Brain Proof — bpleone / trade

Q1. Are predictions being captured?

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Q2. Are outcomes being resolved?

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Q3. Is the model actually learning?

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Q4. Is accuracy real or cached?

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Q5. Are weights converging?

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Q6. Are real prices feeding it?

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🎯 Worker — held-out test results (real signal vs noise)

The worker bootstrap trains on 80% of historical data and tests on the remaining 20% the model NEVER saw. Two splits: random shuffle (stationary upper bound) and walk-forward (honest "trained on past, predicts future" test).

Random 80/20 split — stationary estimate

Test set size

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Accuracy

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Brier Skill Score

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vs constant 0.5 baseline

p-value vs random

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Walk-forward split — honest trading test

Test set size

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Accuracy

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Brier Skill Score

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vs constant 0.5 baseline

p-value vs random

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BSS reading guide: >+0.05 = real edge · 0 to +0.05 = weak signal · ≤0 = below random.
p <0.05 = statistically significant. Walk-forward is the truth-test. If random says REAL SIGNAL but walk-forward says BELOW BASELINE, the model is overfitting / leaking future info.

📜 Weight Ledger — proves weights are changing over time

Each row is a SHA-style hash of the model's weight vector at that moment. If two hashes are different, the brain trained between them. If they're all identical, the brain isn't learning — flag a bug.

Last 20 page-loads. New row added every time you visit this page.

⚗ Live Verification — inject a test prediction

Click below to inject a known prediction (AAPL LONG, prob=0.85) into the journal. Then watch /brain-debug tick — within 30s the new entry shows up. After the short-horizon (24h) elapses it resolves automatically; OR click "Force resolve" to immediately simulate the resolution against current AAPL price.

🧮 Live Accuracy — recomputed from raw journal

Recomputes from bpleone_pred_journal_v1 directly. If this disagrees with the number shown on brain-truth.html, there's a stale cache somewhere — flag it.

Total resolved

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Correct (recomputed)

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Accuracy (recomputed)

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vs baseline 50%

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📡 Recent Activity Stream — last 20 events

Live feed showing the brain capturing predictions and resolving them. If this freezes, the brain isn't ticking.

⚠ What this page does NOT prove

This page proves the mechanics work. It does NOT prove the brain is making GOOD predictions — only that it's capturing, resolving, and training. Whether the predictions actually beat random is a separate question (see /brier-skill and /sharpe-ratio).

It also does not prove the input features are correct — only that whatever-was-captured trains the model. If you suspect bad features, run /self-test which checks the FeatureExtractor's output shape and bounds.

For a paper-trading audit (did open/stop/target prices match real moves?), run /daily-replay for any past day.