qbuntuqbuntu
per-stock model-accuracy decomposition

9563.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 · LONG0.26110.22670.314312
Hit rate · SHORT0.90920.84260.929012
Avg return · LONG (bps)-269.7-311.7-133.912
Avg return · SHORT (bps)249.3223.4296.712
Selection rate · LONG0.00740.00570.010812
Selection rate · SHORT0.00580.00450.006912

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
-42.8
short
35.4
total
-7.3563

appearances 209856 · LONG 1709 · SHORT 1318

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