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BenchAlgo vs building your own Python backtest
Short answer
Write your own backtester if you need a custom engine, your own data or markets we do not cover. Use BenchAlgo if you want the data, the fills and the validation checks ready, and out of your strategy’s reach.
Side by side
| Feature | BenchAlgo | Your own Python backtest |
|---|---|---|
| Market data | CME data for ES, NQ and GC, included in the plan | You buy it, clean it, store it and handle rolls and sessions |
| Markets | ES, NQ and GC, with micro contracts | Anything you have data for |
| Engine | Fixed: one position at a time, flat by the close, 1-minute bars today | Whatever you write |
| Fills and costs | Set by the harness. A strategy cannot change them | You write them, and one optimistic assumption flatters every result |
| Lookahead | Checked on every run | You write the test, or you trust the code |
| Overfitting | Walk-forward, parameter stability and PBO in every report | You build and maintain them |
| Trial count | Kept per campaign and cannot be reset | Whatever you remember to log |
| Raw prices | Hidden. You see dollars and ticks | Yours to use |
| Live trading | Not yet | Whatever you build |
| Cost | $99 a month with credits included | Your time, your data and your compute |
When to build your own
- You trade markets or instruments we do not cover.
- You need something the fixed engine does not allow, such as several positions at once or a portfolio.
- You have your own data and want every raw price.
- You need to run the same code live today.
When to use BenchAlgo
- You want to know whether an idea survives strict checks, not to build the checks.
- You work with an AI and want every attempt recorded, tested the same way and kept out of reach of the data.
- You want a second opinion that your own code cannot influence.
The two also work together. Explore in your own notebooks, then bring an idea here once it deserves a strict test.