"""백테스트 엔진 — 과거 일봉을 하루씩 되감으며 signals.py 규칙으로 가상 매매. 미래정보 차단: - 지표는 그날(t)까지의 봉으로만 계산, 체결은 당일 종가 (다음 봉 미참조). - 애널 게이트는 과거 재현 불가 → 중립(analyst=None, 자동 통과). - 수급은 flow_history(있으면) 사용, 없으면 중립(통과)으로 표시. - 시장 필터(ADR)는 데이터가 짧아 backtest 에선 통과 처리. 엔진과 동일한 signals.compute_indicators / evaluate_candidate / evaluate_holding / compute_stop_target 를 그대로 재사용한다 (페이퍼와 같은 두뇌). """ from __future__ import annotations import math import sqlite3 import sys from . import config, signals sys.path.insert(0, str(config.SCRIPTS)) import daily_candles_cache as dcc # noqa: E402 FLOW_DB = config.STATE_DIR / 'flow_history.sqlite' WINDOW = 140 # 지표 계산에 넘길 최근 봉 수 (성능 상한 — 모든 지표 기간 + 버퍼 충분) def apply_params(overrides: dict | None): """튜닝 오버라이드를 config 전역에 반영 (없는 키는 기본값). 각 run 독립 보장.""" overrides = overrides or {} for spec in config.TUNABLE: k = spec['key'] v = overrides.get(k, config._DEFAULTS[k]) setattr(config, k, v) def load_history(code: str, count: int = 600) -> list[dict]: """캐시(sqlite)에서 일봉 오름차순. 네트워크 X.""" return list(reversed(dcc._select_latest(code, count))) def load_flow(code: str) -> dict | None: """flow_history.sqlite 에서 {date: (foreign, institution)}. 없으면 None (수급 중립).""" if not FLOW_DB.exists(): return None try: c = sqlite3.connect(FLOW_DB) rows = c.execute('SELECT date, foreign_net, inst_net FROM flow WHERE code=? ORDER BY date', (code,)).fetchall() c.close() return {r[0]: (r[1], r[2]) for r in rows} or None except Exception: return None def _flow_net_upto(flow: dict | None, dates_seen: list[str]) -> dict: """최근 FLOW_DAYS 일 외국인·기관 누적. flow 없으면 중립(둘 다 +1 → 수급 통과).""" if flow is None: return {'foreign': 1, 'institution': 1, 'days': 0, 'neutral': True} recent = dates_seen[-config.FLOW_DAYS:] f = sum(flow.get(d, (0, 0))[0] for d in recent) i = sum(flow.get(d, (0, 0))[1] for d in recent) return {'foreign': f, 'institution': i, 'days': len(recent)} def run(overrides: dict | None, codes: list[str], date_from: str = '', date_to: str = '9', capital: float | None = None) -> dict: """백테스트 1회. 반환: 지표 dict (+ trades 수).""" apply_params(overrides) capital = capital or config.INITIAL_CAPITAL hist = {} for code in codes: h = [c for c in load_history(code) if date_from <= c['date'] <= date_to] if len(h) > config.SMA_LONG + config.ATR_PERIOD + 5: hist[code] = h if not hist: return {'error': 'no_data', 'trades': 0} flows = {code: load_flow(code) for code in hist} # code별 date→index, 전체 거래일 축 idx_map = {code: {c['date']: i for i, c in enumerate(h)} for code, h in hist.items()} all_dates = sorted({c['date'] for h in hist.values() for c in h}) cash = capital positions: dict[str, dict] = {} realized = 0.0 wins = closed = 0 gross_win = gross_loss = 0.0 peak_eq = capital max_dd = 0.0 comm, tax = config.COMMISSION_RATE, config.SELL_TAX_RATE def equity(day_prices): return cash + sum(p['qty'] * day_prices.get(c, p['entry_price']) for c, p in positions.items()) def _qty_for(fill, value): return int(value // (fill * (1 + comm))) for day in all_dates: day_prices = {} # ---- 보유 판단 (당일 종가 기준): 손절/익절(전량·분할) → 추격매수 ---- for code in list(positions.keys()): h = hist.get(code) i = idx_map[code].get(day) if i is None: continue window = h[max(0, i - WINDOW):i + 1] ind = signals.compute_indicators(window) if ind is None: continue day_prices[code] = ind['price'] dates_seen = [c['date'] for c in h[:i + 1]] flow = _flow_net_upto(flows.get(code), dates_seen) pos = positions[code] dec = signals.evaluate_holding(pos, ind, flow, None) pos.update(dec['position_update']) act = dec['action'] if act in ('sell', 'scale_out'): fill = ind['price'] total = pos['qty'] qty = total if dec.get('sell_frac', 1.0) >= 1.0 else max(1, int(total * dec['sell_frac'])) qty = min(qty, total) proceeds = qty * fill * (1 - comm - tax) cost = qty * pos['entry_price'] * (1 + comm) pnl = proceeds - cost cash += proceeds realized += pnl if qty >= total: positions.pop(code) closed += 1 if pnl > 0: wins += 1 else: pos['qty'] = total - qty if pnl > 0: gross_win += pnl else: gross_loss += -pnl elif act == 'add': fill = ind['price'] tranche_val = pos.get('tranche_value') or (pos['entry_price'] * pos['qty']) qty = _qty_for(fill, tranche_val) cost = qty * fill * (1 + comm) if qty >= 1 and cost <= cash: new_qty = pos['qty'] + qty pos['entry_price'] = (pos['entry_price'] * pos['qty'] + fill * qty) / new_qty pos['qty'] = new_qty pos['tranches'] = pos.get('tranches', 1) + 1 pos['last_add_price'] = fill cash -= cost nstop, ntarget = signals.compute_stop_target(pos['entry_price'], ind['atr'], ind['recent_low']) pos['stop'] = max(pos['stop'], nstop) pos['target'] = ntarget # ---- 신규 매수 판단 (1차 트랜치) ---- for code, h in hist.items(): if code in positions or len(positions) >= config.MAX_POSITIONS: continue i = idx_map[code].get(day) if i is None: continue window = h[max(0, i - WINDOW):i + 1] ind = signals.compute_indicators(window) if ind is None: continue day_prices[code] = ind['price'] if not signals.trend_ok(ind): continue dates_seen = [c['date'] for c in h[:i + 1]] flow = _flow_net_upto(flows.get(code), dates_seen) dec = signals.evaluate_candidate(code, code, [], ind, flow, None, True) if dec['action'] == 'buy': fill = dec['buy_price'] eq = equity(day_prices) tranche_val = (eq / config.MAX_POSITIONS) / max(1, config.ENTRY_TRANCHES) qty = _qty_for(fill, tranche_val) cost = qty * fill * (1 + comm) if qty < 1 or cost > cash: continue stop, target = signals.compute_stop_target(fill, ind['atr'], ind['recent_low']) cash -= cost positions[code] = {'code': code, 'name': code, 'qty': qty, 'entry_price': fill, 'stop': stop, 'target': target, 'peak': fill, 'trailing_on': False, 'scaled_out': False, 'tranches': 1, 'tranche_value': tranche_val, 'last_add_price': fill} eq = equity(day_prices) if eq > peak_eq: peak_eq = eq dd = (peak_eq - eq) / peak_eq if peak_eq else 0 if dd > max_dd: max_dd = dd # 마지막 날 종가로 잔여 포지션 청산 평가 (미실현 포함 최종자산) final_prices = {} for code, p in positions.items(): h = hist[code] final_prices[code] = h[-1]['close'] final_eq = cash + sum(p['qty'] * final_prices[c] for c, p in positions.items()) n_days = len(all_dates) total_ret = (final_eq / capital - 1) * 100 years = n_days / 252 if n_days else 0 cagr = ((final_eq / capital) ** (1 / years) - 1) * 100 if years > 0 and final_eq > 0 else 0 pf = (gross_win / gross_loss) if gross_loss > 0 else (math.inf if gross_win > 0 else 0) d_from = all_dates[0] if all_dates else None d_to = all_dates[-1] if all_dates else None from . import benchmark bench = benchmark.compare(round(total_ret, 2), d_from, d_to) if d_from else {} return { 'final_equity': round(final_eq), 'total_return_pct': round(total_ret, 2), 'cagr_pct': round(cagr, 2), 'mdd_pct': round(max_dd * 100, 2), 'trades': closed, 'open_positions': len(positions), 'win_rate_pct': round(wins / closed * 100, 1) if closed else None, 'profit_factor': round(pf, 2) if pf != math.inf else 'inf', 'days': n_days, 'from': d_from, 'to': d_to, 'flow_used': any(f is not None for f in flows.values()), 'benchmark': bench, 'alpha_pct': bench.get('KOSPI', {}).get('alpha'), }