qbuntuqbuntu
per-stock model-accuracy decomposition

6335.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)

metricmedianp25 – p75n
Hit rate · LONG0.42290.37820.476912
Hit rate · SHORT0.61360.56160.671212
Avg return · LONG (bps)-10.9-41.176.312
Avg return · SHORT (bps)133.676.1190.212
Selection rate · LONG0.01950.01650.021012
Selection rate · SHORT0.02390.02050.025512

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
0.9204
short
65.3
total
66.2

appearances 185856 · LONG 3373 · SHORT 4311

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