Options Buyer ML: Why One Model Fails (and the V2 Fix)

Lessons from a real rebuild of an options-buyer prediction system. No profit claims — just the architecture that fixes the chronic bugs of V1. The Core Mistake in V1 V1 asked one XGBoost model one big fuzzy question: "CE ya PE?" — directly from raw CE/PE premium data. Premium is a transformed signal (underlying move × delta × gamma × IV × theta × spread × strike distance × liquidity). The model learned noise as much as signal. Concrete evidence from the research logs: Balanced accuracy stuck at 51–61% for months — hyperparameters were never tuned ( lr=0.02, depth=3 defaults used throughout; Optuna existed but was never run). A partition bug ( iv_change_1d shift inside single-row groups) silently zeroed a whole feature for the entire history. A rollup config flag compressed 15-minute bars into 1 row/day, destroying 760× of training volume (387 sequences instead of 295K+). Live paper trading: 31.6% win rate, −₹90.3k PnL , entry confidences only 55–64%. V2 Principle: Split the Question underlying mechanics --> side, range, ETA, invalidation option chain scanner --> is the buyer contract worth paying for? XGBoost (many heads) --> thin calibrated learner on clean mechanics Rule: underlying decides side; option contract decides execution eligibility. CE/PE premium is validated against, never learned as, direction. Many Shallow Heads, Not One Deep Model Instead of one CE/PE answer, V2 trains separate narrow heads: underlying_up/down_touch_{15,30,60}m ce_1p3x / ce_1p5x / ce_2p0x and pe_1p3x / pe_1p5x / pe_2p0x (SEPARATE CE and PE) no_trade_quality This single change removes most of the CE/PE confusion V1 fought for months. The Shallow Regularized Grid (the actual fix for overfit) learning_rate = 0.015 – 0.035 n_estimators = 800 – 2000 ( early stop ) max_depth = 2 – 3 min_child_weight = 12 – 40 gamma = 0.1 – 2.0 subsample = 0.65 – 0.90 colsample_bytree = 0.55 – 0.85 reg_alpha = 0.5 – 3.0 reg_lambda = 6.0 – 20.0 scale_pos_weight = min ( neg / pos , 8.0 ) V1's intraday head ha