(f"invested stocks: {[str(i) for i in self.invested_stocks]}")
return self.invested_stocks
def OnData(self, data):
if not self.recently_rebalanced:
return
insights = []
for symbol in self.invested_stocks:
security = self.Securities[symbol]
if security == self.spy:
# skip SPY
continue
if security.Fundamentals.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/security.Fundamentals.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths < self.min_roic \
or security.Fundamentals.MarketCap/1000000 < self.min_market_cap:
insights.append(Insight.Price(symbol, timedelta(days = 7560), InsightDirection.Flat))
self.invested_stocks.remove(security.Symbol) #remove security from watchlist
self.Debug(f"!!Liquidate {security.Symbol}")
else:
insights.append(Insight.Price(symbol, timedelta(days = 7560), InsightDirection.Up))
self.EmitInsights(insights)
def OnSecuritiesChanged(self, changes):
if len(self.invested_stocks) > 0:
for security in changes.AddedSecurities:
if security == self.spy:
# skip SPY
continue
if security.Fundamentals is None:
self.Debug(f"Buying {security} no fundamental data")
continue
self.Debug(f"Buying {security} @ {security.Price}," \
+ f" ROIC is {security.Fundamentals.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/security.Fundamentals.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths}," \
+ f" PEG is {security.Fundamentals.ValuationRatios.NormalizedPEGatio}," \
+ f" and PB is {security.Fundamentals.ValuationRatios.PBRatio}" \
+ f" MarketCap is {security.Fundamentals.MarketCap/1000000}" \
+ f" and Volume is {security.Fundamentals.DollarVolume/1000000}")
for security in changes.RemovedSecurities:
if security == self.spy:
# skip SPY
continue
if security.Fundamentals is None:
self.Debug(f"!!!Selling {security} no fundamental data")
continue
self.Debug(f"!!!Selling {security} @ {security.Price}," \
+ f" ROIC is {security.Fundamentals.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/security.Fundamentals.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths}," \
+ f" PEG is {security.Fundamentals.ValuationRatios.NormalizedPEGatio}," \
+ f" and PB is {security.Fundamentals.ValuationRatios.PBRatio}" \
+ f" MarketCap is {security.Fundamentals.MarketCap/1000000}" \
+ f" and Volume is {security.Fundamentals.DollarVolume/1000000}")
# this is called according to Schedule.On in Initialize
def Rebalance(self):
self.monthly_rebalance = True
# def OnEndOfDay(self):
# self.Debug(f"Invested Stocks List: {[str(symbol) for symbol in self.invested_stocks]}")
# self.Debug(f"Portfolio Invested Stocks: {[str(symbol) for symbol in self.Portfolio.Keys if self.Portfolio[symbol].Invested]}")
# self.Debug(f"Value of Stocks: {[float(self.Portfolio[symbol].Quantity * self.Portfolio[symbol].Price) for symbol in self.Portfolio.Keys if self.Portfolio[symbol].Invested]}")
# self.Debug(f"Portfolio % Invested: {(self.Portfolio.TotalPortfolioValue - self.Portfolio.Cash)/self.Portfolio.TotalPortfolioValue}")