| Overall Statistics |
|
Total Trades 1003 Average Win 0.10% Average Loss -0.14% Compounding Annual Return -4.681% Drawdown 16.400% Expectancy -0.136 Net Profit -9.167% Sharpe Ratio -0.402 Probabilistic Sharpe Ratio 0.838% Loss Rate 49% Win Rate 51% Profit-Loss Ratio 0.71 Alpha -0.017 Beta -0.085 Annual Standard Deviation 0.076 Annual Variance 0.006 Information Ratio -0.802 Tracking Error 0.239 Treynor Ratio 0.357 Total Fees $1350.72 Estimated Strategy Capacity $41000000.00 Lowest Capacity Asset GS RKEOGCOG6RFP |
# 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', 0.5)
self.SetHoldings('MS', -0.5)
#self.SetHoldings('AMD', 1)
#self.SetHoldings('XOM', 1)