Overall Statistics |
Total Trades 2 Average Win 0% Average Loss 0% Compounding Annual Return -6.216% Drawdown 20.600% Expectancy 0 Net Profit -12.077% Sharpe Ratio -0.445 Probabilistic Sharpe Ratio 0.673% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.024 Beta -0.103 Annual Standard Deviation 0.09 Annual Variance 0.008 Information Ratio -0.815 Tracking Error 0.247 Treynor Ratio 0.391 Total Fees $80.04 Estimated Strategy Capacity $11000000.00 Lowest Capacity Asset MWD R735QTJ8XC9X |
# region imports from AlgorithmImports import * # endregion class EnergeticYellowGreenGiraffe(QCAlgorithm): def Initialize(self): self.SetStartDate(2020,1,1) self.SetEndDate(2021,1,1) self.SetCash(1000000) # add securities self.AddEquity("GOOG", Resolution.Daily) self.GOOG = self.Symbol("GOOG") self.AddEquity("AMZN", Resolution.Daily) self.AMZN = self.Symbol("AMZN") self.count = 0 def OnData(self, data: Slice): if self.count == 0: self.MarketOrder("GOOG", 6000) self.MarketOrder("AMZN",-8000) value = self.Portfolio.TotalPortfolioValue self.Log('Portfolio Value : ' + str(value)) self.count += 1 if value < 900000: order_ids = self.Liquidate()
# region imports from AlgorithmImports import * # endregion class EnergeticYellowGreenGiraffe(QCAlgorithm): def Initialize(self): self.SetStartDate(2020,1,1) self.SetEndDate(2021,1,1) self.SetCash(1000000) # add securities self.AddEquity("GOOG", Resolution.Daily) self.AddEquity("AMZN", Resolution.Daily) def OnData(self, data: Slice): # get starting date prices if self.Time.day == 1 and self.Time.month == 1 and self.Time.year == 2020: self.AMZN_start = self.Securities["AMZN"].Price self.GOOG_start = self.Securities["GOOG"].Price self.LimitOrder("AMZN", -8000, 1.05 * self.AMZN_start) self.LimitOrder("GOOG", 6000, 0.95 * self.GOOG_start) value = self.Portfolio.TotalPortfolioValue if value < 900000: order_ids = self.Liquidate() value = self.Portfolio.TotalPortfolioValue if value < 900000: order_ids = self.Liquidate()
# region imports from AlgorithmImports import * # endregion class MeasuredTanJackal(QCAlgorithm): def Initialize(self): self.SetStartDate(2020,1,1) self.SetEndDate(2021,1,1) self.SetCash(1000000) # add securities self.AddEquity("GOOG", Resolution.Daily) self.AddEquity("AMZN", Resolution.Daily) self.amzn_orders = -5628 self.goog_orders = round(self.amzn_orders * 3/4,0) def OnData(self, data: Slice): self.Debug(f"AMZN : {self.amzn_orders} \n GOOG : {self.goog_orders}") if self.Time.day == 1 and self.Time.year == 2020 and self.Time.month == 1: self.MarketOrder("AMZN", self.amzn_orders) self.MarketOrder("GOOG", -self.goog_orders)
# region imports from AlgorithmImports import * # endregion class EnergeticYellowGreenGiraffe(QCAlgorithm): """ 1. (5 pts) Compute the Sharpe Ratio of a buy-and-hold strategy for each of the above stocks individually for the given time period, that is, you need to compute four Sharpe Ratios separately, one for each stock. """ def Initialize(self): self.SetStartDate(2019,2,1) self.SetEndDate(2021,2,1) self.SetCash(1000000) #self.AddEquity('GS', Resolution.Daily) #self.AddEquity('MS', Resolution.Daily) #self.AddEquity('AMD', Resolution.Daily) self.AddEquity('XOM', Resolution.Daily) def OnData(self, data: Slice): #self.SetHoldings('GS', 1) #self.SetHoldings('MS', 1) #self.SetHoldings('AMD', 1) self.SetHoldings('XOM', 1)
# region imports from AlgorithmImports import * # endregion class EnergeticYellowGreenGiraffe(QCAlgorithm): def Initialize(self): self.SetStartDate(2019,2,1) self.SetEndDate(2021,2,1) self.SetCash(1000000) # just commenting and uncommenting the below to find the statistic for # the relevant ticker #self.AddEquity('GS', Resolution.Daily) self.AddEquity('MS', Resolution.Daily) #self.AddEquity('AMD', Resolution.Daily) #self.AddEquity('XOM', Resolution.Daily) self.count = 0 def OnData(self, data: Slice): if self.count == 0: #self.SetHoldings('GS', 1) self.SetHoldings('MS', 1) #self.SetHoldings('AMD', 1) #self.SetHoldings('XOM', 1) value = self.Portfolio.TotalUnrealizedProfit stop_loss = 0.07 * 1000000 self.count += 1 # with 1MM starting value, equates to losing or gaining $70,000 if (value <= -stop_loss) or (value >= stop_loss): order = self.Liquidate()
# region imports from AlgorithmImports import * # endregion class EnergeticYellowGreenGiraffe(QCAlgorithm): def Initialize(self): self.SetStartDate(2019,2,1) self.SetEndDate(2021,2,1) self.SetCash(1000000) # just commenting and uncommenting the below to find the statistic for # the relevant ticker self.AddEquity('GS', Resolution.Daily) self.AddEquity('MS', Resolution.Daily) #self.AddEquity('AMD', Resolution.Daily) #self.AddEquity('XOM', Resolution.Daily) self.count = 0 def OnData(self, data: Slice): self.SetHoldings('GS', 0.5) self.SetHoldings('MS', -0.5) #self.SetHoldings('AMD', 1) #self.SetHoldings('XOM', 1)
# region imports from AlgorithmImports import * # endregion class EnergeticYellowGreenGiraffe(QCAlgorithm): def Initialize(self): self.SetStartDate(2019,2,1) self.SetEndDate(2021,2,1) self.SetCash(1000000) # just commenting and uncommenting the below to find the statistic for # the relevant ticker self.AddEquity('GS', Resolution.Daily) self.AddEquity('MS', Resolution.Daily) self.AddEquity('AMD', Resolution.Daily) self.AddEquity('XOM', Resolution.Daily) self.count = 0 def OnData(self, data: Slice): if self.count == 0: self.SetHoldings('GS', 0.25) self.SetHoldings('MS', -0.25) self.SetHoldings('AMD', 0.25) self.SetHoldings('XOM', -.25) self.count += 1
# region imports from AlgorithmImports import * # endregion class EnergeticYellowGreenGiraffe(QCAlgorithm): def Initialize(self): self.SetStartDate(2019,2,1) self.SetEndDate(2021,2,1) self.SetCash(1000000) # just commenting and uncommenting the below to find the statistic for # the relevant ticker self.AddEquity('GS', Resolution.Daily) self.AddEquity('MS', Resolution.Daily) #self.AddEquity('AMD', Resolution.Daily) #self.AddEquity('XOM', Resolution.Daily) self.count = 0 def OnData(self, data: Slice): if self.count == 0: self.SetHoldings('GS', 0.5) self.SetHoldings('MS', -0.5) #self.SetHoldings('AMD', 1) #self.SetHoldings('XOM', 1) self.count += 1