97 lines
3.3 KiB
Python
97 lines
3.3 KiB
Python
#!/usr/bin/env python3
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"""
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optuna_breakout_tpe_space.py — 돌파 Optuna 연속(TPE) 탐색 공간
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기존 ``_breakout_grids()`` categorical 경로는 유지. ``skip_hts`` 항상 False.
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"""
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from __future__ import annotations
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from typing import Any, Dict, List
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import optuna
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from kis_trader.backtest.optuna_tpe_common import (
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RATCHET_TPE_AXIS_KEYS,
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r1,
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r2,
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suggest_ratchet_tiers_pct,
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)
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# 매수 시간창(time_end_hm) 은 TPE 제외 — 운영 DB/골든타임 고정. 다단래칫·청산축만 탐색.
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_BREAKOUT_BASE_KEYS: List[str] = [
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"max_daily_chg",
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"vol_mult",
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"vol_window",
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"min_turnover_1m_pct",
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"prev_chg_min",
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"prev_chg_max",
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"min_price",
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"tp_pct",
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"sl_pct",
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"sl_mode",
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"atr_sl_mult",
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"trail_pct",
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"trail_arm_pct",
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"shoulder_min_high_pct",
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"shoulder_cut_pct",
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"lookback_min",
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"confirm_margin_pct",
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"body_min_pct",
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"max_hold_bars",
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]
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BREAKOUT_TPE_AXIS_KEYS: List[str] = list(_BREAKOUT_BASE_KEYS) + list(RATCHET_TPE_AXIS_KEYS)
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_SL_MODE_CHOICES = ["fixed", "atr"]
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def breakout_tpe_axis_keys() -> List[str]:
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return list(BREAKOUT_TPE_AXIS_KEYS)
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def suggest_breakout_params_tpe(trial: optuna.Trial) -> Dict[str, Any]:
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combo: Dict[str, Any] = {}
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combo["max_daily_chg"] = r1(trial.suggest_float("max_daily_chg", 20.0, 55.0, step=1.0))
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combo["vol_mult"] = r2(trial.suggest_float("vol_mult", 1.5, 4.0, step=0.1))
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combo["vol_window"] = trial.suggest_int("vol_window", 1, 15)
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combo["min_turnover_1m_pct"] = r2(
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trial.suggest_float("min_turnover_1m_pct", 0.05, 0.5, step=0.05),
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)
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combo["prev_chg_min"] = r2(trial.suggest_float("prev_chg_min", 0.2, 1.0, step=0.1))
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combo["prev_chg_max"] = r1(trial.suggest_float("prev_chg_max", 5.0, 30.0, step=0.5))
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if combo["prev_chg_min"] >= combo["prev_chg_max"]:
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raise optuna.TrialPruned("prev_chg invalid")
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combo["min_price"] = trial.suggest_int("min_price", 1000, 5000, step=500)
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combo["tp_pct"] = r2(trial.suggest_float("tp_pct", 2.0, 18.0, step=0.5))
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combo["sl_pct"] = r2(trial.suggest_float("sl_pct", 2.0, 6.0, step=0.1))
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combo["sl_mode"] = trial.suggest_categorical("sl_mode", _SL_MODE_CHOICES)
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combo["atr_sl_mult"] = r2(trial.suggest_float("atr_sl_mult", 1.5, 3.5, step=0.1))
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combo["trail_pct"] = r2(trial.suggest_float("trail_pct", 1.0, 4.0, step=0.1))
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combo["trail_arm_pct"] = r2(trial.suggest_float("trail_arm_pct", 1.0, 4.0, step=0.1))
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combo["shoulder_min_high_pct"] = r2(
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trial.suggest_float("shoulder_min_high_pct", 1.0, 6.0, step=0.1),
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)
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combo["shoulder_cut_pct"] = r2(
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trial.suggest_float("shoulder_cut_pct", 0.3, 1.5, step=0.1),
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)
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combo.update(
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suggest_ratchet_tiers_pct(
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trial,
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off_token="",
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n_max=3,
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gain_low=2.0,
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gain_high=15.0,
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gain_step=0.5,
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cut_low=0.5,
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cut_high=3.0,
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cut_step=0.1,
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),
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)
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combo["lookback_min"] = trial.suggest_int("lookback_min", 1, 10)
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combo["confirm_margin_pct"] = r2(
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trial.suggest_float("confirm_margin_pct", 0.0, 1.0, step=0.1),
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)
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combo["body_min_pct"] = r2(trial.suggest_float("body_min_pct", 0.0, 0.5, step=0.1))
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combo["max_hold_bars"] = trial.suggest_int("max_hold_bars", 0, 180, step=10)
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combo["skip_hts_scan_dupes"] = False
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return combo
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