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12 Commits

Author SHA1 Message Date
agentson
694d73b212 fix: lazy session resolver and one-time session_id backfill 2026-02-27 08:51:00 +09:00
agentson
b2b02b6f57 feat: enforce session_id persistence in trade ledger (TASK-CODE-007) 2026-02-27 08:49:04 +09:00
2dbe98615d Merge pull request '[FX-ACCOUNTING] TKT-P1-006 전략/환율 PnL 분리 회계' (#296) from feature/issue-tkt-p1-006-fx-pnl-separation into feature/v3-session-policy-stream 2026-02-27 08:46:56 +09:00
agentson
34cf081c96 fix: backfill split pnl migration and harden partial pnl inputs 2026-02-27 08:46:22 +09:00
agentson
7bc4e88335 feat: separate strategy and fx pnl fields in trade logs (TASK-CODE-011) 2026-02-27 08:44:05 +09:00
386e039ff6 Merge pull request '[BACKTEST-MODEL] TKT-P1-005 보수적 체결 모델 구현' (#294) from feature/issue-tkt-p1-005-conservative-fill-model into feature/v3-session-policy-stream 2026-02-27 08:42:22 +09:00
agentson
13ba9e8081 fix: validate execution assumption ranges in backtest model 2026-02-27 08:41:56 +09:00
agentson
5b52f593a8 feat: add conservative backtest execution simulator (TASK-CODE-010) 2026-02-27 08:40:23 +09:00
2798558bf3 Merge pull request '[BACKTEST-MODEL] TKT-P1-002 백테스트 비용/슬리피지 옵션 필수화' (#292) from feature/issue-tkt-p1-002-backtest-cost-mandatory into feature/v3-session-policy-stream 2026-02-27 08:37:15 +09:00
agentson
2331d80915 fix: reject non-finite backtest cost assumptions 2026-02-27 08:36:38 +09:00
agentson
7d72669cb8 feat: enforce mandatory backtest cost assumptions (TASK-CODE-006) 2026-02-27 08:34:44 +09:00
74a4784b7a Merge pull request '[BACKTEST-MODEL] TKT-P1-004 Walk-forward + Purge/Embargo 분할 유틸' (#290) from feature/issue-tkt-p1-004-walkforward-purge-embargo into feature/v3-session-policy-stream 2026-02-27 08:33:01 +09:00
6 changed files with 550 additions and 4 deletions

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@@ -0,0 +1,52 @@
"""Backtest cost/slippage/failure validation guard."""
from __future__ import annotations
from dataclasses import dataclass
import math
@dataclass(frozen=True)
class BacktestCostModel:
commission_bps: float | None = None
slippage_bps_by_session: dict[str, float] | None = None
failure_rate_by_session: dict[str, float] | None = None
unfavorable_fill_required: bool = True
def validate_backtest_cost_model(
*,
model: BacktestCostModel,
required_sessions: list[str],
) -> None:
"""Raise ValueError when required cost assumptions are missing/invalid."""
if (
model.commission_bps is None
or not math.isfinite(model.commission_bps)
or model.commission_bps < 0
):
raise ValueError("commission_bps must be provided and >= 0")
if not model.unfavorable_fill_required:
raise ValueError("unfavorable_fill_required must be True")
slippage = model.slippage_bps_by_session or {}
failure = model.failure_rate_by_session or {}
missing_slippage = [s for s in required_sessions if s not in slippage]
if missing_slippage:
raise ValueError(
f"missing slippage_bps_by_session for sessions: {', '.join(missing_slippage)}"
)
missing_failure = [s for s in required_sessions if s not in failure]
if missing_failure:
raise ValueError(
f"missing failure_rate_by_session for sessions: {', '.join(missing_failure)}"
)
for sess, bps in slippage.items():
if not math.isfinite(bps) or bps < 0:
raise ValueError(f"slippage bps must be >= 0 for session={sess}")
for sess, rate in failure.items():
if not math.isfinite(rate) or rate < 0 or rate > 1:
raise ValueError(f"failure rate must be within [0,1] for session={sess}")

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@@ -0,0 +1,103 @@
"""Conservative backtest execution model."""
from __future__ import annotations
from dataclasses import dataclass
import math
from random import Random
from typing import Literal
OrderSide = Literal["BUY", "SELL"]
@dataclass(frozen=True)
class ExecutionRequest:
side: OrderSide
session_id: str
qty: int
reference_price: float
@dataclass(frozen=True)
class ExecutionAssumptions:
slippage_bps_by_session: dict[str, float]
failure_rate_by_session: dict[str, float]
partial_fill_rate_by_session: dict[str, float]
partial_fill_min_ratio: float = 0.3
partial_fill_max_ratio: float = 0.8
seed: int = 0
@dataclass(frozen=True)
class ExecutionResult:
status: Literal["FILLED", "PARTIAL", "REJECTED"]
filled_qty: int
avg_price: float
slippage_bps: float
reason: str
class BacktestExecutionModel:
"""Execution simulator with conservative unfavorable fill assumptions."""
def __init__(self, assumptions: ExecutionAssumptions) -> None:
self.assumptions = assumptions
self._rng = Random(assumptions.seed)
if assumptions.partial_fill_min_ratio <= 0 or assumptions.partial_fill_max_ratio > 1:
raise ValueError("partial fill ratios must be within (0,1]")
if assumptions.partial_fill_min_ratio > assumptions.partial_fill_max_ratio:
raise ValueError("partial_fill_min_ratio must be <= partial_fill_max_ratio")
for sess, bps in assumptions.slippage_bps_by_session.items():
if not math.isfinite(bps) or bps < 0:
raise ValueError(f"slippage_bps must be finite and >= 0 for session={sess}")
for sess, rate in assumptions.failure_rate_by_session.items():
if not math.isfinite(rate) or rate < 0 or rate > 1:
raise ValueError(f"failure_rate must be in [0,1] for session={sess}")
for sess, rate in assumptions.partial_fill_rate_by_session.items():
if not math.isfinite(rate) or rate < 0 or rate > 1:
raise ValueError(f"partial_fill_rate must be in [0,1] for session={sess}")
def simulate(self, request: ExecutionRequest) -> ExecutionResult:
if request.qty <= 0:
raise ValueError("qty must be positive")
if request.reference_price <= 0:
raise ValueError("reference_price must be positive")
slippage_bps = self.assumptions.slippage_bps_by_session.get(request.session_id, 0.0)
failure_rate = self.assumptions.failure_rate_by_session.get(request.session_id, 0.0)
partial_rate = self.assumptions.partial_fill_rate_by_session.get(request.session_id, 0.0)
if self._rng.random() < failure_rate:
return ExecutionResult(
status="REJECTED",
filled_qty=0,
avg_price=0.0,
slippage_bps=slippage_bps,
reason="execution_failure",
)
slip_mult = 1.0 + (slippage_bps / 10000.0 if request.side == "BUY" else -slippage_bps / 10000.0)
exec_price = request.reference_price * slip_mult
if self._rng.random() < partial_rate:
ratio = self._rng.uniform(
self.assumptions.partial_fill_min_ratio,
self.assumptions.partial_fill_max_ratio,
)
filled = max(1, min(request.qty - 1, int(request.qty * ratio)))
return ExecutionResult(
status="PARTIAL",
filled_qty=filled,
avg_price=exec_price,
slippage_bps=slippage_bps,
reason="partial_fill",
)
return ExecutionResult(
status="FILLED",
filled_qty=request.qty,
avg_price=exec_price,
slippage_bps=slippage_bps,
reason="filled",
)

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@@ -31,8 +31,12 @@ def init_db(db_path: str) -> sqlite3.Connection:
quantity INTEGER,
price REAL,
pnl REAL DEFAULT 0.0,
strategy_pnl REAL DEFAULT 0.0,
fx_pnl REAL DEFAULT 0.0,
market TEXT DEFAULT 'KR',
exchange_code TEXT DEFAULT 'KRX',
session_id TEXT DEFAULT 'UNKNOWN',
selection_context TEXT,
decision_id TEXT,
mode TEXT DEFAULT 'paper'
)
@@ -53,6 +57,32 @@ def init_db(db_path: str) -> sqlite3.Connection:
conn.execute("ALTER TABLE trades ADD COLUMN decision_id TEXT")
if "mode" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN mode TEXT DEFAULT 'paper'")
session_id_added = False
if "session_id" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN session_id TEXT DEFAULT 'UNKNOWN'")
session_id_added = True
if "strategy_pnl" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN strategy_pnl REAL DEFAULT 0.0")
if "fx_pnl" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN fx_pnl REAL DEFAULT 0.0")
# Backfill legacy rows where only pnl existed before split accounting columns.
conn.execute(
"""
UPDATE trades
SET strategy_pnl = pnl, fx_pnl = 0.0
WHERE pnl != 0.0
AND strategy_pnl = 0.0
AND fx_pnl = 0.0
"""
)
if session_id_added:
conn.execute(
"""
UPDATE trades
SET session_id = 'UNKNOWN'
WHERE session_id IS NULL OR session_id = ''
"""
)
# Context tree tables for multi-layered memory management
conn.execute(
@@ -171,8 +201,11 @@ def log_trade(
quantity: int = 0,
price: float = 0.0,
pnl: float = 0.0,
strategy_pnl: float | None = None,
fx_pnl: float | None = None,
market: str = "KR",
exchange_code: str = "KRX",
session_id: str | None = None,
selection_context: dict[str, any] | None = None,
decision_id: str | None = None,
mode: str = "paper",
@@ -187,24 +220,37 @@ def log_trade(
rationale: AI decision rationale
quantity: Number of shares
price: Trade price
pnl: Profit/loss
pnl: Total profit/loss (backward compatibility)
strategy_pnl: Strategy PnL component
fx_pnl: FX PnL component
market: Market code
exchange_code: Exchange code
session_id: Session identifier (if omitted, auto-derived from market)
selection_context: Scanner selection data (RSI, volume_ratio, signal, score)
decision_id: Unique decision identifier for audit linking
mode: Trading mode ('paper' or 'live') for data separation
"""
# Serialize selection context to JSON
context_json = json.dumps(selection_context) if selection_context else None
resolved_session_id = _resolve_session_id(market=market, session_id=session_id)
if strategy_pnl is None and fx_pnl is None:
strategy_pnl = pnl
fx_pnl = 0.0
elif strategy_pnl is None:
strategy_pnl = pnl - float(fx_pnl or 0.0) if pnl != 0.0 else 0.0
elif fx_pnl is None:
fx_pnl = pnl - float(strategy_pnl) if pnl != 0.0 else 0.0
if pnl == 0.0 and (strategy_pnl or fx_pnl):
pnl = float(strategy_pnl) + float(fx_pnl)
conn.execute(
"""
INSERT INTO trades (
timestamp, stock_code, action, confidence, rationale,
quantity, price, pnl, market, exchange_code, selection_context, decision_id,
mode
quantity, price, pnl, strategy_pnl, fx_pnl,
market, exchange_code, session_id, selection_context, decision_id, mode
)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
(
datetime.now(UTC).isoformat(),
@@ -215,8 +261,11 @@ def log_trade(
quantity,
price,
pnl,
strategy_pnl,
fx_pnl,
market,
exchange_code,
resolved_session_id,
context_json,
decision_id,
mode,
@@ -225,6 +274,21 @@ def log_trade(
conn.commit()
def _resolve_session_id(*, market: str, session_id: str | None) -> str:
if session_id:
return session_id
try:
from src.core.order_policy import classify_session_id
from src.markets.schedule import MARKETS
market_info = MARKETS.get(market)
if market_info is not None:
return classify_session_id(market_info)
except Exception:
pass
return "UNKNOWN"
def get_latest_buy_trade(
conn: sqlite3.Connection, stock_code: str, market: str
) -> dict[str, Any] | None:

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@@ -0,0 +1,83 @@
from __future__ import annotations
import pytest
from src.analysis.backtest_cost_guard import BacktestCostModel, validate_backtest_cost_model
def test_valid_backtest_cost_model_passes() -> None:
model = BacktestCostModel(
commission_bps=5.0,
slippage_bps_by_session={"KRX_REG": 10.0, "US_PRE": 50.0},
failure_rate_by_session={"KRX_REG": 0.01, "US_PRE": 0.08},
unfavorable_fill_required=True,
)
validate_backtest_cost_model(model=model, required_sessions=["KRX_REG", "US_PRE"])
def test_missing_required_slippage_session_raises() -> None:
model = BacktestCostModel(
commission_bps=5.0,
slippage_bps_by_session={"KRX_REG": 10.0},
failure_rate_by_session={"KRX_REG": 0.01, "US_PRE": 0.08},
unfavorable_fill_required=True,
)
with pytest.raises(ValueError, match="missing slippage_bps_by_session.*US_PRE"):
validate_backtest_cost_model(model=model, required_sessions=["KRX_REG", "US_PRE"])
def test_missing_required_failure_rate_session_raises() -> None:
model = BacktestCostModel(
commission_bps=5.0,
slippage_bps_by_session={"KRX_REG": 10.0, "US_PRE": 50.0},
failure_rate_by_session={"KRX_REG": 0.01},
unfavorable_fill_required=True,
)
with pytest.raises(ValueError, match="missing failure_rate_by_session.*US_PRE"):
validate_backtest_cost_model(model=model, required_sessions=["KRX_REG", "US_PRE"])
def test_invalid_failure_rate_range_raises() -> None:
model = BacktestCostModel(
commission_bps=5.0,
slippage_bps_by_session={"KRX_REG": 10.0},
failure_rate_by_session={"KRX_REG": 1.2},
unfavorable_fill_required=True,
)
with pytest.raises(ValueError, match="failure rate must be within"):
validate_backtest_cost_model(model=model, required_sessions=["KRX_REG"])
def test_unfavorable_fill_requirement_cannot_be_disabled() -> None:
model = BacktestCostModel(
commission_bps=5.0,
slippage_bps_by_session={"KRX_REG": 10.0},
failure_rate_by_session={"KRX_REG": 0.02},
unfavorable_fill_required=False,
)
with pytest.raises(ValueError, match="unfavorable_fill_required must be True"):
validate_backtest_cost_model(model=model, required_sessions=["KRX_REG"])
@pytest.mark.parametrize("bad_commission", [float("nan"), float("inf"), float("-inf")])
def test_non_finite_commission_rejected(bad_commission: float) -> None:
model = BacktestCostModel(
commission_bps=bad_commission,
slippage_bps_by_session={"KRX_REG": 10.0},
failure_rate_by_session={"KRX_REG": 0.02},
unfavorable_fill_required=True,
)
with pytest.raises(ValueError, match="commission_bps"):
validate_backtest_cost_model(model=model, required_sessions=["KRX_REG"])
@pytest.mark.parametrize("bad_slippage", [float("nan"), float("inf"), float("-inf")])
def test_non_finite_slippage_rejected(bad_slippage: float) -> None:
model = BacktestCostModel(
commission_bps=5.0,
slippage_bps_by_session={"KRX_REG": bad_slippage},
failure_rate_by_session={"KRX_REG": 0.02},
unfavorable_fill_required=True,
)
with pytest.raises(ValueError, match="slippage bps"):
validate_backtest_cost_model(model=model, required_sessions=["KRX_REG"])

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@@ -0,0 +1,108 @@
from __future__ import annotations
import pytest
from src.analysis.backtest_execution_model import (
BacktestExecutionModel,
ExecutionAssumptions,
ExecutionRequest,
)
def test_buy_uses_unfavorable_slippage_direction() -> None:
model = BacktestExecutionModel(
ExecutionAssumptions(
slippage_bps_by_session={"US_PRE": 50.0},
failure_rate_by_session={"US_PRE": 0.0},
partial_fill_rate_by_session={"US_PRE": 0.0},
seed=1,
)
)
out = model.simulate(
ExecutionRequest(side="BUY", session_id="US_PRE", qty=10, reference_price=100.0)
)
assert out.status == "FILLED"
assert out.avg_price == pytest.approx(100.5)
def test_sell_uses_unfavorable_slippage_direction() -> None:
model = BacktestExecutionModel(
ExecutionAssumptions(
slippage_bps_by_session={"US_PRE": 50.0},
failure_rate_by_session={"US_PRE": 0.0},
partial_fill_rate_by_session={"US_PRE": 0.0},
seed=1,
)
)
out = model.simulate(
ExecutionRequest(side="SELL", session_id="US_PRE", qty=10, reference_price=100.0)
)
assert out.status == "FILLED"
assert out.avg_price == pytest.approx(99.5)
def test_failure_rate_can_reject_order() -> None:
model = BacktestExecutionModel(
ExecutionAssumptions(
slippage_bps_by_session={"KRX_REG": 10.0},
failure_rate_by_session={"KRX_REG": 1.0},
partial_fill_rate_by_session={"KRX_REG": 0.0},
seed=42,
)
)
out = model.simulate(
ExecutionRequest(side="BUY", session_id="KRX_REG", qty=10, reference_price=100.0)
)
assert out.status == "REJECTED"
assert out.filled_qty == 0
def test_partial_fill_applies_when_rate_is_one() -> None:
model = BacktestExecutionModel(
ExecutionAssumptions(
slippage_bps_by_session={"KRX_REG": 0.0},
failure_rate_by_session={"KRX_REG": 0.0},
partial_fill_rate_by_session={"KRX_REG": 1.0},
partial_fill_min_ratio=0.4,
partial_fill_max_ratio=0.4,
seed=0,
)
)
out = model.simulate(
ExecutionRequest(side="BUY", session_id="KRX_REG", qty=10, reference_price=100.0)
)
assert out.status == "PARTIAL"
assert out.filled_qty == 4
assert out.avg_price == 100.0
@pytest.mark.parametrize("bad_slip", [-1.0, float("nan"), float("inf")])
def test_invalid_slippage_is_rejected(bad_slip: float) -> None:
with pytest.raises(ValueError, match="slippage_bps"):
BacktestExecutionModel(
ExecutionAssumptions(
slippage_bps_by_session={"US_PRE": bad_slip},
failure_rate_by_session={"US_PRE": 0.0},
partial_fill_rate_by_session={"US_PRE": 0.0},
)
)
@pytest.mark.parametrize("bad_rate", [-0.1, 1.1, float("nan")])
def test_invalid_failure_or_partial_rates_are_rejected(bad_rate: float) -> None:
with pytest.raises(ValueError, match="failure_rate"):
BacktestExecutionModel(
ExecutionAssumptions(
slippage_bps_by_session={"US_PRE": 10.0},
failure_rate_by_session={"US_PRE": bad_rate},
partial_fill_rate_by_session={"US_PRE": 0.0},
)
)
with pytest.raises(ValueError, match="partial_fill_rate"):
BacktestExecutionModel(
ExecutionAssumptions(
slippage_bps_by_session={"US_PRE": 10.0},
failure_rate_by_session={"US_PRE": 0.0},
partial_fill_rate_by_session={"US_PRE": bad_rate},
)
)

View File

@@ -155,6 +155,9 @@ def test_mode_column_exists_in_schema() -> None:
cursor = conn.execute("PRAGMA table_info(trades)")
columns = {row[1] for row in cursor.fetchall()}
assert "mode" in columns
assert "session_id" in columns
assert "strategy_pnl" in columns
assert "fx_pnl" in columns
def test_mode_migration_adds_column_to_existing_db() -> None:
@@ -182,6 +185,13 @@ def test_mode_migration_adds_column_to_existing_db() -> None:
decision_id TEXT
)"""
)
old_conn.execute(
"""
INSERT INTO trades (
timestamp, stock_code, action, confidence, rationale, quantity, price, pnl
) VALUES ('2026-01-01T00:00:00+00:00', 'AAPL', 'SELL', 90, 'legacy', 1, 100.0, 123.45)
"""
)
old_conn.commit()
old_conn.close()
@@ -190,6 +200,132 @@ def test_mode_migration_adds_column_to_existing_db() -> None:
cursor = conn.execute("PRAGMA table_info(trades)")
columns = {row[1] for row in cursor.fetchall()}
assert "mode" in columns
assert "session_id" in columns
assert "strategy_pnl" in columns
assert "fx_pnl" in columns
migrated = conn.execute(
"SELECT pnl, strategy_pnl, fx_pnl, session_id FROM trades WHERE stock_code='AAPL' LIMIT 1"
).fetchone()
assert migrated is not None
assert migrated[0] == 123.45
assert migrated[1] == 123.45
assert migrated[2] == 0.0
assert migrated[3] == "UNKNOWN"
conn.close()
finally:
os.unlink(db_path)
def test_log_trade_stores_strategy_and_fx_pnl_separately() -> None:
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="AAPL",
action="SELL",
confidence=90,
rationale="fx split",
pnl=120.0,
strategy_pnl=100.0,
fx_pnl=20.0,
market="US_NASDAQ",
exchange_code="NASD",
)
row = conn.execute(
"SELECT pnl, strategy_pnl, fx_pnl FROM trades ORDER BY id DESC LIMIT 1"
).fetchone()
assert row is not None
assert row[0] == 120.0
assert row[1] == 100.0
assert row[2] == 20.0
def test_log_trade_backward_compat_sets_strategy_pnl_from_pnl() -> None:
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="005930",
action="SELL",
confidence=80,
rationale="legacy",
pnl=50.0,
market="KR",
exchange_code="KRX",
)
row = conn.execute(
"SELECT pnl, strategy_pnl, fx_pnl FROM trades ORDER BY id DESC LIMIT 1"
).fetchone()
assert row is not None
assert row[0] == 50.0
assert row[1] == 50.0
assert row[2] == 0.0
def test_log_trade_partial_fx_input_does_not_infer_negative_strategy_pnl() -> None:
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="AAPL",
action="SELL",
confidence=70,
rationale="fx only",
pnl=0.0,
fx_pnl=10.0,
market="US_NASDAQ",
exchange_code="NASD",
)
row = conn.execute(
"SELECT pnl, strategy_pnl, fx_pnl FROM trades ORDER BY id DESC LIMIT 1"
).fetchone()
assert row is not None
assert row[0] == 10.0
assert row[1] == 0.0
assert row[2] == 10.0
def test_log_trade_persists_explicit_session_id() -> None:
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="AAPL",
action="BUY",
confidence=70,
rationale="session test",
market="US_NASDAQ",
exchange_code="NASD",
session_id="US_PRE",
)
row = conn.execute("SELECT session_id FROM trades ORDER BY id DESC LIMIT 1").fetchone()
assert row is not None
assert row[0] == "US_PRE"
def test_log_trade_auto_derives_session_id_when_not_provided() -> None:
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="005930",
action="BUY",
confidence=70,
rationale="auto session",
market="KR",
exchange_code="KRX",
)
row = conn.execute("SELECT session_id FROM trades ORDER BY id DESC LIMIT 1").fetchone()
assert row is not None
assert row[0] != "UNKNOWN"
def test_log_trade_unknown_market_falls_back_to_unknown_session() -> None:
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="X",
action="BUY",
confidence=70,
rationale="unknown market",
market="MARS",
exchange_code="MARS",
)
row = conn.execute("SELECT session_id FROM trades ORDER BY id DESC LIMIT 1").fetchone()
assert row is not None
assert row[0] == "UNKNOWN"