Overall Statistics |
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -2.436 Tracking Error 0.13 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
class PensiveBlackViper(QCAlgorithm): def Initialize(self): self.SetStartDate(2021, 1, 1) self.SetEndDate(2021, 2, 10) self.SetCash(100000) # grabs the minute data for securities self.UniverseSettings.Reloution = Resolution.Minute # grabs extended market data self.UniverseSettings.ExtendedMarketHours = True # Adds the universe of stocks self.AddUniverse(self.CoarseSelectionFilter) def CoarseSelectionFilter(self, coarse): # sort by price highest to lowest # c.DollarVolume <-- looks at coarse object dollar volume and sorts it highest to lowest sortedByDollarVolume = sorted(coarse, key=lambda c: c.DollarVolume, reverse=True) # saves ~8000 stocks currently trading self.coarse = coarse return Universe.Unchanged # selects symbol if price is more than $15 symbols_by_price = [c.Symbol for c in sortedByDollarVolume if c.Price > 15] # returns the 8 most liquid symbols from the filteredByPrice list self.filteredByPrice = symbols_by_price[:10] fml = self.filteredByPrice self.Debug(f"CoarseSelectionFilter({self.Time}):: {fml}") return self.filteredByPrice def OnSecuritiesChanged(self, changes): # saves securities changed as self.changes self.changes = changes # log the changes that were made self.Log(f"OnSecuritiesChanged({self.Time}):: {changes}")