Overall Statistics
Total Orders
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
6.719%
Drawdown
80.900%
Expectancy
0
Start Equity
100000
End Equity
401029.56
Net Profit
301.030%
Sharpe Ratio
0.233
Sortino Ratio
0.254
Probabilistic Sharpe Ratio
0.007%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0.004
Beta
1.133
Annual Standard Deviation
0.216
Annual Variance
0.047
Information Ratio
0.079
Tracking Error
0.116
Treynor Ratio
0.044
Total Fees
$6.23
Estimated Strategy Capacity
$140000000.00
Lowest Capacity Asset
QQQ RIWIV7K5Z9LX
Portfolio Turnover
0.01%
Drawdown Recovery
5443
 
#region imports
from AlgorithmImports import *
#endregion
# For a better understanding of the results : https://www.quantconnect.com/docs/v2/our-platform/backtesting/results
"""
TRADE LOGIC DESCRIPTION

This strategy trades QQQ using a simple buy-and-hold allocation rule. The model
enters a long QQQ position when the portfolio is not already invested and then
continues holding that position indefinitely. The purpose is to test whether full
exposure to QQQ can create value compared with a passive SPY benchmark. The
strategy does not use technical indicators, price momentum, volatility filters,
calendar timing rules, macro signals, or regime logic. It is purely exposure-based.
The strategy invests 100% of the portfolio in QQQ when active and does not keep
a planned cash reserve. SPY is not traded by the strategy; it is used only as the
benchmark for comparison. The benchmark is constructed by compounding the
starting portfolio value using SPY daily close-to-close returns. The model plots
the strategy equity curve and the benchmark equity curve on the same chart.


"""

class RetrospectiveYellowGreenAlligator(QCAlgorithm):

    def Initialize(self):
        
        # INITIALIZE
        self.SetStartDate(2000, 1, 1) 
        self.SetEndDate(2021, 5, 5)
        self.SetCash(100000) 
        self.spy = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.qqq = self.AddEquity("QQQ", Resolution.Daily).Symbol
        
        # SET BENCHMARK AND PREPARE COMPARATIVE PLOT
        self.SetBenchmark("SPY")
        self.lastBenchmarkValue = None
        self.BenchmarkPerformance = self.Portfolio.TotalPortfolioValue
        
    def OnData(self, data):
        
        #INVESTMENT STRATEGY
        if not self.Portfolio.Invested:
            self.SetHoldings("QQQ", 1)
            
        #CREATE A COMPARATIVE PLOT OF STRATEGY VS. BENCHMARK
        benchmark = self.Securities["SPY"].Close    
        if self.lastBenchmarkValue is not  None:
           self.BenchmarkPerformance = self.BenchmarkPerformance * (benchmark/self.lastBenchmarkValue)
        self.lastBenchmarkValue = benchmark
        
        self.Plot("Strategy vs Benchmark", "Portfolio Value", self.Portfolio.TotalPortfolioValue)
        self.Plot("Strategy vs Benchmark", "Benchmark", self.BenchmarkPerformance)