| Overall Statistics |
|
Total Trades 4 Average Win 0% Average Loss 0% Compounding Annual Return 28.962% Drawdown 9.500% Expectancy 0 Net Profit 66.544% Sharpe Ratio 1.26 Probabilistic Sharpe Ratio 59.906% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.162 Beta 0.303 Annual Standard Deviation 0.167 Annual Variance 0.028 Information Ratio 0.233 Tracking Error 0.212 Treynor Ratio 0.694 Total Fees $112.34 Estimated Strategy Capacity $41000000.00 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):
self.SetHoldings('GS', 0.25)
self.SetHoldings('MS', -0.25)
self.SetHoldings('AMD', 0.25)
self.SetHoldings('XOM', -.25)
# 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