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Author SHA1 Message Date
agentson
d6edbc0fa2 feat: use market_outlook to adjust BUY confidence threshold (#173)
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- Import MarketOutlook at module level in main.py
- After scenario evaluation, check market_outlook and apply BUY confidence
  threshold: BEARISH→90, BULLISH→75, others→settings.CONFIDENCE_THRESHOLD
- BUY actions below the adjusted threshold are downgraded to HOLD with
  a descriptive rationale including the outlook and threshold values
- Add 5 integration tests covering bearish suppression, bearish allow,
  bullish allow, bullish suppression, and neutral default threshold

Closes #173

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 08:31:24 +09:00
03f8d220a4 Merge pull request 'fix: use broker balance API as source of truth for SELL qty and holdings (#164 #165)' (#169) from feature/issue-164-165-broker-api-holdings into main
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Reviewed-on: #169
2026-02-20 07:52:26 +09:00
agentson
305120f599 fix: use broker balance API as source of truth for SELL qty and holdings (#164 #165)
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DB의 주문 수량 기록은 실제 체결 수량과 다를 수 있음(부분 체결, 외부 수동 거래).
브로커 잔고 API(output1)를 source of truth로 사용하도록 수정.

## 변경 사항

### SELL 수량 (#164)
- _extract_held_qty_from_balance() 추가
  - 국내: output1의 ord_psbl_qty (→ hldg_qty fallback)
  - 해외: output1의 ovrs_cblc_qty (→ hldg_qty fallback)
- _determine_order_quantity()에 broker_held_qty 파라미터 추가
  - SELL 시 broker_held_qty 반환 (0이면 주문 스킵)
- trading_cycle / run_daily_session 양쪽 호출 지점 수정
  - 이미 fetch된 balance_data에서 수량 추출 (추가 API 호출 없음)

### 보유 종목 루프 (#165)
- _extract_held_codes_from_balance() 추가
  - ord_psbl_qty > 0인 종목 코드 목록 반환
- 실시간 루프에서 스캔 시점에 get_balance() 호출해 보유 종목 병합
  - 스캐너 후보 + 실제 보유 종목 union으로 trading_cycle 순회
  - 실패 시 경고 로그 후 스캐너 후보만으로 계속 진행

### 테스트
- TestExtractHeldQtyFromBalance: 7개 (국내/해외/fallback/미보유)
- TestExtractHeldCodesFromBalance: 4개 (qty>0 포함, qty=0 제외 등)
- TestDetermineOrderQuantity: 5개 (SELL qty, BUY sizing)
- test_sell_order_uses_broker_balance_qty_not_db:
  DB 10주 기록 vs 브로커 5주 확인 → 브로커 값(5) 사용 검증
- 기존 SELL/stop-loss/take-profit 테스트에 output1 mock 추가

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 07:40:45 +09:00
faa23b3f1b Merge pull request 'fix: enforce take_profit_pct in HOLD evaluation loop (#163)' (#166) from feature/issue-163-take-profit-enforcement into main
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Reviewed-on: #166
2026-02-20 07:24:14 +09:00
agentson
5844ec5ad3 fix: enforce take_profit_pct in HOLD evaluation loop (#163)
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HOLD 판정 후 보유 포지션에 대해 stop_loss와 함께 take_profit도 체크하도록 수정.
AI가 생성한 take_profit_pct가 실제 거래 로직에 반영되지 않던 구조적 결함 수정.

- HOLD 블록에서 loss_pct >= take_profit_threshold 조건 추가
- stop_loss와 상호 배타적으로 동작 (stop_loss 우선 체크)
- take_profit 기본값 3.0% (playbook 없는 경우 적용)
- 테스트 2개 추가:
  - test_hold_overridden_to_sell_when_take_profit_triggered
  - test_hold_not_overridden_when_between_stop_loss_and_take_profit

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 03:00:52 +09:00
4 changed files with 908 additions and 127 deletions

View File

@@ -237,28 +237,6 @@ def get_open_position(
return {"decision_id": row[1], "price": row[2], "quantity": row[3]}
def get_open_positions_by_market(
conn: sqlite3.Connection, market: str
) -> list[str]:
"""Return stock codes with a net positive position in the given market.
Uses net BUY - SELL quantity aggregation to avoid false positives from
the simpler "latest record is BUY" heuristic. A stock is considered
open only when the bot's own recorded trades leave a positive net quantity.
"""
cursor = conn.execute(
"""
SELECT stock_code
FROM trades
WHERE market = ?
GROUP BY stock_code
HAVING SUM(CASE WHEN action = 'BUY' THEN quantity ELSE -quantity END) > 0
""",
(market,),
)
return [row[0] for row in cursor.fetchall()]
def get_recent_symbols(
conn: sqlite3.Connection, market: str, limit: int = 30
) -> list[str]:

View File

@@ -32,7 +32,6 @@ from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected, Risk
from src.db import (
get_latest_buy_trade,
get_open_position,
get_open_positions_by_market,
get_recent_symbols,
init_db,
log_trade,
@@ -43,7 +42,7 @@ from src.logging.decision_logger import DecisionLogger
from src.logging_config import setup_logging
from src.markets.schedule import MarketInfo, get_next_market_open, get_open_markets
from src.notifications.telegram_client import NotificationFilter, TelegramClient, TelegramCommandHandler
from src.strategy.models import DayPlaybook
from src.strategy.models import DayPlaybook, MarketOutlook
from src.strategy.playbook_store import PlaybookStore
from src.strategy.pre_market_planner import PreMarketPlanner
from src.strategy.scenario_engine import ScenarioEngine
@@ -107,6 +106,82 @@ def _extract_symbol_from_holding(item: dict[str, Any]) -> str:
return ""
def _extract_held_codes_from_balance(
balance_data: dict[str, Any],
*,
is_domestic: bool,
) -> list[str]:
"""Return stock codes with a positive orderable quantity from a balance response.
Uses the broker's live output1 as the source of truth so that partial fills
and manual external trades are always reflected correctly.
"""
output1 = balance_data.get("output1", [])
if isinstance(output1, dict):
output1 = [output1]
if not isinstance(output1, list):
return []
codes: list[str] = []
for holding in output1:
if not isinstance(holding, dict):
continue
code_key = "pdno" if is_domestic else "ovrs_pdno"
code = str(holding.get(code_key, "")).strip().upper()
if not code:
continue
if is_domestic:
qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
else:
qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
if qty > 0:
codes.append(code)
return codes
def _extract_held_qty_from_balance(
balance_data: dict[str, Any],
stock_code: str,
*,
is_domestic: bool,
) -> int:
"""Extract the broker-confirmed orderable quantity for a stock.
Uses the broker's live balance response (output1) as the source of truth
rather than the local DB, because DB records reflect order quantity which
may differ from actual fill quantity due to partial fills.
Domestic fields (VTTC8434R output1):
pdno — 종목코드
ord_psbl_qty — 주문가능수량 (preferred: excludes unsettled)
hldg_qty — 보유수량 (fallback)
Overseas fields (output1):
ovrs_pdno — 종목코드
ovrs_cblc_qty — 해외잔고수량 (preferred)
hldg_qty — 보유수량 (fallback)
"""
output1 = balance_data.get("output1", [])
if isinstance(output1, dict):
output1 = [output1]
if not isinstance(output1, list):
return 0
for holding in output1:
if not isinstance(holding, dict):
continue
code_key = "pdno" if is_domestic else "ovrs_pdno"
held_code = str(holding.get(code_key, "")).strip().upper()
if held_code != stock_code.strip().upper():
continue
if is_domestic:
qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
else:
qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
return qty
return 0
def _determine_order_quantity(
*,
action: str,
@@ -114,10 +189,11 @@ def _determine_order_quantity(
total_cash: float,
candidate: ScanCandidate | None,
settings: Settings | None,
broker_held_qty: int = 0,
) -> int:
"""Determine order quantity using volatility-aware position sizing."""
if action != "BUY":
return 1
if action == "SELL":
return broker_held_qty
if current_price <= 0 or total_cash <= 0:
return 0
@@ -381,6 +457,34 @@ async def trading_cycle(
)
stock_playbook = playbook.get_stock_playbook(stock_code)
# 2.1. Apply market_outlook-based BUY confidence threshold
if decision.action == "BUY":
base_threshold = (settings.CONFIDENCE_THRESHOLD if settings else 80)
outlook = playbook.market_outlook
if outlook == MarketOutlook.BEARISH:
min_confidence = 90
elif outlook == MarketOutlook.BULLISH:
min_confidence = 75
else:
min_confidence = base_threshold
if match.confidence < min_confidence:
logger.info(
"BUY suppressed for %s (%s): confidence %d < %d (market_outlook=%s)",
stock_code,
market.name,
match.confidence,
min_confidence,
outlook.value,
)
decision = TradeDecision(
action="HOLD",
confidence=match.confidence,
rationale=(
f"BUY confidence {match.confidence} < {min_confidence} "
f"(market_outlook={outlook.value})"
),
)
if decision.action == "HOLD":
open_position = get_open_position(db_conn, stock_code, market.code)
if open_position:
@@ -388,8 +492,10 @@ async def trading_cycle(
if entry_price > 0:
loss_pct = (current_price - entry_price) / entry_price * 100
stop_loss_threshold = -2.0
take_profit_threshold = 3.0
if stock_playbook and stock_playbook.scenarios:
stop_loss_threshold = stock_playbook.scenarios[0].stop_loss_pct
take_profit_threshold = stock_playbook.scenarios[0].take_profit_pct
if loss_pct <= stop_loss_threshold:
decision = TradeDecision(
@@ -407,6 +513,22 @@ async def trading_cycle(
loss_pct,
stop_loss_threshold,
)
elif loss_pct >= take_profit_threshold:
decision = TradeDecision(
action="SELL",
confidence=90,
rationale=(
f"Take-profit triggered ({loss_pct:.2f}% >= "
f"{take_profit_threshold:.2f}%)"
),
)
logger.info(
"Take-profit override for %s (%s): %.2f%% >= %.2f%%",
stock_code,
market.name,
loss_pct,
take_profit_threshold,
)
logger.info(
"Decision for %s (%s): %s (confidence=%d)",
stock_code,
@@ -467,12 +589,20 @@ async def trading_cycle(
trade_price = current_price
trade_pnl = 0.0
if decision.action in ("BUY", "SELL"):
broker_held_qty = (
_extract_held_qty_from_balance(
balance_data, stock_code, is_domestic=market.is_domestic
)
if decision.action == "SELL"
else 0
)
quantity = _determine_order_quantity(
action=decision.action,
current_price=current_price,
total_cash=total_cash,
candidate=candidate,
settings=settings,
broker_held_qty=broker_held_qty,
)
if quantity <= 0:
logger.info(
@@ -892,12 +1022,20 @@ async def run_daily_session(
trade_pnl = 0.0
order_succeeded = True
if decision.action in ("BUY", "SELL"):
daily_broker_held_qty = (
_extract_held_qty_from_balance(
balance_data, stock_code, is_domestic=market.is_domestic
)
if decision.action == "SELL"
else 0
)
quantity = _determine_order_quantity(
action=decision.action,
current_price=stock_data["current_price"],
total_cash=total_cash,
candidate=candidate_map.get(stock_code),
settings=settings,
broker_held_qty=daily_broker_held_qty,
)
if quantity <= 0:
logger.info(
@@ -1864,22 +2002,38 @@ async def run(settings: Settings) -> None:
except Exception as exc:
logger.error("Smart Scanner failed for %s: %s", market.name, exc)
# Get active stocks from scanner (dynamic, no static fallback)
# Also include current holdings so stop-loss / take-profit
# can trigger even when a position drops off the scanner.
# Get active stocks from scanner (dynamic, no static fallback).
# Also include currently-held positions so stop-loss /
# take-profit can fire even when a holding drops off the
# scanner. Broker balance is the source of truth here —
# unlike the local DB it reflects actual fills and any
# manual trades done outside the bot.
scanner_codes = active_stocks.get(market.code, [])
held_codes = get_open_positions_by_market(db_conn, market.code)
# Union: scanner candidates first, then holdings not already present.
# dict.fromkeys preserves insertion order and removes duplicates.
stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
if held_codes:
new_held = [c for c in held_codes if c not in set(scanner_codes)]
if new_held:
logger.info(
"Holdings added to loop for %s (not in scanner): %s",
market.name,
new_held,
try:
if market.is_domestic:
held_balance = await broker.get_balance()
else:
held_balance = await overseas_broker.get_overseas_balance(
market.exchange_code
)
held_codes = _extract_held_codes_from_balance(
held_balance, is_domestic=market.is_domestic
)
except Exception as exc:
logger.warning(
"Failed to fetch holdings for %s: %s — skipping holdings merge",
market.name, exc,
)
held_codes = []
stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
extra_held = [c for c in held_codes if c not in set(scanner_codes)]
if extra_held:
logger.info(
"Holdings added to loop for %s (not in scanner): %s",
market.name, extra_held,
)
if not stock_codes:
logger.debug("No active stocks for market %s", market.code)
continue

View File

@@ -1,6 +1,6 @@
"""Tests for database helper functions."""
from src.db import get_open_position, get_open_positions_by_market, init_db, log_trade
from src.db import get_open_position, init_db, log_trade
def test_get_open_position_returns_latest_buy() -> None:
@@ -58,87 +58,3 @@ def test_get_open_position_returns_none_when_latest_is_sell() -> None:
def test_get_open_position_returns_none_when_no_trades() -> None:
conn = init_db(":memory:")
assert get_open_position(conn, "AAPL", "US_NASDAQ") is None
# --- get_open_positions_by_market tests ---
def test_get_open_positions_by_market_returns_net_positive_stocks() -> None:
"""Stocks with net BUY quantity > 0 are included."""
conn = init_db(":memory:")
log_trade(
conn=conn, stock_code="005930", action="BUY", confidence=90,
rationale="entry", quantity=5, price=70000.0, market="KR",
exchange_code="KRX", decision_id="d1",
)
log_trade(
conn=conn, stock_code="000660", action="BUY", confidence=85,
rationale="entry", quantity=3, price=100000.0, market="KR",
exchange_code="KRX", decision_id="d2",
)
result = get_open_positions_by_market(conn, "KR")
assert set(result) == {"005930", "000660"}
def test_get_open_positions_by_market_excludes_fully_sold_stocks() -> None:
"""Stocks where BUY qty == SELL qty are excluded (net qty = 0)."""
conn = init_db(":memory:")
log_trade(
conn=conn, stock_code="005930", action="BUY", confidence=90,
rationale="entry", quantity=3, price=70000.0, market="KR",
exchange_code="KRX", decision_id="d1",
)
log_trade(
conn=conn, stock_code="005930", action="SELL", confidence=95,
rationale="exit", quantity=3, price=71000.0, market="KR",
exchange_code="KRX", decision_id="d2",
)
result = get_open_positions_by_market(conn, "KR")
assert "005930" not in result
def test_get_open_positions_by_market_includes_partially_sold_stocks() -> None:
"""Stocks with partial SELL (net qty > 0) are still included."""
conn = init_db(":memory:")
log_trade(
conn=conn, stock_code="005930", action="BUY", confidence=90,
rationale="entry", quantity=5, price=70000.0, market="KR",
exchange_code="KRX", decision_id="d1",
)
log_trade(
conn=conn, stock_code="005930", action="SELL", confidence=95,
rationale="partial exit", quantity=2, price=71000.0, market="KR",
exchange_code="KRX", decision_id="d2",
)
result = get_open_positions_by_market(conn, "KR")
assert "005930" in result
def test_get_open_positions_by_market_is_market_scoped() -> None:
"""Only stocks from the specified market are returned."""
conn = init_db(":memory:")
log_trade(
conn=conn, stock_code="005930", action="BUY", confidence=90,
rationale="entry", quantity=3, price=70000.0, market="KR",
exchange_code="KRX", decision_id="d1",
)
log_trade(
conn=conn, stock_code="AAPL", action="BUY", confidence=85,
rationale="entry", quantity=2, price=200.0, market="NASD",
exchange_code="NAS", decision_id="d2",
)
kr_result = get_open_positions_by_market(conn, "KR")
nasd_result = get_open_positions_by_market(conn, "NASD")
assert kr_result == ["005930"]
assert nasd_result == ["AAPL"]
def test_get_open_positions_by_market_returns_empty_when_no_trades() -> None:
"""Empty list returned when no trades exist for the market."""
conn = init_db(":memory:")
assert get_open_positions_by_market(conn, "KR") == []

View File

@@ -14,6 +14,9 @@ from src.evolution.scorecard import DailyScorecard
from src.logging.decision_logger import DecisionLogger
from src.main import (
_apply_dashboard_flag,
_determine_order_quantity,
_extract_held_codes_from_balance,
_extract_held_qty_from_balance,
_handle_market_close,
_run_context_scheduler,
_run_evolution_loop,
@@ -68,6 +71,141 @@ def _make_sell_match(stock_code: str = "005930") -> ScenarioMatch:
)
class TestExtractHeldQtyFromBalance:
"""Tests for _extract_held_qty_from_balance()."""
def _domestic_balance(self, stock_code: str, ord_psbl_qty: int) -> dict:
return {
"output1": [{"pdno": stock_code, "ord_psbl_qty": str(ord_psbl_qty)}],
"output2": [{"dnca_tot_amt": "1000000"}],
}
def test_domestic_returns_ord_psbl_qty(self) -> None:
balance = self._domestic_balance("005930", 7)
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 7
def test_domestic_fallback_to_hldg_qty(self) -> None:
balance = {"output1": [{"pdno": "005930", "hldg_qty": "3"}]}
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 3
def test_domestic_returns_zero_when_not_found(self) -> None:
balance = self._domestic_balance("005930", 5)
assert _extract_held_qty_from_balance(balance, "000660", is_domestic=True) == 0
def test_domestic_returns_zero_when_output1_empty(self) -> None:
balance = {"output1": [], "output2": [{}]}
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 0
def test_overseas_returns_ovrs_cblc_qty(self) -> None:
balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "10"}]}
assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 10
def test_overseas_fallback_to_hldg_qty(self) -> None:
balance = {"output1": [{"ovrs_pdno": "AAPL", "hldg_qty": "4"}]}
assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 4
def test_case_insensitive_match(self) -> None:
balance = {"output1": [{"pdno": "005930", "ord_psbl_qty": "2"}]}
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 2
class TestExtractHeldCodesFromBalance:
"""Tests for _extract_held_codes_from_balance()."""
def test_returns_codes_with_positive_qty(self) -> None:
balance = {
"output1": [
{"pdno": "005930", "ord_psbl_qty": "5"},
{"pdno": "000660", "ord_psbl_qty": "3"},
]
}
result = _extract_held_codes_from_balance(balance, is_domestic=True)
assert set(result) == {"005930", "000660"}
def test_excludes_zero_qty_holdings(self) -> None:
balance = {
"output1": [
{"pdno": "005930", "ord_psbl_qty": "0"},
{"pdno": "000660", "ord_psbl_qty": "2"},
]
}
result = _extract_held_codes_from_balance(balance, is_domestic=True)
assert "005930" not in result
assert "000660" in result
def test_returns_empty_when_output1_missing(self) -> None:
balance: dict = {}
assert _extract_held_codes_from_balance(balance, is_domestic=True) == []
def test_overseas_uses_ovrs_pdno(self) -> None:
balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "3"}]}
result = _extract_held_codes_from_balance(balance, is_domestic=False)
assert result == ["AAPL"]
class TestDetermineOrderQuantity:
"""Test _determine_order_quantity() — SELL uses broker_held_qty."""
def test_sell_returns_broker_held_qty(self) -> None:
result = _determine_order_quantity(
action="SELL",
current_price=105.0,
total_cash=50000.0,
candidate=None,
settings=None,
broker_held_qty=7,
)
assert result == 7
def test_sell_returns_zero_when_broker_qty_zero(self) -> None:
result = _determine_order_quantity(
action="SELL",
current_price=105.0,
total_cash=50000.0,
candidate=None,
settings=None,
broker_held_qty=0,
)
assert result == 0
def test_buy_without_position_sizing_returns_one(self) -> None:
result = _determine_order_quantity(
action="BUY",
current_price=50000.0,
total_cash=1000000.0,
candidate=None,
settings=None,
)
assert result == 1
def test_buy_with_zero_cash_returns_zero(self) -> None:
result = _determine_order_quantity(
action="BUY",
current_price=50000.0,
total_cash=0.0,
candidate=None,
settings=None,
)
assert result == 0
def test_buy_with_position_sizing_calculates_correctly(self) -> None:
settings = MagicMock(spec=Settings)
settings.POSITION_SIZING_ENABLED = True
settings.POSITION_VOLATILITY_TARGET_SCORE = 50.0
settings.POSITION_BASE_ALLOCATION_PCT = 10.0
settings.POSITION_MAX_ALLOCATION_PCT = 30.0
settings.POSITION_MIN_ALLOCATION_PCT = 1.0
# 1,000,000 * 10% = 100,000 budget // 50,000 price = 2 shares
result = _determine_order_quantity(
action="BUY",
current_price=50000.0,
total_cash=1000000.0,
candidate=None,
settings=settings,
)
assert result == 2
class TestSafeFloat:
"""Test safe_float() helper function."""
@@ -1240,13 +1378,14 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
broker.get_current_price = AsyncMock(return_value=(120.0, 0.0, 0.0))
broker.get_balance = AsyncMock(
return_value={
"output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
"output2": [
{
"tot_evlu_amt": "100000",
"dnca_tot_amt": "10000",
"pchs_amt_smtl_amt": "90000",
}
]
],
}
)
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
@@ -1330,13 +1469,14 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
broker.get_balance = AsyncMock(
return_value={
"output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
"output2": [
{
"tot_evlu_amt": "100000",
"dnca_tot_amt": "10000",
"pchs_amt_smtl_amt": "90000",
}
]
],
}
)
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
@@ -1396,6 +1536,318 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
@pytest.mark.asyncio
async def test_hold_overridden_to_sell_when_take_profit_triggered() -> None:
"""HOLD decision should be overridden to SELL when take-profit threshold is reached."""
db_conn = init_db(":memory:")
decision_logger = DecisionLogger(db_conn)
buy_decision_id = decision_logger.log_decision(
stock_code="005930",
market="KR",
exchange_code="KRX",
action="BUY",
confidence=90,
rationale="entry",
context_snapshot={},
input_data={},
)
log_trade(
conn=db_conn,
stock_code="005930",
action="BUY",
confidence=90,
rationale="entry",
quantity=1,
price=100.0,
market="KR",
exchange_code="KRX",
decision_id=buy_decision_id,
)
broker = MagicMock()
# Current price 106.0 → +6% gain, above take_profit_pct=3.0
broker.get_current_price = AsyncMock(return_value=(106.0, 6.0, 0.0))
broker.get_balance = AsyncMock(
return_value={
"output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
"output2": [
{
"tot_evlu_amt": "100000",
"dnca_tot_amt": "10000",
"pchs_amt_smtl_amt": "90000",
}
],
}
)
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
scenario = StockScenario(
condition=StockCondition(rsi_below=30),
action=ScenarioAction.BUY,
confidence=88,
stop_loss_pct=-2.0,
take_profit_pct=3.0,
rationale="take profit policy",
)
playbook = DayPlaybook(
date=date(2026, 2, 8),
market="KR",
stock_playbooks=[
{"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
],
)
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=_make_hold_match())
market = MagicMock()
market.name = "Korea"
market.code = "KR"
market.exchange_code = "KRX"
market.is_domestic = True
telegram = MagicMock()
telegram.notify_trade_execution = AsyncMock()
telegram.notify_fat_finger = AsyncMock()
telegram.notify_circuit_breaker = AsyncMock()
telegram.notify_scenario_matched = AsyncMock()
await trading_cycle(
broker=broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=MagicMock(),
db_conn=db_conn,
decision_logger=decision_logger,
context_store=MagicMock(
get_latest_timeframe=MagicMock(return_value=None),
set_context=MagicMock(),
),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=telegram,
market=market,
stock_code="005930",
scan_candidates={},
)
broker.send_order.assert_called_once()
assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
@pytest.mark.asyncio
async def test_hold_not_overridden_when_between_stop_loss_and_take_profit() -> None:
"""HOLD should remain HOLD when P&L is within stop-loss and take-profit bounds."""
db_conn = init_db(":memory:")
decision_logger = DecisionLogger(db_conn)
buy_decision_id = decision_logger.log_decision(
stock_code="005930",
market="KR",
exchange_code="KRX",
action="BUY",
confidence=90,
rationale="entry",
context_snapshot={},
input_data={},
)
log_trade(
conn=db_conn,
stock_code="005930",
action="BUY",
confidence=90,
rationale="entry",
quantity=1,
price=100.0,
market="KR",
exchange_code="KRX",
decision_id=buy_decision_id,
)
broker = MagicMock()
# Current price 101.0 → +1% gain, within [-2%, +3%] range
broker.get_current_price = AsyncMock(return_value=(101.0, 1.0, 0.0))
broker.get_balance = AsyncMock(
return_value={
"output2": [
{
"tot_evlu_amt": "100000",
"dnca_tot_amt": "10000",
"pchs_amt_smtl_amt": "90000",
}
]
}
)
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
scenario = StockScenario(
condition=StockCondition(rsi_below=30),
action=ScenarioAction.BUY,
confidence=88,
stop_loss_pct=-2.0,
take_profit_pct=3.0,
rationale="within range policy",
)
playbook = DayPlaybook(
date=date(2026, 2, 8),
market="KR",
stock_playbooks=[
{"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
],
)
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=_make_hold_match())
market = MagicMock()
market.name = "Korea"
market.code = "KR"
market.exchange_code = "KRX"
market.is_domestic = True
telegram = MagicMock()
telegram.notify_trade_execution = AsyncMock()
telegram.notify_fat_finger = AsyncMock()
telegram.notify_circuit_breaker = AsyncMock()
telegram.notify_scenario_matched = AsyncMock()
await trading_cycle(
broker=broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=MagicMock(),
db_conn=db_conn,
decision_logger=decision_logger,
context_store=MagicMock(
get_latest_timeframe=MagicMock(return_value=None),
set_context=MagicMock(),
),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=telegram,
market=market,
stock_code="005930",
scan_candidates={},
)
broker.send_order.assert_not_called()
@pytest.mark.asyncio
async def test_sell_order_uses_broker_balance_qty_not_db() -> None:
"""SELL quantity must come from broker balance output1, not DB.
The DB records order quantity which may differ from actual fill quantity.
This test verifies that we use the broker-confirmed orderable quantity.
"""
db_conn = init_db(":memory:")
decision_logger = DecisionLogger(db_conn)
buy_decision_id = decision_logger.log_decision(
stock_code="005930",
market="KR",
exchange_code="KRX",
action="BUY",
confidence=90,
rationale="entry",
context_snapshot={},
input_data={},
)
# DB records 10 shares ordered — but only 5 actually filled (partial fill scenario)
log_trade(
conn=db_conn,
stock_code="005930",
action="BUY",
confidence=90,
rationale="entry",
quantity=10, # ordered quantity (may differ from fill)
price=100.0,
market="KR",
exchange_code="KRX",
decision_id=buy_decision_id,
)
broker = MagicMock()
# Stop-loss triggers (price dropped below -2%)
broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
broker.get_balance = AsyncMock(
return_value={
# Broker confirms only 5 shares are actually orderable (partial fill)
"output1": [{"pdno": "005930", "ord_psbl_qty": "5"}],
"output2": [
{
"tot_evlu_amt": "100000",
"dnca_tot_amt": "10000",
"pchs_amt_smtl_amt": "90000",
}
],
}
)
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
scenario = StockScenario(
condition=StockCondition(rsi_below=30),
action=ScenarioAction.BUY,
confidence=88,
stop_loss_pct=-2.0,
rationale="stop loss policy",
)
playbook = DayPlaybook(
date=date(2026, 2, 8),
market="KR",
stock_playbooks=[
{"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
],
)
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=_make_hold_match())
market = MagicMock()
market.name = "Korea"
market.code = "KR"
market.exchange_code = "KRX"
market.is_domestic = True
telegram = MagicMock()
telegram.notify_trade_execution = AsyncMock()
telegram.notify_fat_finger = AsyncMock()
telegram.notify_circuit_breaker = AsyncMock()
telegram.notify_scenario_matched = AsyncMock()
await trading_cycle(
broker=broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=MagicMock(),
db_conn=db_conn,
decision_logger=decision_logger,
context_store=MagicMock(
get_latest_timeframe=MagicMock(return_value=None),
set_context=MagicMock(),
),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=telegram,
market=market,
stock_code="005930",
scan_candidates={},
)
broker.send_order.assert_called_once()
call_kwargs = broker.send_order.call_args.kwargs
assert call_kwargs["order_type"] == "SELL"
# Must use broker-confirmed qty (5), NOT DB-recorded ordered qty (10)
assert call_kwargs["quantity"] == 5
@pytest.mark.asyncio
async def test_handle_market_close_runs_daily_review_flow() -> None:
"""Market close should aggregate, create scorecard, lessons, and notify."""
@@ -1662,3 +2114,284 @@ def test_start_dashboard_server_enabled_starts_thread() -> None:
assert thread == mock_thread
mock_thread_cls.assert_called_once()
mock_thread.start.assert_called_once()
# ---------------------------------------------------------------------------
# market_outlook BUY confidence threshold tests (#173)
# ---------------------------------------------------------------------------
class TestMarketOutlookConfidenceThreshold:
"""Tests for market_outlook-based BUY confidence suppression in trading_cycle."""
@pytest.fixture
def mock_broker(self) -> MagicMock:
broker = MagicMock()
broker.get_current_price = AsyncMock(return_value=(50000.0, 1.0, 0.0))
broker.get_balance = AsyncMock(
return_value={
"output2": [
{
"tot_evlu_amt": "10000000",
"dnca_tot_amt": "5000000",
"pchs_amt_smtl_amt": "9500000",
}
]
}
)
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
return broker
@pytest.fixture
def mock_market(self) -> MagicMock:
market = MagicMock()
market.name = "Korea"
market.code = "KR"
market.exchange_code = "KRX"
market.is_domestic = True
return market
@pytest.fixture
def mock_telegram(self) -> MagicMock:
telegram = MagicMock()
telegram.notify_trade_execution = AsyncMock()
telegram.notify_scenario_matched = AsyncMock()
telegram.notify_fat_finger = AsyncMock()
return telegram
def _make_buy_match_with_confidence(
self, confidence: int, stock_code: str = "005930"
) -> ScenarioMatch:
from src.strategy.models import StockScenario
scenario = StockScenario(
condition=StockCondition(rsi_below=30),
action=ScenarioAction.BUY,
confidence=confidence,
allocation_pct=10.0,
)
return ScenarioMatch(
stock_code=stock_code,
matched_scenario=scenario,
action=ScenarioAction.BUY,
confidence=confidence,
rationale="Test buy",
)
def _make_playbook_with_outlook(
self, outlook_str: str, market: str = "KR"
) -> DayPlaybook:
from src.strategy.models import MarketOutlook
outlook_map = {
"bearish": MarketOutlook.BEARISH,
"bullish": MarketOutlook.BULLISH,
"neutral": MarketOutlook.NEUTRAL,
"neutral_to_bullish": MarketOutlook.NEUTRAL_TO_BULLISH,
"neutral_to_bearish": MarketOutlook.NEUTRAL_TO_BEARISH,
}
return DayPlaybook(
date=date(2026, 2, 20),
market=market,
market_outlook=outlook_map[outlook_str],
)
@pytest.mark.asyncio
async def test_bearish_outlook_raises_buy_confidence_threshold(
self,
mock_broker: MagicMock,
mock_market: MagicMock,
mock_telegram: MagicMock,
) -> None:
"""BUY with confidence 85 should be suppressed to HOLD in bearish market."""
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(85))
playbook = self._make_playbook_with_outlook("bearish")
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="decision-id")
with patch("src.main.log_trade"):
await trading_cycle(
broker=mock_broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=MagicMock(),
db_conn=MagicMock(),
decision_logger=decision_logger,
context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
# HOLD should be logged (not BUY) — check decision_logger was called with HOLD
call_args = decision_logger.log_decision.call_args
assert call_args is not None
assert call_args.kwargs["action"] == "HOLD"
@pytest.mark.asyncio
async def test_bearish_outlook_allows_high_confidence_buy(
self,
mock_broker: MagicMock,
mock_market: MagicMock,
mock_telegram: MagicMock,
) -> None:
"""BUY with confidence 92 should proceed in bearish market (threshold=90)."""
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(92))
playbook = self._make_playbook_with_outlook("bearish")
risk = MagicMock()
risk.validate_order = MagicMock()
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="decision-id")
with patch("src.main.log_trade"):
await trading_cycle(
broker=mock_broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=risk,
db_conn=MagicMock(),
decision_logger=decision_logger,
context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
call_args = decision_logger.log_decision.call_args
assert call_args is not None
assert call_args.kwargs["action"] == "BUY"
@pytest.mark.asyncio
async def test_bullish_outlook_lowers_buy_confidence_threshold(
self,
mock_broker: MagicMock,
mock_market: MagicMock,
mock_telegram: MagicMock,
) -> None:
"""BUY with confidence 77 should proceed in bullish market (threshold=75)."""
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(77))
playbook = self._make_playbook_with_outlook("bullish")
risk = MagicMock()
risk.validate_order = MagicMock()
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="decision-id")
with patch("src.main.log_trade"):
await trading_cycle(
broker=mock_broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=risk,
db_conn=MagicMock(),
decision_logger=decision_logger,
context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
call_args = decision_logger.log_decision.call_args
assert call_args is not None
assert call_args.kwargs["action"] == "BUY"
@pytest.mark.asyncio
async def test_bullish_outlook_suppresses_very_low_confidence_buy(
self,
mock_broker: MagicMock,
mock_market: MagicMock,
mock_telegram: MagicMock,
) -> None:
"""BUY with confidence 70 should be suppressed even in bullish market (threshold=75)."""
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(70))
playbook = self._make_playbook_with_outlook("bullish")
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="decision-id")
with patch("src.main.log_trade"):
await trading_cycle(
broker=mock_broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=MagicMock(),
db_conn=MagicMock(),
decision_logger=decision_logger,
context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
call_args = decision_logger.log_decision.call_args
assert call_args is not None
assert call_args.kwargs["action"] == "HOLD"
@pytest.mark.asyncio
async def test_neutral_outlook_uses_default_threshold(
self,
mock_broker: MagicMock,
mock_market: MagicMock,
mock_telegram: MagicMock,
) -> None:
"""BUY with confidence 82 should proceed in neutral market (default=80)."""
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(82))
playbook = self._make_playbook_with_outlook("neutral")
risk = MagicMock()
risk.validate_order = MagicMock()
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="decision-id")
with patch("src.main.log_trade"):
await trading_cycle(
broker=mock_broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=playbook,
risk=risk,
db_conn=MagicMock(),
decision_logger=decision_logger,
context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
criticality_assessor=MagicMock(
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
get_timeout=MagicMock(return_value=5.0),
),
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
call_args = decision_logger.log_decision.call_args
assert call_args is not None
assert call_args.kwargs["action"] == "BUY"