feat(spot): fractal_swing live 운영 — 슬리피지·증분 sync·신호 tail 갱신

운영 백테스트(+1,873,140%)과 live/paper 체결 규칙을 맞추고, 캔들 증분 sync· tail 신호 갱신·일일 체결 상한·슬리피지를 반영한다. docs/live 차트 생성 스크립트와 .env.example·README를 갱신한다. Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-13 08:26:11 +09:00
parent 58802bdc5f
commit 2783826a03
20 changed files with 954 additions and 67 deletions
--- a/scripts/3_run_fractal_realistic_backtest.py
+++ b/scripts/3_run_fractal_realistic_backtest.py
@@ -0,0 +1,106 @@
+#!/usr/bin/env python3
+"""fractal_swing 현실적 백테스트 — 슬리피지·일일체결 상한 시나리오."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+SRC = ROOT / "src"
+if str(SRC) not in sys.path:
+    sys.path.insert(0, str(SRC))
+
+from deepcoin.config import load_settings
+from deepcoin.evaluation.causal_sim import normalize_signals_for_sim
+from deepcoin.ground_truth.pnl import simulate_gt_signals_pnl
+from deepcoin.operations.signal_pipeline import (
+    _signals_in_lookback,
+    generate_raw_signals,
+    load_ops_candles,
+)
+
+
+def _configure_logging(verbose: bool) -> None:
+    level = logging.DEBUG if verbose else logging.INFO
+    logging.basicConfig(
+        level=level,
+        format="%(asctime)s [%(levelname)s] %(message)s",
+        datefmt="%Y-%m-%d %H:%M:%S",
+    )
+
+
+def main() -> int:
+    """fractal_swing 슬리피지 시나리오 백테스트."""
+    parser = argparse.ArgumentParser(description="fractal_swing 현실적 3년 백테스트")
+    parser.add_argument("-v", "--verbose", action="store_true")
+    args = parser.parse_args()
+    _configure_logging(args.verbose)
+
+    settings = load_settings()
+    df = load_ops_candles(settings)
+    gen = generate_raw_signals(settings, df=df, use_cache=True)
+    end = gen["data_end"]
+    price = gen["last_price"]
+    scoped = _signals_in_lookback(gen["raw_signals"], end, settings.gt_sim_lookback_days)
+    normalized = normalize_signals_for_sim(scoped)
+
+    scenarios = [
+        {"label": "stage2_ideal", "slippage_rate": 0.0, "daily_max_trades": None},
+        {"label": "ops_default", "slippage_rate": settings.ops_slippage_rate, "daily_max_trades": settings.ops_daily_max_trades},
+        {"label": "slippage_0.1pct", "slippage_rate": 0.001, "daily_max_trades": settings.ops_daily_max_trades},
+        {"label": "slippage_0.1pct_no_cap", "slippage_rate": 0.001, "daily_max_trades": None},
+    ]
+
+    rows = []
+    for sc in scenarios:
+        sim = simulate_gt_signals_pnl(
+            signals=normalized,
+            initial_cash_krw=settings.gt_initial_cash_krw,
+            fee_rate=settings.gt_trading_fee_rate,
+            min_order_krw=settings.ops_min_order_krw,
+            slippage_rate=sc["slippage_rate"],
+            daily_max_trades=sc["daily_max_trades"],
+            sim_lookback_days=settings.gt_sim_lookback_days,
+            data_end=end,
+            last_mark_price=price,
+        )
+        buys = sim["buys_executed"]
+        rows.append({
+            **sc,
+            "return_pct": sim["total_return_pct"],
+            "final_equity_krw": sim["final_equity_krw"],
+            "buys_executed": buys,
+            "sells_executed": sim["sells_executed"],
+            "buys_skipped": sim["buys_skipped"],
+            "daily_buys_avg": round(buys / settings.gt_sim_lookback_days, 2),
+        })
+
+    report = {
+        "technique_id": settings.ops_technique_id,
+        "symbol": settings.symbol,
+        "sim_lookback_days": settings.gt_sim_lookback_days,
+        "initial_cash_krw": settings.gt_initial_cash_krw,
+        "signals_in_period": len(scoped),
+        "scenarios": rows,
+    }
+    out = Path("docs/spot/3_operations/fractal_realistic_backtest.json")
+    out.parent.mkdir(parents=True, exist_ok=True)
+    out.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
+
+    print("\n=== fractal_swing 현실적 백테스트 (3년) ===")
+    for row in rows:
+        print(
+            f"{row['label']}: {row['return_pct']}% "
+            f"(슬리피지 {row['slippage_rate']}, 일상한 {row['daily_max_trades']}) "
+            f"매수 {row['buys_executed']} (일 {row['daily_buys_avg']})"
+        )
+    print(f"\nJSON: {out}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())