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Backtest Linter & Lookahead Detector
A static analysis CLI tool and GitHub Action specifically designed for pandas/numpy trading code. It scans dataframes for common 'lookahead bias' leaks and missing slippage implementations before the backtest is run.
Ver en RedditDesglose de puntuación
Diferenciación
Voces de la comunidad
Citas reales de comentarios de Reddit que inspiraron esta oportunidad
- “tiny lookahead mistakes can make a strategy look like magic”
- “dangerously good at creating strategies that look genius in backtests and completely fall apart live”
- “Lookahead leaks are the silent killer. I've seen models confidently write `df['ret'].shift(-1)` in the wrong place and produce a 4 Sharpe out of nothing”
- “people backtest on a feature that looks predictive on the train slice and doesnt generalize”
- “If I did, I'd have a dashboard to verify hallucinations.”
- “help me not spend two hours fighting dataframe plumbing”
- “The biggest value for me is less 'find me alpha' and more 'help me not spend two hours fighting dataframe plumbing.'”
- “speedup is pretty massive once you stop spending most of your time wiring things together manually”
Plan de Acción
Valida esta oportunidad antes de escribir código
Próximo Paso Recomendado
Construir
Señales de demanda fuertes. Hay dolor real y disposición a pagar — empieza a construir un MVP.
Kit de Textos para Landing Page
Textos listos para pegar, basados en el lenguaje real de la comunidad de Reddit
Titular
Backtest Linter & Lookahead Detector
Subtítulo
A static analysis CLI tool and GitHub Action specifically designed for pandas/numpy trading code. It scans dataframes for common 'lookahead bias' leaks and missing slippage implementations before the backtest is run.
Para Quién Es
Para Retail algorithmic traders, quantitative researchers, and small prop shops.
Lista de Funciones
✓ Static analysis for improper `.shift(-1)` usage ✓ Detection of future-data leakage in rolling windows ✓ Automated flagging of missing transaction costs/slippage ✓ Jupyter Notebook extension integration
Prueba Social
“tiny lookahead mistakes can make a strategy look like magic”— Usuario de Reddit, r/r/algotrading
“dangerously good at creating strategies that look genius in backtests and completely fall apart live”— Usuario de Reddit, r/r/algotrading
“Lookahead leaks are the silent killer. I've seen models confidently write `df['ret'].shift(-1)` in the wrong place and produce a 4 Sharpe out of nothing”— Usuario de Reddit, r/r/algotrading
“people backtest on a feature that looks predictive on the train slice and doesnt generalize”— Usuario de Reddit, r/r/algotrading
“If I did, I'd have a dashboard to verify hallucinations.”— Usuario de Reddit, r/r/algotrading
“help me not spend two hours fighting dataframe plumbing”— Usuario de Reddit, r/r/algotrading
“The biggest value for me is less 'find me alpha' and more 'help me not spend two hours fighting dataframe plumbing.'”— Usuario de Reddit, r/r/algotrading
“speedup is pretty massive once you stop spending most of your time wiring things together manually”— Usuario de Reddit, r/r/algotrading
Dónde Validar
Comparte tu landing page en r/r/algotrading — ahí es exactamente donde se descubrieron estos puntos de dolor.