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