Overall Statistics
Total Orders
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
26.053%
Drawdown
10.200%
Expectancy
0
Start Equity
100000
End Equity
125946.45
Net Profit
25.946%
Sharpe Ratio
1.191
Sortino Ratio
1.648
Probabilistic Sharpe Ratio
77.552%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
-0
Beta
0.995
Annual Standard Deviation
0.095
Annual Variance
0.009
Information Ratio
-1.937
Tracking Error
0
Treynor Ratio
0.114
Total Fees
$1.24
Estimated Strategy Capacity
$100000000.00
Lowest Capacity Asset
SPY R735QTJ8XC9X
Portfolio Turnover
0.27%
 
#region imports
from AlgorithmImports import *
#endregion
# In this part of Module 5, we address simulation.
# We will generate alternative trading histories to get a better picture of what could happen, 
# in comparison to what have happened or what should happen. 
# We will also use simulation to study factors in option pricing: the Greeks, the probability of OTM, 
# and so on. 
# We will mainly use the research environment.

# region imports
from AlgorithmImports import *
# endregion

class FormalGreenCamel(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2023, 4, 27)  # Set Start Date
        self.SetCash(100000)  # Set Strategy Cash
        self.AddEquity("SPY", Resolution.Minute)


    def OnData(self, data: Slice):
        if not self.Portfolio.Invested:
            self.SetHoldings("SPY", 1.0)