| Strategy |
Stocks-Bonds Seasonal Rotation Backtest |
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This strategy modifies the "Sell in May and go away" strategy. The idea is to move to bonds from May to October and return to the stock market from November to April. In this backtest, we used only SPY (the SPDR S&P 500 ETF) and TLT (the iShares 20+ Year Treasury Bond ETF), but this strategy can also be applied to other trading instruments. |
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| Type of Positions |
Long |
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| Criteria for Opening a Position: |
(ticker(spy) and month(oct)) or (ticker(tlt) and month(may))
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| Order Execution Model: |
Close Prices
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| Criteria for Closing a Position: |
(ticker(spy) and month(may)) or (ticker(tlt) and month(oct))
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| Order Execution Model: |
Close Prices
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| Initial Capital: |
$10,000 |
| Capital at Risk: |
100%
per trade
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| Portfolio Max Size: |
1 positions |
| Comm. per Trade: |
0.05%
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| Avg Bid-Ask Spread: |
0.1% |
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| Period: |
1/1/2026 - 12/31/2026 |
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| Total Profit: |
$-879 |
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Total Trades: |
2 |
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| Capital Growth: | -8.79% |
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Profit Trades, % of Total: | 0% |
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| Profit Factor: [?] |
0.00 | |
Avg Trade Duration, days: | 63 |
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| Payoff Ratio: [?] |
0.00 |
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Avg Profit per Trade: | -4.45% |
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| Max Drawdown: | 11% |
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Avg Profit per Day: | -0.071% |
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| Max Drawdown, $: |
1,123 |
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Avg Market Impact: [?] |
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| Restoration Factor: [?] |
-0.78 |
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Overall Viability Score: [?] |
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| Avg Annual Return: |
-8.79% |
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CAGR: [?] | 0% |
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| Year |
S&P 500 |
Equity |
Jan | Feb |
Mar | Apr | May |
Jun | Jul | Aug |
Sep | Oct | Nov |
Dec |
| 2026 |
10.73 |
-8.79 |
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0.18
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1.16
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-4.46
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0.73
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-5.37
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-1.17
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| Symbol |
Entry Date |
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Exit Date |
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Shares |
Profit, $ |
Exit On |
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MI
[?] |
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10/01/2026 |
763.99 |
10/30/2026 |
755.72 |
12 |
-117.43 |
Period End |
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05/01/2026 |
83.95 |
10/01/2026 |
77.71 |
119 |
-761.43 |
Close Signal |
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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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