# 富士通 (6702.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**: 富士通
- **Sector**: 電機・精密
- **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/6702.T
- **JSON**: https://qbuntu.ai/v1/stocks/6702.T
- **License**: CC-BY-4.0

## Accuracy (median across grid)

Median LONG hit rate is 0.2500 — below a coin flip.

| metric | median | p25 | p75 | n |
|---|---:|---:|---:|---:|
| hit_rate_long | 0.2500 | 0 | 0.5333 | 11 |
| hit_rate_short | 0 | 0 | 0 | 5 |
| avg_return_long_bps | -88.6 | -104.3 | -22.1 | 11 |
| avg_return_short_bps | -255.2 | -255.2 | -255.2 | 5 |
| selection_rate_long | 0.0001 | 0 | 0.0001 | 12 |
| selection_rate_short | 0 | 0 | 0 | 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: -0.3427
- short: -0.1069
- total: -0.4496
- appearances: LONG 70 / SHORT 8 of 871680

---

Research, not investment advice. These metrics describe model–stock fit, not the stock's merit.
Cite as: qbuntu (2026). 6702.T per-stock accuracy. https://qbuntu.ai/stocks/6702.T