| Strategy |
Dogs of the Dow - Low Priced 5 Backtest |
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As you can guess from the name, this strategy completely replicates the '"Dogs of the Dow" strategy but selects only 5 tickers with the lowest price. That is, out of the 10 highest dividend-yielding stocks of the Dow Jones Industrial Average index, we select only the 5 lowest-priced stocks. The strategy requires re-balancing at the beginning of each calendar year. |
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| Type of Positions |
Long |
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| Criteria for Opening a Position: |
index(dow) and sortby(dvd_yield,desc,10)
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| Prioritize Stocks by [?] |
Lowest Price |
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| Order Execution Model: |
Close Prices
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| Initial Capital: |
$10,000 |
| Capital at Risk: |
20%
per trade
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| Portfolio Max Size: |
5 positions |
| Comm. per Trade: |
0.05%
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| Avg Bid-Ask Spread: |
0.1% |
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| Close position at the end of: |
Year |
| Period: |
1/1/2026 - 12/31/2026 |
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| Total Profit: |
$1,549 |
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Total Trades: |
5 |
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| Capital Growth: | 15.5% |
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Profit Trades, % of Total: | 80% |
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| Profit Factor: [?] |
3.10 | |
Avg Trade Duration, days: | 208 |
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| Payoff Ratio: [?] |
0.77 |
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Avg Profit per Trade: | 15.8% |
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| Max Drawdown: | 10% |
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Avg Profit per Day: | 0.076% |
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| Max Drawdown, $: |
1,134 |
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Avg Market Impact: [?] |
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| Restoration Factor: [?] |
1.37 |
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Overall Viability Score: [?] |
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| Avg Annual Return: |
15.5% |
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CAGR: [?] | 15.5% |
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| Year |
S&P 500 |
Equity |
Jan | Feb |
Mar | Apr | May |
Jun | Jul | Aug |
Sep | Oct | Nov |
Dec |
| 2026 |
10.73 |
15.49 |
5.70
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8.94
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-6.78
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-3.88
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1.79
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-0.98
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4.67
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4.15
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-3.57
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5.63
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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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01/02/2026 |
37.96 |
10/30/2026 |
44.73 |
52 |
347.56 |
Period End |
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01/02/2026 |
61.64 |
10/30/2026 |
38.67 |
32 |
-737.88 |
Period End |
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01/02/2026 |
67.80 |
10/30/2026 |
94.08 |
29 |
757.04 |
Period End |
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01/02/2026 |
104.30 |
10/30/2026 |
149.52 |
19 |
853.93 |
Period End |
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01/02/2026 |
137.79 |
10/30/2026 |
161.57 |
14 |
328.56 |
Period End |
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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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