Model Proof

Prove whether high scores worked.

Start with top-score outcomes versus the S&P 500 baseline, then inspect the distributions and raw archived rows behind the proof.

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Forward performance is calculated from cached daily bars, not from live API calls.

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Model Proof

2026-09-18 · 5D

twelvedata 0 checked / 500 total

Model Proof

Do high Cursor_18.25 scores perform better?

Compare top score groups against the same-day S&P 500 baseline using archived forward returns.

2026-09-18 · 5D 0 checked / 500 total 500 pending outcomes

Forward outcomes are still pending.

Choose an older snapshot or a shorter horizon to see checked model proof metrics.

Model Proof uses archived market data to evaluate research quality. It is not a trading result, prediction, or financial advice.

Avg forward return n/a

Median forward return n/a

Hit rate n/a

Avg max runup n/a

Avg drawdown n/a

Pending 500

Main score distribution

X axis shows score ranges: 50 → 75. Bar-top labels show count.

5D momentum v2 distribution

X axis shows score ranges: 0 → 35. Bar-top labels show count.

Score with momentum v2 distribution

X axis shows score ranges: 65 → 100. Bar-top labels show count.

Dollar volume distribution

X axis shows bucket midpoint: 10^8.1 → 10^10.6. Bar-top labels show count.

Risk level distribution

Medium

Elevated

Low

5D forward return distribution

No chart data yet.

Live comparison

Which chart looks strongest? · 2026-09-18 · 5D

How to read Corr, R², and n

Each scatter chart shows sample size, correlation, and explanatory power in the top-right box.

Solid line = linear trend Orange line = bucket average Top-right box = Corr / R² / n

Sample size (n) How many checked outcomes are included in the chart.

Correlation (Corr) Whether higher scores align with higher forward returns.

Explanatory power (R²) How much return variation the score linearly explains.

n (sample size)

Level	Approx.
Best	400+ (near full checked universe)
Usable	200+
Caution	<100 (Corr / R² can swing easily)

A small n can look good by chance even when Corr looks attractive.

Corr (correlation)

The model goal is higher score → higher forward return, so positive Corr is preferred.

Corr	Meaning
+0.15 ~ +0.30	Decent for noisy short-term stock returns
+0.30+	Strong; check whether it repeats across dates
~0	Little linear relationship
< 0	Direction reversed for this horizon

R² (explanatory power, shown as %)

R² will usually stay low. Do not expect 50% or 80%.

R²	Meaning
<2%	Very weak; score barely explains return
2% ~ 8%	Normal and usable for short-term finance research
8% ~ 15%	Relatively strong; worth a closer look
>15%	Uncommon; check sample size and sparse buckets

Compare across the five charts: prefer the chart with positive Corr and the highest R².