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Strategy

Sell in May and Go Away Backtest

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Sell in May and go away is an investment strategy for stocks based on the theory that the period from November to April has significantly stronger stock market growth on average than the other months. In this backtest, we used only SPY (the SPDR S&P 500 ETF), butĀ this strategy can also be appliedĀ to other trading instruments.

Type of Positions Long
 Position Opening 
Criteria for Opening a Position: ticker(spy) and month(oct)
Order Execution Model: Close Prices
 Position Closing 
Criteria for Closing a Position: month(may)
Order Execution Model: Close Prices
 Backtest Parameters 
Initial Capital: $10,000
Capital at Risk: 100% per trade
Portfolio Max Size: 1 positions
Comm. per Trade: 0.05%  
Avg Bid-Ask Spread: 0.1%  
Period: 1/1/2026 - 12/31/2026
 Results 
Total Profit: $-127   Total Trades: 1  
Capital Growth:-1.27%   Profit Trades, % of Total:0%  
Profit Factor: [?] 0.00  Avg Trade Duration, days:21  
Payoff Ratio: [?] 0.00   Avg Profit per Trade:-1.28%  
Max Drawdown:3%   Avg Profit per Day:-0.061%  
Max Drawdown, $: 256   Avg Market Impact: [?]
Minor  
 
Restoration Factor: [?] -0.50   Overall Viability Score: [?]
3 / 10
 
Avg Annual Return: -1.27%   CAGR: [?]0%  
 Equity Graph 
 Performance 
Year S&P 500 Equity JanFeb MarAprMay JunJulAug SepOctNov Dec
2026 10.73 -1.27 -1.27
        
Performed Trades  
 Symbol Entry Date
Entry
Price, $
Exit Date
Exit
Price, $
Shares Profit, $  Exit On
Stop
Loss, $
Take
Profit, $
 MI [?]
 SPY 10/01/2026 763.99 10/30/2026 755.72 13 -127.21  Period End  Minor 
1 trades
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Backtesting Results Disclaimer
Past hypothetical backtest results are neither an indicator nor a guarantee of future returns. Actual results may vary from the analysis. Hypothetical performance results have many inherent limitations and cannot fully account for market factors such as bid-ask spread, slippage, and commission costs. There are numerous other factors related to the markets, which cannot be fully accounted for in the backtesting algorithm, but all of which can adversely affect actual trading results.



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