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NeuPortal Quant Lab

أبحاث حول وكلاء الذكاء الاصطناعي، والاختبار الرجعي وتدقيق توقعات السوق، وبنية المنصة.

مزالق النماذج · 18

  1. مزالق النماذج

    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.

    قراءة في 11 دقيقة9 أقسام

  2. مزالق النماذج

    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.

    قراءة في 7 دقيقة7 أقسام

  3. مزالق النماذج

    Why AI Models Break When Conditions Change, and How to Notice Early

    Regime shift is the most common way machine learning fails in production, and backtests average it away. A worked example with real numbers from our own board, and four habits that catch it before the results do.

    قراءة في 5 دقيقة6 أقسام

  4. مزالق النماذج

    Survivorship Bias: Why the Data You Can See Is Already Filtered

    Survivorship bias is the error of studying only the winners because the losers have quietly disappeared from the data. Here is how it distorts financial results and how to guard against it.

    قراءة في 4 دقيقة5 أقسام

  5. مزالق النماذج

    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.

    قراءة في 4 دقيقة5 أقسام

  6. مزالق النماذج

    Overfitting: Why a Great Backtest Can Still Lose in the Real World

    A model that looks spectacular on historical data is the easiest thing to build and the hardest to trust. What overfitting is, why it fools you, and the only test that cannot be gamed.

    قراءة في 4 دقيقة5 أقسام

  7. مزالق النماذج

    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.

    قراءة في 7 دقيقة7 أقسام

  8. مزالق النماذج

    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.

    قراءة في 8 دقيقة8 أقسام

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