refactor: MVC 구조 분리 + 미사용 파일 archive 정리
- tick_trader.py를 Controller로 축소, 로직을 3개 모듈로 분리: - core/signal.py: 시그널 감지, 지표 계산 (calc_vr, calc_atr, detect_signal) - core/order.py: Upbit 주문 실행 (매수/매도/취소/조회) - core/position_manager.py: 포지션 관리, DB sync, 복구, 청산 조건 - type hints, Google docstring, 구체적 예외 타입 적용 - 50줄 초과 함수 분리 (process_signal, restore_positions) - 미사용 파일 58개 archive/ 폴더로 이동 - README.md 추가 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
joungmin
310
archive/tests/sweep_1min.py
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310
archive/tests/sweep_1min.py
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"""1분봉 연속 상승 vol spike 전략 파라미터 스윕.
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시그널 조건:
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봉[n-1]: vol_ratio >= VOL_MIN, 양봉 (close > open)
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봉[n] : vol_ratio >= VOL_MIN, 양봉, close > 봉[n-1].close (연속 상승)
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진입: 봉[n] 다음 봉 (봉[n+1]) close에서 즉시
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추적: 1분봉 trail stop (ATR 기반) + time stop
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DB 계산: 지표·시그널·진입·running_peak 모두 Oracle SQL / 월별 배치
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"""
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import sys, os, itertools
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from datetime import datetime, timedelta
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from dotenv import load_dotenv
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load_dotenv(os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), '.env'))
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import pandas as pd
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import oracledb
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import time as _time
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# ── 고정 파라미터 ─────────────────────────────────────────────────────────────
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VOL_LOOKBACK = 61 # vol_ratio 기준: 이전 60봉 평균
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ATR_LOOKBACK = 28 # ATR 계산 봉 수
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TS_N = 240 # 타임스탑 봉수 (240분 = 4시간)
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TIME_STOP_PCT = 0.0 / 100
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FEE = 0.0005
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BUDGET = 15_000_000
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MAX_POS = 3
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PER_POS = BUDGET // MAX_POS
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# ── 스윕 파라미터 ─────────────────────────────────────────────────────────────
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SWEEP = {
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"VOL": [15.0, 20.0, 25.0, 30.0, 40.0, 50.0], # 시그널 거래량 배율 (상위 범위 탐색)
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"ATR_MULT": [1.5, 2.0, 2.5, 3.0],
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"ATR_MIN": [0.005, 0.010, 0.015],
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"ATR_MAX": [0.020, 0.025, 0.030],
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}
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VOL_MIN = min(SWEEP["VOL"]) # SQL pre-filter (15x 이상만 로드)
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# ── 시뮬 구간 ─────────────────────────────────────────────────────────────────
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SIM_START = datetime(2025, 8, 1)
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SIM_END = datetime(2026, 3, 4)
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WARMUP_MINS = 120
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TICKERS = [
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'KRW-XRP','KRW-BTC','KRW-ETH','KRW-SOL','KRW-DOGE',
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'KRW-ADA','KRW-SUI','KRW-NEAR','KRW-KAVA','KRW-SXP',
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'KRW-AKT','KRW-SONIC','KRW-IP','KRW-ORBS','KRW-VIRTUAL',
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'KRW-BARD','KRW-XPL','KRW-KITE','KRW-ENSO','KRW-0G',
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]
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_TK = ",".join(f"'{t}'" for t in TICKERS)
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def _months(start: datetime, end: datetime):
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m = start.replace(day=1)
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while m < end:
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nxt = (m + timedelta(days=32)).replace(day=1)
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if nxt > end:
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nxt = end
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yield m, nxt
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m = nxt
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def _get_conn():
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kwargs = dict(user=os.environ["ORACLE_USER"],
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password=os.environ["ORACLE_PASSWORD"],
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dsn=os.environ["ORACLE_DSN"])
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wallet = os.environ.get("ORACLE_WALLET")
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if wallet:
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kwargs["config_dir"] = wallet
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return oracledb.connect(**kwargs)
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# ── 핵심 SQL ──────────────────────────────────────────────────────────────────
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# 연속 2봉 vol spike + 상승 확인 후 다음 봉 즉시 진입
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TRADE_SQL = f"""
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WITH
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-- 1) 1분봉 + TR + 이전 봉 정보
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base AS (
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SELECT ticker, ts, open_p, close_p, high_p, low_p, volume_p,
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LAG(close_p, 1) OVER (PARTITION BY ticker ORDER BY ts) prev_close,
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LAG(open_p, 1) OVER (PARTITION BY ticker ORDER BY ts) prev_open,
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LAG(volume_p, 1) OVER (PARTITION BY ticker ORDER BY ts) prev_volume,
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GREATEST(
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high_p - low_p,
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ABS(high_p - LAG(close_p,1) OVER (PARTITION BY ticker ORDER BY ts)),
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ABS(low_p - LAG(close_p,1) OVER (PARTITION BY ticker ORDER BY ts))
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) tr
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FROM backtest_ohlcv
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WHERE interval_cd = 'minute1'
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AND ts >= TO_TIMESTAMP(:load_since, 'YYYY-MM-DD HH24:MI:SS')
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AND ts < TO_TIMESTAMP(:sim_end, 'YYYY-MM-DD HH24:MI:SS')
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AND ticker IN ({_TK})
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),
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-- 2) 지표: vol_ratio (현재봉), prev_vol_ratio (이전봉), atr_raw
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indicators AS (
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SELECT ticker, ts, open_p, close_p, prev_close, prev_open,
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-- 현재 봉 vol_ratio
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volume_p / NULLIF(
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AVG(volume_p) OVER (PARTITION BY ticker ORDER BY ts
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ROWS BETWEEN {VOL_LOOKBACK} PRECEDING AND 2 PRECEDING), 0
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) vol_ratio,
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-- 이전 봉 vol_ratio (LAG로 한 봉 앞)
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prev_volume / NULLIF(
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AVG(volume_p) OVER (PARTITION BY ticker ORDER BY ts
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ROWS BETWEEN {VOL_LOOKBACK} PRECEDING AND 2 PRECEDING), 0
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) prev_vol_ratio,
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-- ATR
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AVG(tr) OVER (PARTITION BY ticker ORDER BY ts
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ROWS BETWEEN {ATR_LOOKBACK} PRECEDING AND 1 PRECEDING)
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/ NULLIF(prev_close, 0) atr_raw
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FROM base
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),
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-- 3) 연속 2봉 조건:
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-- 봉[n-1]: prev_vol_ratio >= min_vol, 이전 봉 양봉
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-- 봉[n] : vol_ratio >= min_vol, 양봉, close > prev_close (상승 지속)
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signals AS (
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SELECT ticker, ts sig_ts, close_p sig_price, vol_ratio, atr_raw
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FROM indicators
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WHERE ts >= TO_TIMESTAMP(:sim_start, 'YYYY-MM-DD HH24:MI:SS')
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AND ts < TO_TIMESTAMP(:sim_end, 'YYYY-MM-DD HH24:MI:SS')
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-- 현재 봉 조건
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AND vol_ratio >= :min_vol
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AND close_p > open_p
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-- 이전 봉 조건
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AND prev_vol_ratio >= :min_vol
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AND prev_close > prev_open
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-- 연속 상승
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AND close_p > prev_close
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),
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-- 4) 진입: 시그널 다음 1분봉 즉시
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entry_cands AS (
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SELECT
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s.ticker, s.sig_ts, s.sig_price, s.vol_ratio, s.atr_raw,
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e.ts entry_ts,
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e.close_p entry_price,
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ROW_NUMBER() OVER (PARTITION BY s.ticker, s.sig_ts ORDER BY e.ts) rn
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FROM signals s
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JOIN backtest_ohlcv e
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ON e.ticker = s.ticker
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AND e.interval_cd = 'minute1'
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AND e.ts > s.sig_ts
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AND e.ts <= s.sig_ts + INTERVAL '3' MINUTE
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),
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-- 5) 첫 봉만
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entries AS (
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SELECT ticker, sig_ts, sig_price, vol_ratio, atr_raw,
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entry_ts, entry_price
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FROM entry_cands WHERE rn = 1
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),
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-- 6) 진입 후 TS_N분 1분봉 + 롤링 피크
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post_entry AS (
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SELECT
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e.ticker, e.sig_ts, e.entry_ts, e.entry_price,
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e.vol_ratio, e.atr_raw,
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b.close_p bar_price,
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ROW_NUMBER() OVER (PARTITION BY e.ticker, e.entry_ts ORDER BY b.ts) bar_n,
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MAX(b.close_p) OVER (PARTITION BY e.ticker, e.entry_ts
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ORDER BY b.ts
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ROWS UNBOUNDED PRECEDING) running_peak
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FROM entries e
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JOIN backtest_ohlcv b
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ON b.ticker = e.ticker
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AND b.interval_cd = 'minute1'
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AND b.ts >= e.entry_ts
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AND b.ts <= e.entry_ts + INTERVAL '{TS_N}' MINUTE
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)
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SELECT ticker, sig_ts, entry_ts, entry_price,
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vol_ratio, atr_raw,
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bar_n, bar_price, running_peak
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FROM post_entry
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WHERE bar_n <= :ts_n + 1
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ORDER BY ticker, entry_ts, bar_n
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"""
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# ── 월별 데이터 로드 ──────────────────────────────────────────────────────────
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print(f"연속 2봉 vol spike 전략 (VOL>={VOL_MIN}x, 연속 상승 후 즉시 진입)\n", flush=True)
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print("월별 DB 로드...\n", flush=True)
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conn = _get_conn()
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cur = conn.cursor()
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cur.arraysize = 100_000
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ENTRIES: dict = {}
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t_load = _time.time()
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for m_start, m_end in _months(SIM_START, SIM_END):
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load_since = (m_start - timedelta(minutes=WARMUP_MINS)).strftime('%Y-%m-%d %H:%M:%S')
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sim_start = m_start.strftime('%Y-%m-%d %H:%M:%S')
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sim_end = m_end.strftime('%Y-%m-%d %H:%M:%S')
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t0 = _time.time()
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cur.execute(TRADE_SQL, {
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"load_since": load_since,
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"sim_start": sim_start,
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"sim_end": sim_end,
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"min_vol": VOL_MIN,
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"ts_n": TS_N,
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})
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rows = cur.fetchall()
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t1 = _time.time()
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n_new = 0
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for row in rows:
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(ticker, sig_ts, entry_ts, entry_price,
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vol_ratio, atr_raw,
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bar_n, bar_price, running_peak) = row
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key = (ticker, entry_ts)
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if key not in ENTRIES:
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ENTRIES[key] = {
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'entry_price': float(entry_price),
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'vol_ratio': float(vol_ratio),
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'atr_raw': float(atr_raw) if atr_raw is not None else float('nan'),
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'bars': [],
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}
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n_new += 1
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ENTRIES[key]['bars'].append((float(bar_price), float(running_peak)))
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print(f" {sim_start[:7]}: {len(rows):>8,}행 ({t1-t0:.1f}s) | 진입 {n_new:>5}건", flush=True)
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conn.close()
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print(f"\n총 진입 이벤트: {len(ENTRIES):,}건 | 로드 {_time.time()-t_load:.1f}s\n", flush=True)
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# ── 출구 탐색 ─────────────────────────────────────────────────────────────────
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def find_exit(entry_price: float, atr_stop: float, bars: list) -> float:
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for n, (bp, pk) in enumerate(bars):
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drop = (pk - bp) / pk if pk > 0 else 0.0
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pnl = (bp - entry_price) / entry_price
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if drop >= atr_stop:
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return pnl * 100
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if n + 1 >= TS_N and pnl < TIME_STOP_PCT:
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return pnl * 100
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return (bars[-1][0] - entry_price) / entry_price * 100 if bars else 0.0
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# ── 스윕 ──────────────────────────────────────────────────────────────────────
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ENTRY_LIST = list(ENTRIES.values())
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keys = list(SWEEP.keys())
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combos = list(itertools.product(*SWEEP.values()))
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print(f"총 {len(combos)}가지 조합 스윕...\n", flush=True)
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t_sweep = _time.time()
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results = []
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for combo in combos:
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params = dict(zip(keys, combo))
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if params['ATR_MIN'] >= params['ATR_MAX']:
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continue
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vol_thr = params['VOL']
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atr_mult = params['ATR_MULT']
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atr_min = params['ATR_MIN']
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atr_max = params['ATR_MAX']
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trades = []
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for e in ENTRY_LIST:
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if e['vol_ratio'] < vol_thr:
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continue
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ar = e['atr_raw']
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atr_s = (atr_min if (ar != ar)
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else max(atr_min, min(atr_max, ar * atr_mult)))
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pnl_pct = find_exit(e['entry_price'], atr_s, e['bars'])
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krw = PER_POS * (pnl_pct / 100) - PER_POS * FEE * 2
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trades.append((pnl_pct, krw))
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if not trades:
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results.append({**params, 'trades': 0, 'wins': 0,
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'win_rate': 0.0, 'avg_pnl': 0.0, 'total_krw': 0.0})
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continue
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wins = sum(1 for p, _ in trades if p > 0)
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results.append({
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**params,
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'trades': len(trades),
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'wins': wins,
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'win_rate': wins / len(trades) * 100,
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'avg_pnl': sum(p for p, _ in trades) / len(trades),
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'total_krw': sum(k for _, k in trades),
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})
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print(f"스윕 완료 ({_time.time()-t_sweep:.1f}s)\n")
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# ── 결과 출력 ─────────────────────────────────────────────────────────────────
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df_r = pd.DataFrame(results)
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df_r = df_r[df_r['trades'] > 0].sort_values('total_krw', ascending=False)
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print("=" * 100)
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print(f"{'순위':>4} {'VOL':>5} {'ATR_M':>6} {'ATR_N':>6} {'ATR_X':>6} "
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f"{'건수':>5} {'승률':>6} {'평균PNL':>8} {'총손익':>14}")
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print("=" * 100)
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for rank, (_, row) in enumerate(df_r.head(20).iterrows(), 1):
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print(f"{rank:>4} {row['VOL']:>4.0f}x {row['ATR_MULT']:>6.1f} "
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f"{row['ATR_MIN']*100:>5.1f}% {row['ATR_MAX']*100:>5.1f}% "
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f"{int(row['trades']):>5}건 {row['win_rate']:>5.0f}% "
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f"{row['avg_pnl']:>+7.2f}% {row['total_krw']:>+14,.0f}원")
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# VOL별 최상위 요약
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print("\n" + "─" * 75)
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print(f" {'VOL':>5} {'건수':>5} {'승률':>5} {'평균PNL':>8} {'총손익':>14} (최적 ATR)")
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print("─" * 75)
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for vol in SWEEP["VOL"]:
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sub = df_r[df_r['VOL'] == vol]
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if sub.empty:
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continue
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best = sub.iloc[0]
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print(f" {vol:>4.0f}x {int(best['trades']):>5}건 {best['win_rate']:>4.0f}% "
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f"{best['avg_pnl']:>+7.2f}% {best['total_krw']:>+14,.0f}원 "
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f"(M={best['ATR_MULT']:.1f} N={best['ATR_MIN']*100:.1f}% X={best['ATR_MAX']*100:.1f}%)")
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Reference in New Issue
Block a user