# 中村超硬 (6166.T) — per-stock model accuracy

> Model predictability decomposition: measures how accurately the ml-factor-lgbm-9f-jp-growth model family predicts this stock's returns within the jp-listed universe. High hit_rate_long does NOT mean 'good stock to buy' -- it means 'the model historically predicted this stock well when selecting it LONG'. This is a property of model-stock fit, not intrinsic stock quality.

- **Name**: 中村超硬
- **Sector**: 機械
- **Universe**: jp-listed
- **Decomposes**: `ml-factor-lgbm-9f-jp-growth` (strategy verdict: marginal) — https://qbuntu.ai/strategies/ml-factor-lgbm-9f-jp-growth
- **Computed asof**: 2026-10-01T02:33:09
- **HTML**: https://qbuntu.ai/stocks/6166.T
- **JSON**: https://qbuntu.ai/v1/stocks/6166.T
- **License**: CC-BY-4.0

## Accuracy (median across grid)

Median LONG hit rate is 0.4426 — below a coin flip.

| metric | median | p25 | p75 | n |
|---|---:|---:|---:|---:|
| hit_rate_long | 0.4426 | 0.3414 | 0.5333 | 12 |
| hit_rate_short | 0.4902 | 0.4471 | 0.5797 | 12 |
| avg_return_long_bps | -69.7 | -143.9 | -22.8 | 12 |
| avg_return_short_bps | 228.7 | 60.9 | 307.4 | 12 |
| selection_rate_long | 0.0085 | 0.0062 | 0.0116 | 12 |
| selection_rate_short | 0.0125 | 0.0120 | 0.0143 | 12 |

Hit rate ≈ 0.5 means the model's picks on this stock were near coin-flip. Returns in bps/trade. Metrics with n = 0 are omitted; n < 5 is a thin sample.

## PnL contribution

- long: -30.5
- short: 102.6
- total: 72.1
- appearances: LONG 4018 / SHORT 5808 of 437760

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Research, not investment advice. These metrics describe model–stock fit, not the stock's merit.
Cite as: qbuntu (2026). 6166.T per-stock accuracy. https://qbuntu.ai/stocks/6166.T