per-stock model-accuracy decomposition

2705.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	0.4583	0.3646 – 0.5746	12
Hit rate · SHORT	1	1 – 1	1
Avg return · LONG (bps)	16.6	-28.5 – 49.0	12
Avg return · SHORT (bps)	132.9	132.9 – 132.9	1
Selection rate · LONG	0.0004	0.0002 – 0.0005	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 per trade (1 bps = 0.01%).

PnL contribution

long

0.0678

short

0.0266

total

0.0943

appearances 405504 · LONG 149 · SHORT 2

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