per-stock model-accuracy decomposition

1758.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	0.2338	0.1000 – 0.3531	12
Hit rate · SHORT	0.9688	0.6712 – 1	11
Avg return · LONG (bps)	-70.8	-210.8 – -29.2	12
Avg return · SHORT (bps)	136.1	101.6 – 156.6	11
Selection rate · LONG	0.0080	0.0053 – 0.0113	12
Selection rate · SHORT	0.0024	0.0007 – 0.0043	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

-3.5606

short

2.3249

total

-1.2357

appearances 64512 · LONG 539 · SHORT 198

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