per-stock model-accuracy decomposition

6307.T

computed asof 2026-08-07T09:15:52

read this first — not a buy signal

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.

Decomposes ml-factor-lgbm-9f-jp-growth. Standalone walk-forward run of the same LightGBM 9-factor family on the jp-listed universe (~4,100 tickers); the referenced record's verdict applies to the jp-growth universe only.

Accuracy (median across grid)

metric	median	p25 – p75	n
Hit rate · LONG	0.4688	0.2723 – 0.9272	11
Hit rate · SHORT	0.1833	0 – 0.3438	10
Avg return · LONG (bps)	94.0	-44.4 – 101.2	11
Avg return · SHORT (bps)	-299.0	-428.9 – -104.7	10
Selection rate · LONG	0.0090	0.0048 – 0.0236	12
Selection rate · SHORT	0.0012	0.0003 – 0.0018	12

Hit rate ≈ 0.5 means the model's picks on this stock were near coin-flip. Returns in bps per trade (1 bps = 0.01%).

PnL contribution

long

3.0183

short

-1.1938

total

1.8245

appearances 34560 · LONG 463 · SHORT 58

Research, not investment advice. Metrics describe model–stock fit, not the stock's merit.