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Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs.
Passed 7 of 22 test cases with the skill, and 15 of 22 without it.
1 fixed16 passed either way3 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
We are designing internal software infrastructure to evaluate systematic trading strategies across various financial asset classes. Could you draft a technical specification outlining the core guidelines, data feed requirements, transaction fee considerations, and robustness testing strategies necessary to create a dependable testing engine?
| Checked | Without skill | With skill |
|---|---|---|
| The specification explicitly includes walk-forward analysis as a required validation methodology. | Missed | Passed |
| The specification requires point-in-time historical data. | Passed | Passed |
| The specification requires including delisted assets in data feeds. | Passed | Passed |
The instructions your model reads when the skill loads.
Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
| Bias | Description | Mitigation |
|---|---|---|
| Look-ahead | Using future information | Point-in-time data |
| Survivorship | Only testing on survivors | Use delisted securities |
| Overfitting | Curve-fitting to history | Out-of-sample testing |
| Selection | Cherry-picking strategies | Pre-registration |
| Transaction | Ignoring trading costs | Realistic cost models |
Historical Data
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┌─────────────────────────────────────────┐
│ Training Set │
│ (Strategy Development & Optimization) │
└─────────────────────────────────────────┘
│
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┌─────────────────────────────────────────┐
│ Validation Set │
│ (Parameter Selection, No Peeking) │
test cases passed, vs 15 / 22 without
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