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NeuPortal Quant Lab

Ricerche su agenti IA, backtest e audit delle previsioni di mercato, e sull’architettura della piattaforma.

Insidie dei modelli · 18

  1. Insidie dei modelli

    How Often Do AI Agents Actually Finish the Job? 66% Once, 47% Every Time

    Thinkingbox runs 507 stateful business workflows past AI agents 20 times each and reports pass^20, not just pass@1. The strongest model solves 66.50% on one attempt and 47.53% on all twenty; another posts 89.35% pass@20 and 7.50% pass^20. What that gap means for agents running unattended, why the attempts are not coin flips, and how to measure your own.

    11 min di lettura9 sezioni

  2. Insidie dei modelli

    Your 30-Day Backtest Has 3,275 Windows and 110 Observations

    Slide a window across price history and you get thousands of samples. Almost none of them are independent. Here is the arithmetic, measured on real Binance history, and what it means for every confidence interval you have ever published.

    7 min di lettura7 sezioni

  3. Insidie dei modelli

    What Is Backtesting? Testing a Strategy on the Past

    Backtesting runs a strategy against historical data to see how it would have performed. Here is what it really measures, why a great backtest is so easy to fake, and what an honest one looks like.

    4 min di lettura5 sezioni

  4. Insidie dei modelli

    How to Spot Overfitted Financial Models

    Learn the key warning signs of overfitted financial models, the tests that expose them, and why transparency in any AI-driven market tool is non-negotiable.

    7 min di lettura7 sezioni

  5. Insidie dei modelli

    What Is Feature Importance in a Trading Model?

    Learn what feature importance means in AI trading models, why it matters for transparency, and how to interpret it without being a data scientist.

    8 min di lettura8 sezioni

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