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8 Commits

Author SHA1 Message Date
joungmin
83a229dd26 feat: add market regime filter and compound reinvestment
- Add market_regime.py: BTC/ETH/SOL/XRP weighted 2h trend score
  Bull(≥+1.5%) / Neutral / Bear(<-1%) regime detection with 10min cache
- strategy.py: dynamic TREND/VOL thresholds based on current regime
  Bull: 3%/1.5x, Neutral: 5%/2.0x, Bear: 8%/3.5x
- price_collector.py: always include leader coins in price history
- trader.py: compound reinvestment (profit added to budget, floor at initial)
- notify.py: regime info in hourly report, P&L icons (/, 💚/🔴)
- main.py: hourly status at top-of-hour, filter positions held 1h+
- backtest.py: timestop/combo comparison modes

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-01 10:14:36 +09:00
joungmin
035b3e2f30 fix: use actual order fills for weighted avg sell price
After sell_market_order, query Upbit /v1/order API to get actual
trade fills. If split across multiple fills, compute weighted average
price and use actual paid_fee instead of estimate.

Falls back to get_current_price if order query fails.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-01 06:11:29 +09:00
joungmin
bcef128155 feat: add trade_id + full trade record to trade_results
Each buy generates a UUID trade_id stored in positions table.
Each sell links via same trade_id in trade_results, enabling
round-trip grouping of buy→sell pairs.

Additional fields saved per trade:
- fee_krw: commission amount (0.05% each side)
- krw_profit: net KRW profit/loss after fees
- buy_price / sell_price: exact prices
- invested_krw: capital deployed
- sell_reason: trailing stop / time stop / etc.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-01 05:54:06 +09:00
joungmin
60e739d18b fix: use local 5h volume baseline instead of 23h global average
23h average includes high-volume daytime periods, causing false negatives
at early morning hours. Now compare last 1h candle against the previous
5h local average (same time-of-day context) with 1.2x multiplier.

Also add momentum failure debug logs to show exact reason for rejection.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-01 05:46:25 +09:00
joungmin
5df56a933e feat: use 60min volume, add KRW P&L log, relax re-entry after win
- strategy: replace daily volume check with 60-min candle volume
  (daily volume at 5am is tiny -> BTC/ETH never matched; now uses
  last 1h candle vs previous 23h avg × 2)
- trader: log actual KRW net profit and fee on every sell
- trader: skip re-entry +1% block when last trade was a win
  (allow re-entry on new trend signal even below last sell price)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-01 05:38:37 +09:00
joungmin
d2a5c3ae9e fix: persist sell prices to DB and add WF filter bootstrap
- price_db: add sell_prices table (ensure/upsert/load/delete)
- trader: restore _last_sell_prices from DB on startup so re-entry
  block survives restarts; persist each sell price immediately
- market: retry chunk requests up to 3 times with backoff on 429

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-01 05:19:22 +09:00
joungmin
0b264b304c feat: add backtest module with DB cache and scenario comparison
Backtest improvements:
- Add backtest.py with Oracle DB-backed OHLCV cache (no repeated API calls)
- Add backtest_trades table to cache simulation results by params hash
  (same params -> instant load, skip re-simulation)
- Add walk-forward scenario comparison (--walkforward-cmp)
- Add trend ceiling filter (--trend-cmp, max gain threshold)
- Add ticker win-rate filter (--ticker-cmp, SQL-based instant analysis)
- Precompute daily_features once per data load (not per scenario)

Live bot fixes:
- monitor: add hard stop-loss from buy price (in addition to trailing)
- strategy: fix re-entry condition to require +1% above last sell price
- price_collector: add 48h backfill on startup for trend calculation
- main: call backfill_prices() at startup

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-28 23:28:27 +09:00
joungmin
4888aa0faa feat: add walk-forward trade filter to prevent re-entry on losing tickers
- Add trade_results table to Oracle DB for persistent trade history
- Record win/loss after each sell with pnl_pct
- Load last N trades per ticker from DB on startup (survives restarts)
- Block buy() when recent win rate (last 5 trades) < 40% threshold
- Configurable via WF_WINDOW and WF_MIN_WIN_RATE env vars
- Backtest showed improvement from -7.5% to +37.4% cumulative return

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-28 23:28:07 +09:00
10 changed files with 2588 additions and 99 deletions

1701
backtest.py Normal file

File diff suppressed because it is too large Load Diff

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@@ -29,15 +29,27 @@ def get_top_tickers() -> list[str]:
if not all_tickers:
return []
# 100개씩 나눠서 조회 (URL 길이 제한)
# 100개씩 나눠서 조회 (URL 길이 제한, 429 재시도 포함)
chunk_size = 100
ticker_data = []
for i in range(0, len(all_tickers), chunk_size):
chunk = all_tickers[i:i + chunk_size]
params = {"markets": ",".join(chunk)}
for attempt in range(3):
try:
resp = requests.get(_TICKER_URL, params=params, timeout=5)
if resp.status_code == 429:
wait = 2 ** attempt # 1s → 2s → 4s
logger.warning(f"429 Rate Limit, {wait}s 대기 후 재시도 ({attempt+1}/3)")
time.sleep(wait)
continue
resp.raise_for_status()
ticker_data.extend(resp.json())
break
except Exception as e:
if attempt == 2:
raise
time.sleep(1)
# 스테이블코인 제외
EXCLUDE = {"KRW-USDT", "KRW-USDC", "KRW-DAI", "KRW-BUSD"}

110
core/market_regime.py Normal file
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@@ -0,0 +1,110 @@
"""시장 레짐(Bull/Neutral/Bear) 판단.
BTC·ETH·SOL·XRP 가중 평균 2h 추세로 레짐을 결정하고
매수 조건 파라미터(trend_pct, vol_mult)를 동적으로 반환한다.
계산된 현재가는 price_history DB에 저장해 재활용한다.
"""
from __future__ import annotations
import logging
import time
import pyupbit
from .price_db import get_price_n_hours_ago, insert_prices
logger = logging.getLogger(__name__)
# 대장 코인 가중치
LEADERS: dict[str, float] = {
"KRW-BTC": 0.40,
"KRW-ETH": 0.30,
"KRW-SOL": 0.15,
"KRW-XRP": 0.15,
}
TREND_HOURS = 2 # 2h 추세 기준
BULL_THRESHOLD = 1.5 # score ≥ 1.5% → Bull
BEAR_THRESHOLD = -1.0 # score < -1.0% → Bear
# 레짐별 매수 조건 파라미터
REGIME_PARAMS: dict[str, dict] = {
"bull": {"trend_pct": 3.0, "vol_mult": 1.5, "emoji": "🟢"},
"neutral": {"trend_pct": 5.0, "vol_mult": 2.0, "emoji": "🟡"},
"bear": {"trend_pct": 8.0, "vol_mult": 3.5, "emoji": "🔴"},
}
# 10분 캐시 (스캔 루프마다 API 호출 방지)
_cache: dict = {}
_cache_ts: float = 0.0
_CACHE_TTL = 600
def get_regime() -> dict:
"""현재 시장 레짐 반환.
Returns:
{
'name': 'bull' | 'neutral' | 'bear',
'score': float, # 가중 평균 2h 추세(%)
'trend_pct': float, # 매수 추세 임계값
'vol_mult': float, # 거래량 배수 임계값
'emoji': str,
}
"""
global _cache, _cache_ts
if _cache and (time.time() - _cache_ts) < _CACHE_TTL:
return _cache
score = 0.0
current_prices: dict[str, float] = {}
for ticker, weight in LEADERS.items():
try:
current = pyupbit.get_current_price(ticker)
if not current:
continue
current_prices[ticker] = current
# DB에서 2h 전 가격 조회 → 없으면 API 캔들로 대체
past = get_price_n_hours_ago(ticker, TREND_HOURS)
if past is None:
df = pyupbit.get_ohlcv(ticker, interval="minute60", count=4)
if df is not None and len(df) >= 3:
past = float(df["close"].iloc[-3])
if past:
trend = (current - past) / past * 100
score += trend * weight
logger.debug(f"[레짐] {ticker} {trend:+.2f}% (기여 {trend*weight:+.3f})")
except Exception as e:
logger.warning(f"[레짐] {ticker} 오류: {e}")
# 현재가 DB 저장 (다음 레짐 계산 및 추세 판단에 재활용)
if current_prices:
try:
insert_prices(current_prices)
except Exception as e:
logger.warning(f"[레짐] 가격 저장 오류: {e}")
# 레짐 결정
if score >= BULL_THRESHOLD:
name = "bull"
elif score < BEAR_THRESHOLD:
name = "bear"
else:
name = "neutral"
params = REGIME_PARAMS[name]
result = {"name": name, "score": round(score, 3), **params}
logger.info(
f"[레짐] score={score:+.3f}% → {params['emoji']} {name.upper()} "
f"(TREND≥{params['trend_pct']}% / VOL≥{params['vol_mult']}x)"
)
_cache = result
_cache_ts = time.time()
return result

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@@ -19,7 +19,7 @@ TIME_STOP_MIN_GAIN_PCT = float(os.getenv("TIME_STOP_MIN_GAIN_PCT", "3"))
def _check_trailing_stop(ticker: str, pos: dict, current: float) -> bool:
"""트레일링 스탑 체크. 매도 시 True 반환."""
"""트레일링 스탑(최고가 기준) + 고정 스탑(매수가 기준) 체크. 매도 시 True 반환."""
trader.update_peak(ticker, current)
pos = trader.get_positions().get(ticker)
@@ -27,15 +27,24 @@ def _check_trailing_stop(ticker: str, pos: dict, current: float) -> bool:
return False
peak = pos["peak_price"]
buy_price = pos["buy_price"]
drop_from_peak = (peak - current) / peak
drop_from_buy = (buy_price - current) / buy_price # 구매가 대비 하락률
if drop_from_peak >= STOP_LOSS_PCT:
reason = (
f"트레일링스탑 | 최고가={peak:,.0f}원 → "
f"현재={current:,.0f}원 ({drop_from_peak:.1%} 하락)"
)
trader.sell(ticker, reason=reason)
return True
return trader.sell(ticker, reason=reason)
if drop_from_buy >= STOP_LOSS_PCT:
reason = (
f"스탑로스 | 매수가={buy_price:,.0f}원 → "
f"현재={current:,.0f}원 ({drop_from_buy:.1%} 하락)"
)
return trader.sell(ticker, reason=reason)
return False
@@ -70,15 +79,17 @@ def _check_position(ticker: str, pos: dict) -> None:
if current is None:
return
pnl = (current - pos["buy_price"]) / pos["buy_price"] * 100
buy_price = pos["buy_price"]
pnl = (current - buy_price) / buy_price * 100
peak = pos["peak_price"]
drop_from_peak = (peak - current) / peak
drop_from_buy = (buy_price - current) / buy_price
entry_time = pos.get("entry_time", datetime.now())
elapsed_hours = (datetime.now() - entry_time).total_seconds() / 3600
logger.info(
f"[감시] {ticker} 현재={current:,.0f} | 최고={peak:,.0f} | "
f"하락={drop_from_peak:.1%} | 수익률={pnl:+.1f}% | "
f"[감시] {ticker} 현재={current:,.0f} | 매수가={buy_price:,.0f} | 최고={peak:,.0f} | "
f"수익률={pnl:+.1f}% | peak하락={drop_from_peak:.1%} | buy하락={drop_from_buy:.1%} | "
f"보유={elapsed_hours:.1f}h"
)
@@ -94,7 +105,7 @@ def run_monitor(interval: int = CHECK_INTERVAL) -> None:
"""전체 포지션 감시 루프."""
logger.info(
f"모니터 시작 | 체크={interval}초 | "
f"트레일링스탑={STOP_LOSS_PCT:.0%} | "
f"트레일링스탑={STOP_LOSS_PCT:.1%} | "
f"타임스탑={TIME_STOP_HOURS:.0f}h/{TIME_STOP_MIN_GAIN_PCT:+.0f}%"
)
while True:

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@@ -28,21 +28,36 @@ def _send(text: str) -> None:
logger.error(f"Telegram 알림 실패: {e}")
def notify_buy(ticker: str, price: float, amount: float, invested_krw: int) -> None:
def notify_buy(
ticker: str, price: float, amount: float, invested_krw: int,
max_budget: int = 0, per_position: int = 0,
) -> None:
budget_line = (
f"운용예산: {max_budget:,}원 (포지션당 {per_position:,}원)\n"
if max_budget else ""
)
_send(
f"📈 <b>[매수]</b> {ticker}\n"
f"가격: {price:,.0f}\n"
f"수량: {amount}\n"
f"투자금: {invested_krw:,}"
f"투자금: {invested_krw:,}\n"
f"{budget_line}"
)
def notify_sell(ticker: str, price: float, pnl_pct: float, reason: str) -> None:
emoji = "" if pnl_pct >= 0 else "🔴"
def notify_sell(
ticker: str, price: float, pnl_pct: float, reason: str,
krw_profit: float = 0.0, fee_krw: float = 0.0,
cum_profit: float = 0.0,
) -> None:
trade_emoji = "" if pnl_pct >= 0 else ""
cum_emoji = "💚" if cum_profit >= 0 else "🔴"
_send(
f"{emoji} <b>[매도]</b> {ticker}\n"
f"{trade_emoji} <b>[매도]</b> {ticker}\n"
f"가격: {price:,.0f}\n"
f"수익률: {pnl_pct:+.1f}%\n"
f"수익률: {pnl_pct:+.2f}%\n"
f"실손익: {krw_profit:+,.0f}원 (수수료 {fee_krw:,.0f}원)\n"
f"{cum_emoji} 누적손익: {cum_profit:+,.0f}\n"
f"사유: {reason}"
)
@@ -51,19 +66,50 @@ def notify_error(message: str) -> None:
_send(f"⚠️ <b>[오류]</b>\n{message}")
def notify_status(positions: dict) -> None:
"""1시간마다 포지션 현황 요약 전송."""
def notify_status(
positions: dict,
max_budget: int = 0,
per_position: int = 0,
cum_profit: float = 0.0,
) -> None:
"""정각마다 시장 레짐 + 1시간 이상 보유 포지션 현황 전송."""
from datetime import datetime
import pyupbit
from .market_regime import get_regime
now = datetime.now().strftime("%H:%M")
cum_sign = "+" if cum_profit >= 0 else ""
if not positions:
_send(f"📊 <b>[{now} 현황]</b>\n보유 포지션 없음 — 매수 신호 대기 중")
# 시장 레짐
regime = get_regime()
regime_line = (
f"{regime['emoji']} 시장: {regime['name'].upper()} "
f"(score {regime['score']:+.2f}%) "
f"| 조건 TREND≥{regime['trend_pct']}% / VOL≥{regime['vol_mult']}x\n"
)
# 1시간 이상 보유 포지션만 필터
long_positions = {
ticker: pos for ticker, pos in positions.items()
if (datetime.now() - pos["entry_time"]).total_seconds() >= 3600
}
cum_emoji = "💚" if cum_profit >= 0 else "🔴"
budget_info = (
f"💰 운용예산: {max_budget:,}원 | 포지션당: {per_position:,}\n"
f"{cum_emoji} 누적손익: {cum_sign}{cum_profit:,.0f}\n"
if max_budget else ""
)
# 포지션 없어도 레짐 정보는 전송
header = f"📊 <b>[{now} 현황]</b>\n{regime_line}{budget_info}"
if not long_positions:
_send(header + "1h+ 보유 포지션 없음")
return
lines = [f"📊 <b>[{now} 현황]</b>"]
for ticker, pos in positions.items():
lines = [header]
for ticker, pos in long_positions.items():
current = pyupbit.get_current_price(ticker)
if not current:
continue
@@ -73,9 +119,9 @@ def notify_status(positions: dict) -> None:
elapsed = (datetime.now() - pos["entry_time"]).total_seconds() / 3600
emoji = "📈" if pnl >= 0 else "📉"
lines.append(
f"\n{emoji} <b>{ticker}</b>\n"
f"{emoji} <b>{ticker}</b>\n"
f" 현재가: {current:,.0f}\n"
f" 수익률: {pnl:+.1f}%\n"
f" 수익률: {pnl:+.2f}%\n"
f" 최고가 대비: -{drop:.1f}%\n"
f" 보유: {elapsed:.1f}h"
)

View File

@@ -5,10 +5,12 @@ from __future__ import annotations
import logging
import time
import pyupbit
import requests
from .market import get_top_tickers
from .price_db import cleanup_old_prices, insert_prices
from .market_regime import LEADERS
from .price_db import cleanup_old_prices, insert_prices, insert_prices_with_time
logger = logging.getLogger(__name__)
@@ -16,6 +18,42 @@ COLLECT_INTERVAL = 600 # 10분 (초)
CLEANUP_EVERY = 6 # 1시간(10분 × 6)마다 오래된 데이터 정리
def backfill_prices(hours: int = 48) -> None:
"""시작 시 과거 N시간치 1시간봉 종가를 DB에 백필.
price_history에 데이터가 없으면 추세 판단이 불가능하므로
봇 시작 직후 한 번 호출해 과거 데이터를 채운다.
"""
tickers = get_top_tickers()
if not tickers:
logger.warning("[백필] 종목 목록 없음, 스킵")
return
# 대장 코인 항상 포함
for leader in LEADERS:
if leader not in tickers:
tickers = tickers + [leader]
count = hours + 2 # 여유 있게 요청
total_rows = 0
for ticker in tickers:
try:
df = pyupbit.get_ohlcv(ticker, interval="minute60", count=count)
if df is None or df.empty:
continue
rows = [
(ticker, float(row["close"]), ts.to_pydatetime())
for ts, row in df.iterrows()
]
insert_prices_with_time(rows)
total_rows += len(rows)
time.sleep(0.1)
except Exception as e:
logger.error(f"[백필] {ticker} 오류: {e}")
logger.info(f"[백필] 완료 — {len(tickers)}개 종목 / {total_rows}개 레코드 저장")
def run_collector(interval: int = COLLECT_INTERVAL) -> None:
"""가격 수집 루프."""
logger.info(f"가격 수집기 시작 (주기={interval//60}분)")
@@ -26,6 +64,10 @@ def run_collector(interval: int = COLLECT_INTERVAL) -> None:
tickers = get_top_tickers()
if not tickers:
continue
# 대장 코인은 top20 밖이어도 항상 포함
for leader in LEADERS:
if leader not in tickers:
tickers = tickers + [leader]
resp = requests.get(
"https://api.upbit.com/v1/ticker",
params={"markets": ",".join(tickers)},

View File

@@ -44,7 +44,7 @@ def _conn() -> Generator[oracledb.Connection, None, None]:
def insert_prices(ticker_prices: dict[str, float]) -> None:
"""여러 종목의 현재가를 한 번에 저장."""
"""여러 종목의 현재가를 한 번에 저장 (recorded_at = 현재 시각)."""
if not ticker_prices:
return
rows = [(ticker, price) for ticker, price in ticker_prices.items()]
@@ -53,6 +53,18 @@ def insert_prices(ticker_prices: dict[str, float]) -> None:
conn.cursor().executemany(sql, rows)
def insert_prices_with_time(rows: list[tuple]) -> None:
"""(ticker, price, recorded_at) 튜플 리스트를 한 번에 저장 (백필용)."""
if not rows:
return
sql = """
INSERT INTO price_history (ticker, price, recorded_at)
VALUES (:1, :2, :3)
"""
with _conn() as conn:
conn.cursor().executemany(sql, rows)
def get_price_n_hours_ago(ticker: str, hours: float) -> Optional[float]:
"""N시간 전 가장 가까운 가격 반환. 데이터 없으면 None."""
sql = """
@@ -89,3 +101,208 @@ def cleanup_old_prices(keep_hours: int = 48) -> None:
sql = f"DELETE FROM price_history WHERE recorded_at < SYSTIMESTAMP - ({keep_hours}/24)"
with _conn() as conn:
conn.cursor().execute(sql)
# ── 포지션 영구 저장 (재시작 후 실제 매수가 복원용) ──────────────────────────
def upsert_position(
ticker: str,
buy_price: float,
peak_price: float,
amount: float,
invested_krw: int,
entry_time: str, # ISO 포맷 문자열
trade_id: str = "",
) -> None:
"""포지션 저장 또는 갱신 (MERGE)."""
sql = """
MERGE INTO positions p
USING (SELECT :ticker AS ticker FROM dual) s
ON (p.ticker = s.ticker)
WHEN MATCHED THEN
UPDATE SET peak_price = :peak_price,
amount = :amount,
invested_krw = :invested_krw,
updated_at = SYSTIMESTAMP
WHEN NOT MATCHED THEN
INSERT (ticker, buy_price, peak_price, amount, invested_krw, entry_time, trade_id)
VALUES (:ticker, :buy_price, :peak_price, :amount, :invested_krw,
TO_TIMESTAMP(:entry_time, 'YYYY-MM-DD"T"HH24:MI:SS.FF6'), :trade_id)
"""
with _conn() as conn:
conn.cursor().execute(sql, {
"ticker": ticker,
"buy_price": buy_price,
"peak_price": peak_price,
"amount": amount,
"invested_krw": invested_krw,
"entry_time": entry_time,
"trade_id": trade_id,
})
def delete_position(ticker: str) -> None:
"""포지션 삭제 (매도 완료 시)."""
with _conn() as conn:
conn.cursor().execute(
"DELETE FROM positions WHERE ticker = :ticker", {"ticker": ticker}
)
# ── Walk-forward 거래 이력 ────────────────────────────────────────────────────
def ensure_trade_results_table() -> None:
"""trade_results 테이블이 없으면 생성."""
ddl = """
CREATE TABLE trade_results (
id NUMBER GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
ticker VARCHAR2(20) NOT NULL,
is_win NUMBER(1) NOT NULL,
pnl_pct NUMBER(10,4),
traded_at TIMESTAMP DEFAULT SYSTIMESTAMP NOT NULL
)
"""
idx = "CREATE INDEX idx_tr_ticker ON trade_results (ticker, traded_at DESC)"
with _conn() as conn:
for sql in (ddl, idx):
try:
conn.cursor().execute(sql)
except oracledb.DatabaseError as e:
if e.args[0].code not in (955, 1408):
raise
def record_trade(
ticker: str,
is_win: bool,
pnl_pct: float,
fee_krw: float = 0.0,
krw_profit: float = 0.0,
trade_id: str = "",
buy_price: float = 0.0,
sell_price: float = 0.0,
invested_krw: int = 0,
sell_reason: str = "",
) -> None:
"""거래 결과 저장 (수수료·KRW 손익·trade_id 포함)."""
with _conn() as conn:
conn.cursor().execute(
"INSERT INTO trade_results "
"(ticker, is_win, pnl_pct, fee_krw, krw_profit, "
" trade_id, buy_price, sell_price, invested_krw, sell_reason) "
"VALUES (:t, :w, :p, :f, :k, :tid, :bp, :sp, :ikrw, :sr)",
{
"t": ticker,
"w": 1 if is_win else 0,
"p": round(pnl_pct, 4),
"f": round(fee_krw, 2),
"k": round(krw_profit, 2),
"tid": trade_id,
"bp": buy_price,
"sp": sell_price,
"ikrw": invested_krw,
"sr": sell_reason,
},
)
def get_cumulative_krw_profit() -> float:
"""전체 거래 누적 KRW 손익 반환 (수수료 차감 후). 데이터 없으면 0."""
with _conn() as conn:
cur = conn.cursor()
cur.execute("SELECT SUM(krw_profit) FROM trade_results WHERE krw_profit IS NOT NULL")
row = cur.fetchone()
return float(row[0]) if row and row[0] is not None else 0.0
def load_recent_wins(ticker: str, n: int = 5) -> list[bool]:
"""직전 N건 거래의 승/패 리스트 반환 (오래된 순). 없으면 빈 리스트."""
sql = """
SELECT is_win FROM (
SELECT is_win FROM trade_results
WHERE ticker = :t
ORDER BY traded_at DESC
FETCH FIRST :n ROWS ONLY
) ORDER BY ROWNUM DESC
"""
with _conn() as conn:
cur = conn.cursor()
cur.execute(sql, {"t": ticker, "n": n})
rows = cur.fetchall()
return [bool(r[0]) for r in rows]
# ── 직전 매도가 영구 저장 (재시작 후 재매수 차단 유지용) ──────────────────────
def ensure_sell_prices_table() -> None:
"""sell_prices 테이블이 없으면 생성."""
ddl = """
CREATE TABLE sell_prices (
ticker VARCHAR2(20) NOT NULL PRIMARY KEY,
price NUMBER(20,8) NOT NULL,
updated_at TIMESTAMP DEFAULT SYSTIMESTAMP NOT NULL
)
"""
with _conn() as conn:
try:
conn.cursor().execute(ddl)
except oracledb.DatabaseError as e:
if e.args[0].code != 955: # ORA-00955: 이미 존재
raise
def upsert_sell_price(ticker: str, price: float) -> None:
"""직전 매도가 저장 또는 갱신."""
sql = """
MERGE INTO sell_prices s
USING (SELECT :ticker AS ticker FROM dual) d
ON (s.ticker = d.ticker)
WHEN MATCHED THEN
UPDATE SET price = :price, updated_at = SYSTIMESTAMP
WHEN NOT MATCHED THEN
INSERT (ticker, price) VALUES (:ticker, :price)
"""
with _conn() as conn:
conn.cursor().execute(sql, {"ticker": ticker, "price": price})
def load_sell_prices() -> dict[str, float]:
"""저장된 직전 매도가 전체 로드."""
with _conn() as conn:
cur = conn.cursor()
cur.execute("SELECT ticker, price FROM sell_prices")
return {r[0]: float(r[1]) for r in cur.fetchall()}
def delete_sell_price(ticker: str) -> None:
"""매도가 기록 삭제 (더 이상 필요 없을 때)."""
with _conn() as conn:
conn.cursor().execute(
"DELETE FROM sell_prices WHERE ticker = :ticker", {"ticker": ticker}
)
def load_positions() -> list[dict]:
"""저장된 전체 포지션 로드."""
sql = """
SELECT ticker, buy_price, peak_price, amount, invested_krw,
TO_CHAR(entry_time, 'YYYY-MM-DD"T"HH24:MI:SS.FF6') AS entry_time,
trade_id
FROM positions
"""
with _conn() as conn:
cursor = conn.cursor()
cursor.execute(sql)
rows = cursor.fetchall()
return [
{
"ticker": r[0],
"buy_price": float(r[1]),
"peak_price": float(r[2]),
"amount": float(r[3]),
"invested_krw": int(r[4]),
"entry_time": r[5],
"trade_id": r[6] or "",
}
for r in rows
]

View File

@@ -1,29 +1,32 @@
"""Strategy C: 실시간 상승 추세(DB) AND 거래량 모멘텀 동시 충족 시 매수 신호."""
"""Strategy C: 현재 기준 N시간 전 대비 상승 추세(DB) AND 거래량 모멘텀 동시 충족 시 매수 신호."""
from __future__ import annotations
import logging
import os
import pyupbit
from .market import get_current_price, get_ohlcv
from .market_regime import get_regime
from .price_db import get_price_n_hours_ago
logger = logging.getLogger(__name__)
# 추세 판단: N시간 전 대비 +M% 이상이면 상승 중
TREND_HOURS = float(os.getenv("TREND_HOURS", "1"))
TREND_MIN_GAIN_PCT = float(os.getenv("TREND_MIN_GAIN_PCT", "3"))
# 추세 판단: 현재 기준 N시간 전 DB 가격 대비 +M% 이상이면 상승 중
TREND_HOURS = float(os.getenv("TREND_HOURS", "12"))
TREND_MIN_GAIN_PCT = float(os.getenv("TREND_MIN_GAIN_PCT", "5")) # 레짐이 없을 때 기본값
# 모멘텀: MA 기간, 거래량 급증 배수
MA_PERIOD = 20
VOLUME_MULTIPLIER = 2.0
VOLUME_MULTIPLIER = float(os.getenv("VOLUME_MULTIPLIER", "2.0")) # 레짐이 없을 때 기본값
LOCAL_VOL_HOURS = 5 # 로컬 기준 시간 (h)
def check_trend(ticker: str) -> bool:
"""상승 추세 조건: 현재가가 N시간 전 대비 +M% 이상."""
def check_trend(ticker: str, min_gain_pct: float) -> bool:
"""상승 추세 조건: 현재가가 DB에 저장된 N시간 전 가격 대비 +min_gain_pct% 이상."""
past_price = get_price_n_hours_ago(ticker, TREND_HOURS)
if past_price is None:
logger.debug(f"[추세] {ticker} 과거 가격 없음 (데이터 수집 중)")
logger.debug(f"[추세] {ticker} {TREND_HOURS:.0f}h 전 가격 없음 (수집 중)")
return False
current = get_current_price(ticker)
@@ -31,48 +34,74 @@ def check_trend(ticker: str) -> bool:
return False
gain_pct = (current - past_price) / past_price * 100
result = gain_pct >= TREND_MIN_GAIN_PCT
result = gain_pct >= min_gain_pct
if result:
logger.info(
f"[추세↑] {ticker} {TREND_HOURS:.0f}h 전={past_price:,.0f} "
f"현재={current:,.0f} (+{gain_pct:.1f}%)"
f"[추세↑] {ticker} {TREND_HOURS:.0f}h 전={past_price:,.2f} "
f"현재={current:,.2f} (+{gain_pct:.1f}%{min_gain_pct}%)"
)
else:
logger.debug(
f"[추세✗] {ticker} {gain_pct:+.1f}% (기준={TREND_MIN_GAIN_PCT:+.0f}%)"
f"[추세✗] {ticker} {gain_pct:+.1f}% (기준={min_gain_pct:+.0f}%)"
)
return result
def check_momentum(ticker: str) -> bool:
"""모멘텀 조건: 현재가 > MA20 AND 오늘 거래량 > 20일 평균 × 2."""
df = get_ohlcv(ticker, count=MA_PERIOD + 1)
if df is None or len(df) < MA_PERIOD + 1:
def check_momentum(ticker: str, vol_mult: float) -> bool:
"""모멘텀 조건: 현재가 > MA20(일봉) AND 최근 1h 거래량 > 로컬 5h 평균 × vol_mult.
23h 평균은 낮 시간대 고거래량이 포함돼 새벽에 항상 미달하므로,
로컬 5h 평균(같은 시간대 컨텍스트)과 비교한다.
"""
# MA20: 일봉 기준
df_daily = get_ohlcv(ticker, count=MA_PERIOD + 1)
if df_daily is None or len(df_daily) < MA_PERIOD + 1:
return False
ma = df["close"].iloc[-MA_PERIOD:].mean()
avg_vol = df["volume"].iloc[:-1].mean()
today_vol = df["volume"].iloc[-1]
ma = df_daily["close"].iloc[-MA_PERIOD:].mean()
current = get_current_price(ticker)
if current is None:
return False
price_ok = current > ma
vol_ok = today_vol > avg_vol * VOLUME_MULTIPLIER
result = price_ok and vol_ok
if not price_ok:
logger.debug(f"[모멘텀✗] {ticker} 현재={current:,.0f} < MA20={ma:,.0f} (가격 기준 미달)")
return False
if result:
logger.debug(
f"[모멘텀] {ticker} 현재={current:,.0f} MA20={ma:,.0f} "
f"거래량={today_vol:.0f} 평균={avg_vol:.0f}"
# 거래량: 60분봉 기준 (최근 1h vs 이전 LOCAL_VOL_HOURS h 로컬 평균)
fetch_count = LOCAL_VOL_HOURS + 3 # 여유 있게 fetch
try:
df_hour = pyupbit.get_ohlcv(ticker, interval="minute60", count=fetch_count)
except Exception:
return False
if df_hour is None or len(df_hour) < LOCAL_VOL_HOURS + 1:
return False
recent_vol = df_hour["volume"].iloc[-2] # 직전 완성된 1h 봉
local_avg = df_hour["volume"].iloc[-(LOCAL_VOL_HOURS + 1):-2].mean() # 이전 LOCAL_VOL_HOURS h 평균
vol_ok = local_avg > 0 and recent_vol >= local_avg * vol_mult
ratio = recent_vol / local_avg if local_avg > 0 else 0
if vol_ok:
logger.info(
f"[모멘텀↑] {ticker} 현재={current:,.0f} MA20={ma:,.0f} "
f"1h거래량={recent_vol:.0f} 로컬{LOCAL_VOL_HOURS}h평균={local_avg:.0f} ({ratio:.2f}x ≥ {vol_mult}x)"
)
return result
else:
logger.debug(
f"[모멘텀✗] {ticker} 1h거래량={recent_vol:.0f} 로컬{LOCAL_VOL_HOURS}h평균={local_avg:.0f} "
f"({ratio:.2f}x < {vol_mult}x)"
)
return vol_ok
def should_buy(ticker: str) -> bool:
"""Strategy C: 실시간 상승 추세 AND 거래량 모멘텀 모두 충족 시 True."""
if not check_trend(ticker):
"""Strategy C + 시장 레짐: 레짐별 동적 임계값으로 추세 AND 모멘텀 판단."""
regime = get_regime()
trend_pct = regime["trend_pct"]
vol_mult = regime["vol_mult"]
if not check_trend(ticker, trend_pct):
return False
return check_momentum(ticker)
return check_momentum(ticker, vol_mult)

View File

@@ -6,25 +6,65 @@ import logging
import os
import threading
import time
import uuid
from datetime import datetime
from typing import Optional
import pyupbit
from dotenv import load_dotenv
from .notify import notify_buy, notify_sell, notify_error
from .price_db import (
delete_position, load_positions, upsert_position,
ensure_trade_results_table, record_trade, load_recent_wins,
ensure_sell_prices_table, upsert_sell_price, load_sell_prices,
get_cumulative_krw_profit,
)
load_dotenv()
logger = logging.getLogger(__name__)
MAX_BUDGET = 1_000_000 # 총 운용 한도: 100만원
MAX_POSITIONS = 3 # 최대 동시 보유 종목 수
PER_POSITION = MAX_BUDGET // MAX_POSITIONS # 종목당 33만3천원
INITIAL_BUDGET = int(os.getenv("MAX_BUDGET", "10000000")) # 초기 원금 (고정)
MAX_POSITIONS = int(os.getenv("MAX_POSITIONS", "3")) # 최대 동시 보유 종목 수
# 복리 적용 예산 (매도 후 재계산) — 수익 발생 시만 증가, 손실 시 원금 유지
MAX_BUDGET = INITIAL_BUDGET
PER_POSITION = INITIAL_BUDGET // MAX_POSITIONS
def _recalc_compound_budget() -> None:
"""누적 수익을 반영해 MAX_BUDGET / PER_POSITION 재계산.
수익이 발생한 만큼만 예산에 더함 (손실 시 원금 아래로 내려가지 않음).
매도 완료 후 호출.
"""
global MAX_BUDGET, PER_POSITION
try:
cum_profit = get_cumulative_krw_profit()
effective = INITIAL_BUDGET + max(int(cum_profit), 0)
MAX_BUDGET = effective
PER_POSITION = effective // MAX_POSITIONS
logger.info(
f"[복리] 누적수익={cum_profit:+,.0f}원 | "
f"운용예산={MAX_BUDGET:,}원 | 포지션당={PER_POSITION:,}"
)
except Exception as e:
logger.warning(f"[복리] 예산 재계산 실패 (이전 값 유지): {e}")
# Walk-forward 필터 설정
WF_WINDOW = int(float(os.getenv("WF_WINDOW", "5"))) # 이력 윈도우 크기
WF_MIN_WIN_RATE = float(os.getenv("WF_MIN_WIN_RATE", "0.40")) # 최소 승률 임계값
_lock = threading.Lock()
_positions: dict = {}
# 구조: { ticker: { buy_price, peak_price, amount, invested_krw, entry_time } }
_last_sell_prices: dict[str, float] = {}
# 직전 매도가 기록 — 재매수 시 이 가격 이상일 때만 진입 허용
_trade_history: dict[str, list[bool]] = {}
# walk-forward 이력: { ticker: [True/False, ...] } (True=수익)
_upbit: Optional[pyupbit.Upbit] = None
@@ -35,14 +75,107 @@ def _get_upbit() -> pyupbit.Upbit:
return _upbit
def _get_history(ticker: str) -> list[bool]:
"""in-memory 이력 반환. 없으면 DB에서 초기 로드."""
if ticker not in _trade_history:
try:
_trade_history[ticker] = load_recent_wins(ticker, WF_WINDOW)
except Exception:
_trade_history[ticker] = []
return _trade_history[ticker]
def _update_history(
ticker: str, is_win: bool, pnl_pct: float,
fee_krw: float = 0.0, krw_profit: float = 0.0,
trade_id: str = "", buy_price: float = 0.0,
sell_price: float = 0.0, invested_krw: int = 0,
sell_reason: str = "",
) -> None:
"""매도 후 in-memory 이력 갱신 + DB 기록."""
hist = _trade_history.setdefault(ticker, [])
hist.append(is_win)
# 윈도우 초과분 제거 (메모리 절약)
if len(hist) > WF_WINDOW * 2:
_trade_history[ticker] = hist[-WF_WINDOW:]
try:
record_trade(
ticker, is_win, pnl_pct, fee_krw, krw_profit,
trade_id, buy_price, sell_price, invested_krw, sell_reason,
)
except Exception as e:
logger.error(f"거래 이력 저장 실패 {ticker}: {e}")
def _db_upsert(ticker: str, pos: dict) -> None:
"""포지션을 Oracle DB에 저장 (실패해도 거래는 계속)."""
try:
upsert_position(
ticker=ticker,
buy_price=pos["buy_price"],
peak_price=pos["peak_price"],
amount=pos["amount"],
invested_krw=pos["invested_krw"],
entry_time=pos["entry_time"].isoformat(),
trade_id=pos.get("trade_id", ""),
)
except Exception as e:
logger.error(f"포지션 DB 저장 실패 {ticker}: {e}")
def get_positions() -> dict:
return _positions
def get_budget_info() -> dict:
"""현재 복리 예산 정보 반환 (main.py 등 외부에서 동적 조회용)."""
return {
"max_budget": MAX_BUDGET,
"per_position": PER_POSITION,
"initial": INITIAL_BUDGET,
}
def restore_positions() -> None:
"""시작 시 Upbit 실제 잔고를 읽어 포지션 복원 (재시작 이중 매수 방지)."""
"""시작 시 Oracle DB + Upbit 잔고를 교차 확인하여 포지션 복원.
trade_results 테이블도 이 시점에 생성 (없으면).
DB에 저장된 실제 매수가를 복원하고, Upbit 잔고에 없으면 DB에서도 삭제한다.
"""
# trade_results / sell_prices 테이블 초기화
try:
ensure_trade_results_table()
except Exception as e:
logger.warning(f"trade_results 테이블 생성 실패 (무시): {e}")
# 시작 시 복리 예산 복원 (이전 세션 수익 반영)
_recalc_compound_budget()
try:
ensure_sell_prices_table()
except Exception as e:
logger.warning(f"sell_prices 테이블 생성 실패 (무시): {e}")
# 직전 매도가 복원 (재매수 차단 기준 유지)
try:
loaded = load_sell_prices()
_last_sell_prices.update(loaded)
if loaded:
logger.info(f"[복원] 직전 매도가 {len(loaded)}건 복원: {list(loaded.keys())}")
except Exception as e:
logger.warning(f"직전 매도가 복원 실패 (무시): {e}")
# DB에서 저장된 포지션 로드
try:
saved = {row["ticker"]: row for row in load_positions()}
except Exception as e:
logger.error(f"DB 포지션 로드 실패: {e}")
saved = {}
upbit = _get_upbit()
balances = upbit.get_balances()
upbit_tickers = set()
for b in balances:
currency = b["currency"]
if currency == "KRW":
@@ -57,19 +190,53 @@ def restore_positions() -> None:
invested_krw = int(amount * current)
if invested_krw < 1_000: # 소액 잔고 무시
continue
upbit_tickers.add(ticker)
if ticker in saved:
# DB에 저장된 실제 매수가 복원
s = saved[ticker]
peak = max(s["peak_price"], current) # 재시작 중 올랐을 수 있으므로 높은 쪽
entry_time = datetime.fromisoformat(s["entry_time"]) if isinstance(s["entry_time"], str) else s["entry_time"]
with _lock:
_positions[ticker] = {
"buy_price": current, # 정확한 매수가 불명 → 현재가로 초기화
"buy_price": s["buy_price"],
"peak_price": peak,
"amount": amount,
"invested_krw": s["invested_krw"],
"entry_time": entry_time,
"trade_id": s.get("trade_id", ""),
}
logger.info(
f"[복원] {ticker} 매수가={s['buy_price']:,.0f}원 | 현재가={current:,.0f}"
f"| 수량={amount} (DB 복원)"
)
else:
# DB에 없음 → 현재가로 초기화 후 DB에 저장
entry_time = datetime.now()
with _lock:
_positions[ticker] = {
"buy_price": current,
"peak_price": current,
"amount": amount,
"invested_krw": min(invested_krw, PER_POSITION),
"entry_time": datetime.now(),
"entry_time": entry_time,
}
logger.info(
f"[복원] {ticker} 수량={amount} | 현재가={current:,.0f}"
f"(재시작 시 복원, 매수가 불명으로 현재가 기준)"
_db_upsert(ticker, _positions[ticker])
logger.warning(
f"[복원] {ticker} 현재가={current:,.0f}원 | 수량={amount} "
f"(DB 기록 없음 → 현재가로 초기화)"
)
# Upbit 잔고에 없는데 DB에 남아있는 항목 정리
for ticker in saved:
if ticker not in upbit_tickers:
try:
delete_position(ticker)
logger.info(f"[정리] {ticker} Upbit 잔고 없음 → DB 포지션 삭제")
except Exception as e:
logger.error(f"DB 포지션 삭제 실패 {ticker}: {e}")
def buy(ticker: str) -> bool:
"""시장가 매수. 예산·포지션 수 확인 후 진입."""
@@ -78,6 +245,34 @@ def buy(ticker: str) -> bool:
logger.debug(f"{ticker} 이미 보유 중")
return False
# 직전 매도가 +1% 이상일 때만 재진입 (손절 직후 역방향 재매수 방지)
# 단, 직전 거래가 수익(승)이었으면 이 필터 스킵 — 다시 상승 시 재진입 허용
if ticker in _last_sell_prices:
hist = _get_history(ticker)
last_was_win = bool(hist[-1]) if hist else False
if not last_was_win:
current_check = pyupbit.get_current_price(ticker)
last_sell = _last_sell_prices[ticker]
threshold = last_sell * 1.01
if current_check and current_check < threshold:
logger.info(
f"[재매수 차단] {ticker} 현재={current_check:,.2f} < "
f"직전매도+1%={threshold:,.2f} → 상승 흐름 미확인"
)
return False
# Walk-forward 필터: 직전 WF_WINDOW건 승률이 낮으면 진입 차단
if WF_MIN_WIN_RATE > 0:
hist = _get_history(ticker)
if len(hist) >= WF_WINDOW:
recent_wr = sum(hist[-WF_WINDOW:]) / WF_WINDOW
if recent_wr < WF_MIN_WIN_RATE:
logger.info(
f"[WF차단] {ticker} 직전{WF_WINDOW}건 승률={recent_wr*100:.0f}%"
f" < {WF_MIN_WIN_RATE*100:.0f}% → 진입 차단"
)
return False
if len(_positions) >= MAX_POSITIONS:
logger.info(f"최대 포지션 도달({MAX_POSITIONS}), {ticker} 패스")
return False
@@ -92,7 +287,6 @@ def buy(ticker: str) -> bool:
upbit = _get_upbit()
try:
current = pyupbit.get_current_price(ticker)
result = upbit.buy_market_order(ticker, order_krw)
if not result or "error" in str(result):
logger.error(f"매수 실패: {result}")
@@ -102,18 +296,26 @@ def buy(ticker: str) -> bool:
currency = ticker.split("-")[1]
amount = float(upbit.get_balance(currency) or 0)
# 실제 체결가 = 투자금 / 수량 (시장가 주문 슬리피지 반영)
actual_price = order_krw / amount if amount > 0 else pyupbit.get_current_price(ticker)
entry_time = datetime.now()
trade_id = str(uuid.uuid4())
_positions[ticker] = {
"buy_price": current,
"peak_price": current,
"buy_price": actual_price,
"peak_price": actual_price,
"amount": amount,
"invested_krw": order_krw,
"entry_time": datetime.now(),
"entry_time": entry_time,
"trade_id": trade_id,
}
_db_upsert(ticker, _positions[ticker])
logger.info(
f"[매수] {ticker} @ {current:,.0f}원 | "
f"수량={amount} | 투자금={order_krw:,}"
f"[매수] {ticker} @ {actual_price:,.0f} (실체결가) | "
f"수량={amount} | 투자금={order_krw:,} | trade_id={trade_id[:8]}"
)
notify_buy(ticker, current, amount, order_krw)
notify_buy(ticker, actual_price, amount, order_krw,
max_budget=MAX_BUDGET, per_position=PER_POSITION)
return True
except Exception as e:
logger.error(f"매수 예외 {ticker}: {e}")
@@ -121,6 +323,59 @@ def buy(ticker: str) -> bool:
return False
def _get_avg_fill_price(
upbit: pyupbit.Upbit,
order_uuid: str,
ticker: str,
fallback: float,
) -> tuple[float, float | None]:
"""주문 UUID로 실제 체결 내역을 조회해 가중평균 체결가와 실수수료를 반환.
분할 체결(여러 fills)이면 합산 평균가 계산.
조회 실패 시 (fallback_price, None) 반환.
"""
if not order_uuid:
return fallback, None
try:
import hashlib
import jwt as _jwt
import requests as _req
query_str = f"uuid={order_uuid}"
payload = {
"access_key": upbit.access_key,
"nonce": str(uuid.uuid4()),
"query_hash": hashlib.sha512(query_str.encode()).hexdigest(),
"query_hash_alg": "SHA512",
}
token = _jwt.encode(payload, upbit.secret_key, algorithm="HS256")
resp = _req.get(
"https://api.upbit.com/v1/order",
params={"uuid": order_uuid},
headers={"Authorization": f"Bearer {token}"},
timeout=5,
)
data = resp.json()
trades = data.get("trades", [])
if not trades:
return fallback, None
total_vol = sum(float(t["volume"]) for t in trades)
total_krw = sum(float(t["price"]) * float(t["volume"]) for t in trades)
avg_price = total_krw / total_vol if total_vol > 0 else fallback
paid_fee = float(data.get("paid_fee", 0))
if len(trades) > 1:
logger.info(
f"[분할체결] {ticker} {len(trades)}건 → "
f"평균={avg_price:,.4f}원 (수수료={paid_fee:,.0f}원)"
)
return avg_price, paid_fee
except Exception as e:
logger.debug(f"[체결조회 실패] {ticker} uuid={order_uuid[:8]}: {e}")
return fallback, None
def sell(ticker: str, reason: str = "") -> bool:
"""시장가 전량 매도."""
with _lock:
@@ -130,19 +385,71 @@ def sell(ticker: str, reason: str = "") -> bool:
pos = _positions[ticker]
upbit = _get_upbit()
try:
result = upbit.sell_market_order(ticker, pos["amount"])
currency = ticker.split("-")[1]
# 실제 잔고 확인 (재시작 후 이미 매도된 경우 대비)
actual_amount = float(upbit.get_balance(currency) or 0)
if actual_amount < 0.00001:
logger.warning(f"[매도] {ticker} 실제 잔고 없음 → 포지션 정리 (이미 매도됨)")
del _positions[ticker]
return True
result = upbit.sell_market_order(ticker, actual_amount)
if not result or "error" in str(result):
logger.error(f"매도 실패: {result}")
# 실패 후에도 잔고 재확인 → 0이면 실제로는 매도됨
actual_amount2 = float(upbit.get_balance(currency) or 0)
if actual_amount2 < 0.00001:
logger.warning(f"[매도] {ticker} 잔고 소진 확인 → 포지션 정리")
del _positions[ticker]
return True
return False
current = pyupbit.get_current_price(ticker)
pnl = (current - pos["buy_price"]) / pos["buy_price"] * 100
logger.info(
f"[매도] {ticker} @ {current:,.0f}원 | "
f"수익률={pnl:+.1f}% | 사유={reason}"
time.sleep(0.5) # 체결 완료 대기
# 실제 체결 내역으로 가중평균 매도가 계산 (분할 체결 대응)
order_uuid = result.get("uuid", "") if isinstance(result, dict) else ""
fallback_price = pyupbit.get_current_price(ticker) or pos["buy_price"]
actual_sell_price, actual_fee_from_order = _get_avg_fill_price(
upbit, order_uuid, ticker, fallback_price
)
pnl = (actual_sell_price - pos["buy_price"]) / pos["buy_price"] * 100
sell_value = actual_sell_price * actual_amount
# 수수료: 주문 조회 성공 시 실제값, 아니면 추정값 (0.05% 양방향)
fee = actual_fee_from_order if actual_fee_from_order is not None \
else (pos["invested_krw"] * 0.0005 + sell_value * 0.0005)
krw_profit = sell_value - pos["invested_krw"] - fee
logger.info(
f"[매도] {ticker} @ {actual_sell_price:,.4f}원 | "
f"수익률={pnl:+.1f}% | 순익={krw_profit:+,.0f}원 (수수료 {fee:,.0f}원) | 사유={reason}"
)
try:
cum = get_cumulative_krw_profit() + krw_profit
except Exception:
cum = 0.0
notify_sell(ticker, actual_sell_price, pnl, reason,
krw_profit=krw_profit, fee_krw=fee, cum_profit=cum)
_last_sell_prices[ticker] = actual_sell_price
try:
upsert_sell_price(ticker, actual_sell_price)
except Exception as e:
logger.error(f"직전 매도가 DB 저장 실패 {ticker}: {e}")
_update_history(
ticker, pnl > 0, pnl, fee, krw_profit,
trade_id=pos.get("trade_id", ""),
buy_price=pos["buy_price"],
sell_price=actual_sell_price,
invested_krw=pos["invested_krw"],
sell_reason=reason,
)
notify_sell(ticker, current, pnl, reason)
del _positions[ticker]
try:
delete_position(ticker)
except Exception as e:
logger.error(f"포지션 DB 삭제 실패 {ticker}: {e}")
# 복리 예산 재계산: 수익 발생분만 다음 투자에 반영
_recalc_compound_budget()
return True
except Exception as e:
logger.error(f"매도 예외 {ticker}: {e}")
@@ -156,3 +463,4 @@ def update_peak(ticker: str, current_price: float) -> None:
if ticker in _positions:
if current_price > _positions[ticker]["peak_price"]:
_positions[ticker]["peak_price"] = current_price
_db_upsert(ticker, _positions[ticker])

37
main.py
View File

@@ -19,24 +19,33 @@ logging.basicConfig(
from core.monitor import run_monitor
from core.notify import notify_error, notify_status
from core.price_collector import run_collector
from core.trader import get_positions, restore_positions
from core.price_collector import backfill_prices, run_collector
from core.price_db import get_cumulative_krw_profit
from core.trader import get_positions, get_budget_info, restore_positions
from daemon.runner import run_scanner
STATUS_INTERVAL = 3600 # 1시간마다 요약 전송
def run_status_reporter(interval: int = STATUS_INTERVAL) -> None:
"""주기적으로 포지션 현황을 Telegram으로 전송."""
def run_status_reporter() -> None:
"""매 정각마다 1시간 이상 보유 포지션 현황 전송."""
import datetime as _dt
logger = logging.getLogger("status")
logger.info(f"상태 리포터 시작 (주기={interval//60})")
time.sleep(interval) # 첫 전송은 1시간 후
logger.info("상태 리포터 시작 (매 정각 트리거)")
while True:
now = _dt.datetime.now()
# 다음 정각까지 대기
secs_to_next_hour = (60 - now.minute) * 60 - now.second
time.sleep(secs_to_next_hour)
try:
notify_status(dict(get_positions()))
budget = get_budget_info()
cum = get_cumulative_krw_profit()
notify_status(
dict(get_positions()),
max_budget=budget["max_budget"],
per_position=budget["per_position"],
cum_profit=cum,
)
except Exception as e:
logger.error(f"상태 리포트 오류: {e}")
time.sleep(interval)
def main() -> None:
@@ -45,19 +54,23 @@ def main() -> None:
# 재시작 시 기존 잔고 복원 (이중 매수 방지)
restore_positions()
# 과거 가격 백필 (추세 판단용 DB 데이터가 없는 경우 채움)
logger.info("과거 가격 백필 시작 (48시간)...")
backfill_prices(hours=48)
# 트레일링 스탑 감시 스레드 (10초 주기)
monitor_thread = threading.Thread(
target=run_monitor, args=(10,), daemon=True, name="monitor"
)
monitor_thread.start()
# 1시간 주기 상태 리포트 스레드
# 매 정각 상태 리포트 스레드 (1시간 이상 보유 포지션만)
status_thread = threading.Thread(
target=run_status_reporter, daemon=True, name="status"
)
status_thread.start()
# 10분 주기 가격 수집 스레드 (추세 판단용 DB 저장)
# 가격 수집 스레드 (10분 주기 → Oracle DB price_history 저장, 추세 판단용)
collector_thread = threading.Thread(
target=run_collector, daemon=True, name="collector"
)