Files
kis_bot/kis_trader/backtest/breakout_portfolio_backtest.py
Hwang 78edb75e01 feat: Add new files and enhance backtesting functionality
Changes:
- Introduced new files for strategy definitions and study names.
- Enhanced `backtest_web.py` with functions to handle integer display prices and trade data formatting.
- Updated backtesting logic to incorporate end-of-day (EOD) parameters for breakout and momentum strategies.
- Added EOD configuration options in the database and parameter search files.

Impact:
- These changes improve the modularity and usability of the backtesting framework, allowing for better integration of EOD strategies and clearer trade data presentation.
2026-07-06 19:11:34 +09:00

414 lines
16 KiB
Python

#!/usr/bin/env python3
"""
돌파매매 시각순 포트폴리오 백테스트 — tail/scalping 포트폴리오와 동일 Phase0/1/2 구조.
"""
from __future__ import annotations
from typing import Any, Dict, List, Optional, Tuple
from kis_trader.backtest.backtest_portfolio_common import (
min_invest_ratio_of_slot,
portfolio_exposure_krw,
target_qty_and_cost,
)
from kis_trader.engine.scalping_engine import (
_t2dt,
_to_bool,
check_sell_signal_backtest_bar,
)
from kis_trader.share.stock_share import share_denom_for_code
from kis_trader.engine.indicator_cache import (
attach_indicator_caches_to_params,
get_indicator_cache_from_params,
)
from kis_trader.engine.whipsaw_filter import inject_whipsaw_ticks_into_params
from kis_trader.backtest.trigger_snapshot_loader import inject_trigger_snapshots_into_params
from kis_trader.strategies.breakout import (
_bt_slot_key,
breakout_entry_mode,
breakout_invest_amount_krw,
breakout_scan_buy_at_bar,
check_sell_signal_breakout_live,
normalize_breakout_max_loss_krw,
)
from kis_trader.strategies.base import is_strategy_eod_bar
from kis_trader.engine.tail_engine import compute_atr_series
def _entry_atr_at(ctx: Dict[str, Any], idx: int) -> float:
"""ctx 사전계산 ATR 시리즈에서 진입 봉(idx) 변동성 조회. 없으면 0.0(=고정손절 폴백)."""
arr = ctx.get("atr_arr")
if arr is not None and 0 <= idx < len(arr):
v = arr[idx]
if v is not None:
return float(v)
return 0.0
def _buy_priority_key(
code: str,
uni_codes: Optional[List[str]],
) -> Tuple[int, str]:
"""유니버스 편입 순서(HTS/DB insert 순) = 실매 매수 우선순위. None=필터없음."""
if uni_codes is None:
return (0, code)
try:
return (uni_codes.index(code), code)
except ValueError:
return (999999, code)
def _universe_codes_at(
t: str,
slot_key: str,
universe_timeline: Optional[Any],
universe_by_slot: Optional[Dict[str, List[str]]],
) -> Optional[List[str]]:
"""그 시각(봉 마감초) 유효 유니버스 코드 리스트.
- ``universe_timeline`` (초단위, 실매 get_universe_at 정합) 우선 — 봉 마감(HH:MM:59)
직전 최신 스냅샷. strict lag(1분 지연) 없이 실매와 동일 시점 조회.
- 없으면 1분 슬롯(``universe_by_slot``) 폴백. 둘 다 없으면 None(전종목·필터없음).
"""
if universe_timeline is not None:
return universe_timeline.codes_at(str(t)[:12] + "59")
if universe_by_slot is not None:
return universe_by_slot.get(slot_key, [])
return None
def _max_stocks_from_params(params: Dict[str, Any]) -> int:
for key in ("max_stocks", "breakout_max_stocks", "short_max_stocks"):
v = params.get(key)
if v not in (None, "", 0):
return max(1, int(v))
try:
from kis_trader.utils.env import get_env_int
n = get_env_int("BREAKOUT_MAX_STOCKS", 0) or get_env_int("MAX_STOCKS", 3)
return max(1, int(n))
except Exception:
return 3
def _total_budget_from_params(params: Dict[str, Any]) -> float:
for key in ("total_budget_krw", "breakout_total_budget_krw", "short_total_budget_krw"):
v = params.get(key)
if v not in (None, ""):
try:
return float(v)
except (TypeError, ValueError):
pass
try:
from kis_trader.utils.env import get_env_int
cap = get_env_int("BREAKOUT_TOTAL_BUDGET_KRW", 0)
if cap > 0:
return float(cap)
except Exception:
pass
return 0.0
def _resolve_breakout_invest_cap(params: Dict[str, Any]) -> float:
slot_money = float(params.get("slot_money", 2_000_000))
sl_pct = abs(float(params.get("stop_loss_pct", params.get("sl_pct", -0.02))))
max_loss_krw = normalize_breakout_max_loss_krw(params.get("max_loss_krw", 200_000))
return breakout_invest_amount_krw(max_loss_krw, sl_pct * 100.0, slot_money)
def run_breakout_backtest_portfolio(
codes_candles: Dict[str, List[Dict]],
params: Dict[str, Any],
universe_by_slot: Optional[Dict[str, List[str]]] = None,
ticks_by_code: Optional[Dict[str, Dict[str, List[Dict]]]] = None,
orderbook_by_code: Optional[Dict[str, Dict[str, List[Any]]]] = None,
program_by_code: Optional[Dict[str, Dict[str, List[Any]]]] = None,
) -> List[Dict]:
"""
시각순 포트폴리오 돌파 백테스트.
- 매수: ``check_buy_signal_breakout_live`` → 다음 봉 시가 예약
- 매도: ``check_sell_signal_breakout_live`` via ``check_sell_signal_backtest_bar``
"""
lookback_min = int(params.get("lookback_min", 1))
vol_window = int(params.get("vol_window", 7))
need_n = max(lookback_min, vol_window) + 2
_mode = breakout_entry_mode(params)
min_bars = need_n + (0 if _mode in ("intrabar", "b", "live_b", "hts") else 1)
cooldown_min = float(params.get("cooldown_min", 30))
max_daily = int(params.get("max_daily", 1))
max_stocks = _max_stocks_from_params(params)
slot_money = float(params.get("slot_money", 2_000_000))
total_budget = _total_budget_from_params(params)
if total_budget <= 0:
total_budget = float(max_stocks * slot_money)
min_invest_ratio = min_invest_ratio_of_slot(params, strategy="BREAKOUT")
invest_cap = _resolve_breakout_invest_cap(params)
time_start_hm = int(params.get("time_start_hm", 900))
time_end_hm = int(params.get("time_end_hm", 1030))
# [ATR 동적 손절] sl_mode='atr' 일 때만 종목별 ATR(RMA) 시리즈를 1회 사전계산해 ctx 에 캐시.
# fixed(기본)면 계산 자체를 건너뛰어 기존 경로와 동일한 비용/동작 유지.
_sl_mode_atr = str(params.get("sl_mode", "fixed") or "fixed").strip().lower() == "atr"
_atr_period = int(params.get("atr_period", 14) or 14)
buy_params = dict(params)
buy_params["time_start_hm"] = time_start_hm
buy_params["time_end_hm"] = time_end_hm
attach_indicator_caches_to_params(buy_params, codes_candles)
skipped_micro_buys = 0
ctx_by_code: Dict[str, Dict[str, Any]] = {}
all_times_set = set()
for code, raw_rows in codes_candles.items():
if len(raw_rows) < min_bars:
continue
candles = [dict(r) for r in raw_rows]
# [성능] 봉별 '당일 시가' 사전계산(O(n) 1회). 매수스캔(_eval 이격과열 필터)에서
# 매번 처음부터 당일시가를 정주행 스캔하던 비용을 제거하기 위해 주입한다.
day_open_arr: List[float] = [0.0] * len(candles)
_cur_day = None
_cur_open = 0.0
_first_open = float(candles[0].get("open") or 0) if candles else 0.0
for _idx, _c in enumerate(candles):
_d = str(_c.get("candle_time") or "")[:8]
if _d != _cur_day:
_cur_day = _d
_cur_open = float(_c.get("open") or 0)
day_open_arr[_idx] = _cur_open if _cur_open > 0 else _first_open
# ATR 시리즈(진입 봉 변동성) — sl_mode='atr' 일 때만. 아니면 None(기존과 동일).
atr_arr = compute_atr_series(candles, _atr_period) if _sl_mode_atr else None
ctx_by_code[code] = {
"code": code,
"candles": candles,
"time_index": {c["candle_time"]: idx for idx, c in enumerate(candles)},
"day_open_arr": day_open_arr,
"atr_arr": atr_arr,
"last_exit_dt": {},
"daily_cnt": {},
"pending_entry": None,
}
for c in candles:
all_times_set.add(c["candle_time"])
all_times = sorted(all_times_set)
portfolio: Dict[str, Dict[str, Any]] = {}
all_trades: List[Dict] = []
universe_timeline = params.get("_universe_timeline")
for t in all_times:
slot_key = _bt_slot_key(t, int(params.get("scan_interval_min", 1)))
# 초단위 유니버스(실매 정합) — 타임라인 우선, 없으면 1분 슬롯 폴백
uni_codes = _universe_codes_at(t, slot_key, universe_timeline, universe_by_slot)
uni_set = set(uni_codes) if uni_codes is not None else None
# ── Phase 0: 예약 진입 ──
pending_codes = [
code for code, ctx in ctx_by_code.items()
if ctx.get("pending_entry") and ctx["pending_entry"].get("entry_time") == t
]
pending_codes.sort(key=lambda c: _buy_priority_key(c, uni_codes))
for code in pending_codes:
ctx = ctx_by_code[code]
pe = ctx.pop("pending_entry", None)
if not pe or code in portfolio:
continue
if len(portfolio) >= max_stocks:
break
entry_price = float(pe["entry_price"])
if entry_price <= 0:
continue
exposure = portfolio_exposure_krw(portfolio)
remaining = max(0.0, total_budget - exposure)
target_qty, target_cost = target_qty_and_cost(entry_price, invest_cap)
min_required = target_cost * min_invest_ratio
if target_qty < 1 or remaining < min_required:
skipped_micro_buys += 1
continue
invest = min(invest_cap, remaining, target_cost)
qty = int(invest / entry_price)
if qty < 1:
skipped_micro_buys += 1
continue
cost = qty * entry_price
if cost < min_required:
skipped_micro_buys += 1
continue
if exposure + cost > total_budget + 1e-6:
skipped_micro_buys += 1
continue
portfolio[code] = {
"entry_price": entry_price,
"entry_time": t,
"qty": qty,
"max_price": entry_price,
"entry_atr": float(pe.get("entry_atr") or 0.0), # 신호 봉에서 운반된 ATR
}
ctx["daily_cnt"][t[:8]] = ctx["daily_cnt"].get(t[:8], 0) + 1
break
# ── Phase 1: 청산 ──
for code in list(portfolio.keys()):
ctx = ctx_by_code.get(code)
if ctx is None:
continue
idx = ctx["time_index"].get(t)
if idx is None:
continue
candles = ctx["candles"]
c = candles[idx]
day = t[:8]
cl = float(c["close"])
is_eod = is_strategy_eod_bar(t, params, "BREAKOUT")
pos = portfolio[code]
if t == pos["entry_time"]:
continue
bar = dict(c)
if "open" not in bar or bar.get("open") in (None, ""):
bar["open"] = float(c.get("open") or cl)
res = check_sell_signal_backtest_bar(
pos,
bar,
params,
is_eod=is_eod,
sell_fn=check_sell_signal_breakout_live,
low_mode="current",
)
if not res:
continue
reason, exit_price = res
all_trades.append({
"code": code,
"buy_time": pos["entry_time"],
"sell_time": t,
"buy_price": pos["entry_price"],
"sell_price": round(exit_price, 2),
"qty": pos.get("qty", 1),
"pnl": 0,
"sell_reason": reason,
"hold_min": 0,
})
ctx["last_exit_dt"][day] = _t2dt(t)
del portfolio[code]
# ── Phase 2: 신규 매수 신호 ──
if len(portfolio) >= max_stocks:
continue
exposure = portfolio_exposure_krw(portfolio)
if exposure >= total_budget - 1e-6:
continue
candidates: List[Tuple[Tuple[int, str], str, Dict[str, Any]]] = []
for code, ctx in ctx_by_code.items():
if code in portfolio or ctx.get("pending_entry"):
continue
idx = ctx["time_index"].get(t)
if idx is None:
continue
candles = ctx["candles"]
c = candles[idx]
day = t[:8]
cl = float(c["close"])
if cl <= 0:
continue
if uni_set is not None:
if code not in uni_set:
continue
if day in ctx["last_exit_dt"]:
elapsed = (_t2dt(t) - ctx["last_exit_dt"][day]).total_seconds() / 60
if elapsed < cooldown_min:
continue
if ctx["daily_cnt"].get(day, 0) >= max_daily:
continue
minute_ticks = None
if ticks_by_code:
minute_ticks = (ticks_by_code.get(code) or {}).get(str(t)[:12])
_day_open_arr = ctx.get("day_open_arr")
_day_open = (
_day_open_arr[idx]
if _day_open_arr is not None and 0 <= idx < len(_day_open_arr)
else None
)
code_buy = dict(buy_params)
code_buy["share_denom"] = share_denom_for_code(buy_params, code)
ic = get_indicator_cache_from_params(buy_params, code)
if ic is not None:
code_buy["_indicator_cache"] = ic
inject_whipsaw_ticks_into_params(
code_buy,
ticks_by_code=ticks_by_code,
code=code,
bar_candle_time=t,
strategy="BREAKOUT",
tf_min=1,
)
inject_trigger_snapshots_into_params(
code_buy,
orderbook_by_code=orderbook_by_code,
program_by_code=program_by_code,
code=code,
bar_candle_time=t,
)
_reason, _msg, signal, entry_price, entry_time = breakout_scan_buy_at_bar(
candles, idx, code_buy, minute_ticks=minute_ticks, day_open=_day_open,
)
if not signal or entry_price <= 0 or not entry_time:
continue
if entry_time[:8] != day:
continue
pri = _buy_priority_key(code, uni_codes)
pe = {
"entry_time": entry_time,
"entry_price": entry_price,
"entry_atr": _entry_atr_at(ctx, idx), # 신호 봉 변동성(ATR 동적 손절용)
}
if entry_time == t and code not in portfolio:
exposure = portfolio_exposure_krw(portfolio)
remaining = max(0.0, total_budget - exposure)
target_qty, target_cost = target_qty_and_cost(entry_price, invest_cap)
min_required = target_cost * min_invest_ratio
if (
len(portfolio) < max_stocks
and target_qty >= 1
and remaining >= min_required
and exposure + target_cost <= total_budget + 1e-6
):
invest = min(invest_cap, remaining, target_cost)
qty = int(invest / entry_price)
if qty < 1:
continue
cost = qty * entry_price
if cost >= min_required:
portfolio[code] = {
"entry_price": entry_price,
"entry_time": t,
"qty": qty,
"max_price": entry_price,
"entry_atr": _entry_atr_at(ctx, idx),
}
ctx["daily_cnt"][day] = ctx["daily_cnt"].get(day, 0) + 1
continue
candidates.append((pri, code, pe))
if not candidates:
continue
candidates.sort(key=lambda x: x[0])
_pri, pick_code, pe = candidates[0]
ctx_by_code[pick_code]["pending_entry"] = pe
if skipped_micro_buys:
params["_portfolio_skip_stats"] = {"skipped_micro_buys": skipped_micro_buys}
all_trades.sort(key=lambda x: x["sell_time"])
return all_trades