refactor(web-ai): rename signal_v2→ai_trade, deprecate signal_v1

박재오 결정 2026-05-19 — V2를 정식 명칭 ai_trade로 graduation,
V1은 deprecated 마킹 (legacy 디렉토리 이동은 file lock 풀린 후 후속).

변경 사항:
- signal_v2/ → ai_trade/ (git mv, import 일괄 sed: signal_v2.x → ai_trade.x)
- root start.bat → legacy/start_v1.bat (V1 자동 시작 차단)
- ai_trade/start.bat 내부 uvicorn target signal_v2.main → ai_trade.main
- signal_v1/DEPRECATED.md 추가 (사용 금지 명시)
- CLAUDE.md 디렉토리 표·서버 시작 방식 갱신
- services/ 디렉토리 미래 예정 (Plan-B-Insta 작업 시 신설)

ai_trade tests 59/59 PASS 확인.

signal_v1/ 디렉토리 자체 이동(legacy/signal_v1/)은 telegram_bot.log +
data/news_snapshots.db file lock으로 보류. lock 해제 후 후속 커밋.

후속 작업: Plan-B-Insta (services/insta-render + NAS insta 분할)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

ai_trade/tests/conftest.py

@@ -0,0 +1,18 @@
+"""Pytest fixtures for ai_trade tests."""
+from pathlib import Path
+
+import pytest
+import respx
+
+
+@pytest.fixture
+def tmp_dedup_db(tmp_path) -> Path:
+    """SQLite 단위 테스트용 임시 DB path."""
+    return tmp_path / "test_ai_trade.db"
+
+
+@pytest.fixture
+def mock_stock_api():
+    """respx 로 stock API mock. base_url 은 테스트마다 임의."""
+    with respx.mock(base_url="https://test.stock.local", assert_all_called=False) as mock:
+        yield mock

ai_trade/tests/test_chronos_predictor.py

@@ -0,0 +1,92 @@
+"""Tests for ChronosPredictor (model mock)."""
+from unittest.mock import MagicMock, patch
+
+import numpy as np
+import pytest
+
+
+@pytest.fixture
+def mock_pipeline():
+    """Mock BaseChronosPipeline.from_pretrained returning a mock pipeline object."""
+    with patch("chronos.BaseChronosPipeline") as cls:
+        cls.__name__ = "BaseChronosPipeline"
+        instance = MagicMock()
+        # ChronosBolt API: predict_quantiles returns (quantiles_tensor, mean_tensor)
+        # Modern (predict_quantiles) branch will be used since hasattr(MagicMock, "predict_quantiles") is True.
+        cls.from_pretrained.return_value = instance
+        yield instance
+
+
+@pytest.fixture
+def mock_torch_cpu():
+    with patch("torch.cuda.is_available", return_value=False):
+        yield
+
+
+def _daily_ohlcv(close_seq):
+    return [{"datetime": f"2026-05-{i+1:02d}", "open": c, "high": c, "low": c,
+             "close": c, "volume": 1000} for i, c in enumerate(close_seq)]
+
+
+def _mk_quantiles_tensor(q10_price: float, q50_price: float, q90_price: float):
+    """Helper: build predict_quantiles return tensor shape [1, 1, 3]."""
+    import torch
+    return torch.tensor([[[q10_price, q50_price, q90_price]]], dtype=torch.float32)
+
+
+def test_predict_batch_returns_prediction_dict(mock_pipeline, mock_torch_cpu):
+    """mock predict_quantiles → dict[ticker, ChronosPrediction]. last_close=100, q50=102 → median≈+2%."""
+    quantiles = _mk_quantiles_tensor(101.5, 102.0, 102.5)  # narrow around 102
+    mock_pipeline.predict_quantiles.return_value = (quantiles, None)
+
+    from ai_trade.chronos_predictor import ChronosPredictor, ChronosPrediction
+    predictor = ChronosPredictor(model_name="mock-model")
+    daily = {"005930": _daily_ohlcv([100] * 60)}
+    result = predictor.predict_batch(daily)
+    assert "005930" in result
+    pred = result["005930"]
+    assert isinstance(pred, ChronosPrediction)
+    assert abs(pred.median - 0.02) < 0.001
+
+
+def test_conf_high_when_distribution_narrow(mock_pipeline, mock_torch_cpu):
+    """좁은 distribution (q90-q10 작음, median 0 아님) → conf ≈ 1."""
+    # last_close=100, q10=101.99, q50=102.00, q90=102.01
+    # returns: q10=0.0199, q50=0.02, q90=0.0201
+    # spread = (0.0201 - 0.0199) / max(0.02, 0.001) = 0.0002/0.02 = 0.01 → conf = 1 - 0.005 = 0.995
+    quantiles = _mk_quantiles_tensor(101.99, 102.0, 102.01)
+    mock_pipeline.predict_quantiles.return_value = (quantiles, None)
+
+    from ai_trade.chronos_predictor import ChronosPredictor
+    predictor = ChronosPredictor(model_name="mock-model")
+    daily = {"005930": _daily_ohlcv([100] * 60)}
+    result = predictor.predict_batch(daily)
+    assert result["005930"].conf > 0.8
+
+
+def test_conf_low_when_distribution_wide(mock_pipeline, mock_torch_cpu):
+    """넓은 distribution → conf ≈ 0."""
+    # last_close=100, q10=70, q50=100, q90=130
+    # returns: q10=-0.3, q50=0.0, q90=0.3
+    # spread = (0.3 - (-0.3)) / max(0.0, 0.001) = 0.6 / 0.001 = 600 → conf = max(0, 1 - 300) = 0
+    quantiles = _mk_quantiles_tensor(70.0, 100.0, 130.0)
+    mock_pipeline.predict_quantiles.return_value = (quantiles, None)
+
+    from ai_trade.chronos_predictor import ChronosPredictor
+    predictor = ChronosPredictor(model_name="mock-model")
+    daily = {"005930": _daily_ohlcv([100] * 60)}
+    result = predictor.predict_batch(daily)
+    assert result["005930"].conf < 0.3
+
+
+def test_return_computed_from_price_relative_to_last_close(mock_pipeline, mock_torch_cpu):
+    """price 예측 → last_close 대비 return 변환. last_close=100, q50=110 → return ≈ +10%."""
+    quantiles = _mk_quantiles_tensor(109.0, 110.0, 111.0)
+    mock_pipeline.predict_quantiles.return_value = (quantiles, None)
+
+    from ai_trade.chronos_predictor import ChronosPredictor
+    predictor = ChronosPredictor(model_name="mock-model")
+    # last close = 100
+    daily = {"005930": _daily_ohlcv(list(range(41, 101)))}  # last = 100
+    result = predictor.predict_batch(daily)
+    assert abs(result["005930"].median - 0.10) < 0.001

ai_trade/tests/test_kis_client.py

@@ -0,0 +1,161 @@
+"""Tests for KISClient (REST)."""
+import json
+from pathlib import Path
+
+import httpx
+import pytest
+import respx
+
+from ai_trade.kis_client import KISClient
+
+
+@pytest.fixture
+def fake_v1_token(tmp_path):
+    """V1 토큰 파일 fixture."""
+    token_file = tmp_path / "kis_token.json"
+    token_file.write_text(json.dumps({
+        "access_token": "test-kis-token-abc123",
+        "token_expired": "2099-12-31 23:59:59",
+    }))
+    return token_file
+
+
+@pytest.fixture
+def kis_client_factory(fake_v1_token):
+    def _make():
+        return KISClient(
+            app_key="test-app-key",
+            app_secret="test-app-secret",
+            account="50000000-01",
+            is_virtual=True,
+            v1_token_path=fake_v1_token,
+        )
+    return _make
+
+
+@respx.mock
+async def test_get_minute_ohlcv_normal_returns_30_bars(kis_client_factory):
+    """정상 200 → 30개 분봉 list 반환."""
+    sample_output2 = [
+        {
+            "stck_bsop_date": "20260518",
+            "stck_cntg_hour": f"09{m:02d}00",
+            "stck_oprc": "78000", "stck_hgpr": "78500",
+            "stck_lwpr": "77800", "stck_prpr": "78300",
+            "cntg_vol": "12345",
+        }
+        for m in range(30)  # 9:00-9:29 = 30 bars
+    ]
+    respx.get(
+        "https://openapivts.koreainvestment.com:29443/uapi/domestic-stock/v1/quotations/inquire-time-itemchartprice"
+    ).mock(
+        return_value=httpx.Response(200, json={"output2": sample_output2})
+    )
+
+    client = kis_client_factory()
+    try:
+        bars = await client.get_minute_ohlcv("005930")
+        assert len(bars) == 30
+        assert bars[0]["close"] == 78300
+        assert "datetime" in bars[0]
+    finally:
+        await client.close()
+
+
+@respx.mock
+async def test_get_minute_ohlcv_429_retry_then_success(kis_client_factory, monkeypatch):
+    """429 → exponential backoff → 200."""
+    sleep_calls = []
+    async def fake_sleep(s): sleep_calls.append(s)
+    monkeypatch.setattr("asyncio.sleep", fake_sleep)
+
+    respx.get(
+        "https://openapivts.koreainvestment.com:29443/uapi/domestic-stock/v1/quotations/inquire-time-itemchartprice"
+    ).mock(side_effect=[
+        httpx.Response(429, text="rate limit"),
+        httpx.Response(200, json={"output2": []}),
+    ])
+    client = kis_client_factory()
+    try:
+        result = await client.get_minute_ohlcv("005930")
+        assert result == []
+        assert 1 in sleep_calls
+    finally:
+        await client.close()
+
+
+@respx.mock
+async def test_get_minute_ohlcv_uses_v1_token(kis_client_factory, fake_v1_token):
+    """KIS 호출 헤더에 V1 토큰 파일의 access_token 사용."""
+    route = respx.get(
+        "https://openapivts.koreainvestment.com:29443/uapi/domestic-stock/v1/quotations/inquire-time-itemchartprice"
+    ).mock(return_value=httpx.Response(200, json={"output2": []}))
+
+    client = kis_client_factory()
+    try:
+        await client.get_minute_ohlcv("005930")
+        assert route.called
+        req = route.calls.last.request
+        # check authorization header contains the V1 token
+        auth = req.headers.get("authorization", "")
+        assert "test-kis-token-abc123" in auth
+    finally:
+        await client.close()
+
+
+@respx.mock
+async def test_get_asking_price_computes_bid_ratio(kis_client_factory):
+    """호가 응답 → bid_total/(bid+ask) bid_ratio 계산."""
+    respx.get(
+        "https://openapivts.koreainvestment.com:29443/uapi/domestic-stock/v1/quotations/inquire-asking-price-exp-ccn"
+    ).mock(return_value=httpx.Response(200, json={
+        "output1": {
+            "total_bidp_rsqn": "600",
+            "total_askp_rsqn": "400",
+            "stck_prpr": "78500",
+        }
+    }))
+
+    client = kis_client_factory()
+    try:
+        data = await client.get_asking_price("005930")
+        assert data["bid_total"] == 600
+        assert data["ask_total"] == 400
+        assert abs(data["bid_ratio"] - 0.6) < 1e-9
+        assert data["current_price"] == 78500
+        assert "as_of" in data
+    finally:
+        await client.close()
+
+
+@respx.mock
+async def test_get_daily_ohlcv_returns_60_bars(kis_client_factory):
+    """KIS daily endpoint returns 60 ascending bars after parsing."""
+    # Build 60 KIS-format daily bars (descending dates as KIS does)
+    sample_output2 = []
+    for i in range(60):
+        # Generate a fake date 60 days ago, descending
+        day = 60 - i
+        sample_output2.append({
+            "stck_bsop_date": f"2026{(((day-1)//30)+1):02d}{(((day-1)%30)+1):02d}",
+            "stck_oprc": "78000", "stck_hgpr": "78500",
+            "stck_lwpr": "77800", "stck_clpr": str(78000 + i),
+            "acml_vol": "12345",
+        })
+
+    respx.get(
+        "https://openapivts.koreainvestment.com:29443/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
+    ).mock(return_value=httpx.Response(200, json={"output2": sample_output2}))
+
+    client = kis_client_factory()
+    try:
+        bars = await client.get_daily_ohlcv("005930", days=60)
+        # KIS returns descending; client reverses to ascending
+        assert len(bars) == 60
+        # Ascending order: first item has smaller datetime than last
+        assert bars[0]["datetime"] < bars[-1]["datetime"]
+        assert isinstance(bars[0]["open"], int)
+        assert isinstance(bars[0]["close"], int)
+        assert "datetime" in bars[0]
+    finally:
+        await client.close()

ai_trade/tests/test_kis_websocket.py

@@ -0,0 +1,94 @@
+"""Tests for KISWebSocket."""
+import asyncio
+import json
+from unittest.mock import AsyncMock, MagicMock
+
+import httpx
+import pytest
+import respx
+
+from ai_trade.kis_websocket import KISWebSocket
+
+
+BASE_REST = "https://openapivts.koreainvestment.com:29443"
+
+
+@respx.mock
+async def test_fetch_approval_key_via_oauth_endpoint():
+    """POST /oauth2/Approval → approval_key 추출."""
+    respx.post(f"{BASE_REST}/oauth2/Approval").mock(
+        return_value=httpx.Response(200, json={"approval_key": "test-approval-key-xyz"})
+    )
+    ws = KISWebSocket(app_key="k", app_secret="s", is_virtual=True)
+    key = await ws._fetch_approval_key()
+    assert key == "test-approval-key-xyz"
+    assert ws._approval_key == "test-approval-key-xyz"
+
+
+async def test_subscribe_sends_h0stasp0_message():
+    """subscribe() → WebSocket 으로 H0STASP0 구독 메시지 전송."""
+    sent_messages = []
+    mock_ws = AsyncMock()
+    mock_ws.send = AsyncMock(side_effect=lambda m: sent_messages.append(m))
+
+    ws = KISWebSocket(app_key="k", app_secret="s", is_virtual=True)
+    ws._approval_key = "test-key"
+    ws._ws = mock_ws
+    await ws.subscribe("005930")
+    assert ws._subscriptions == {"005930"}
+    assert len(sent_messages) == 1
+    msg = json.loads(sent_messages[0])
+    assert msg["header"]["tr_type"] == "1"  # subscribe
+    assert msg["body"]["input"]["tr_id"] == "H0STASP0"
+    assert msg["body"]["input"]["tr_key"] == "005930"
+
+
+def test_parse_asking_price_extracts_bid_ask_totals():
+    """KIS raw '0|H0STASP0|001|...' → (ticker, dict).
+
+    KIS 호가 메시지 형식 — KIS 공식 spec 의 정확한 필드 인덱스 운영 검증 필요.
+    본 테스트는 implementer 의 _parse_asking_price 구현 인덱스에 맞춰서 sample 작성.
+    """
+    ws = KISWebSocket(app_key="k", app_secret="s", is_virtual=True)
+    # Build a sample raw message — implementer 가 _ASKING_TOTAL_BID/ASK 인덱스에
+    # 맞춰서 필드 배치하면 됨. 예: 마지막 2개 필드를 bid_total / ask_total 로.
+    fields = ["005930", "091500", "78500"]  # ticker, time, current_price
+    fields.extend(["0"] * 40)  # padding (KIS 의 실 필드 수 ~50개)
+    fields.append("400")  # ask_total
+    fields.append("600")  # bid_total
+    raw = f"0|H0STASP0|001|{'^'.join(fields)}"
+
+    result = ws._parse_asking_price(raw)
+    assert result is not None, "parse_asking_price returned None"
+    ticker, data = result
+    assert ticker == "005930"
+    assert "bid_total" in data
+    assert "ask_total" in data
+    assert "bid_ratio" in data
+    assert "current_price" in data
+    # bid_total=600, ask_total=400, bid_ratio=0.6
+    assert data["bid_total"] == 600
+    assert data["ask_total"] == 400
+    assert abs(data["bid_ratio"] - 0.6) < 1e-9
+
+
+async def test_reconnect_on_disconnect_with_backoff(monkeypatch):
+    """연결 끊김 → exponential backoff retry. _connect_with_backoff() 검증."""
+    sleep_calls = []
+    async def fake_sleep(s): sleep_calls.append(s)
+    monkeypatch.setattr("asyncio.sleep", fake_sleep)
+
+    ws = KISWebSocket(app_key="k", app_secret="s", is_virtual=True)
+    # Mock _connect to fail twice then succeed
+    call_count = [0]
+    async def fake_connect():
+        call_count[0] += 1
+        if call_count[0] < 3:
+            raise ConnectionError("fake disconnect")
+        return AsyncMock()
+    monkeypatch.setattr(ws, "_connect", fake_connect)
+
+    result = await ws._connect_with_backoff()
+    assert call_count[0] == 3  # 2 fails + 1 success
+    # exponential 1s, 2s
+    assert sleep_calls[:2] == [1, 2]

ai_trade/tests/test_main.py

@@ -0,0 +1,62 @@
+"""Tests for FastAPI main app."""
+import logging
+
+import pytest
+from fastapi.testclient import TestClient
+
+
+def test_health_endpoint_returns_status_online(monkeypatch):
+    monkeypatch.setenv("STOCK_API_URL", "https://test.stock.local")
+    monkeypatch.setenv("WEBAI_API_KEY", "test-secret")
+    # Reload modules so they pick up the new env
+    import importlib
+    from ai_trade import config as cfg
+    importlib.reload(cfg)
+    from ai_trade import main as main_mod
+    importlib.reload(main_mod)
+    with TestClient(main_mod.app) as client:
+        r = client.get("/health")
+        assert r.status_code == 200
+        body = r.json()
+        assert body["status"] == "online"
+        assert body["stock_api_url"] == "https://test.stock.local"
+
+
+def test_startup_warns_if_webai_api_key_missing(monkeypatch, caplog):
+    # Use setenv with empty string + no-op load_dotenv to defeat .env re-read on reload
+    monkeypatch.setattr("ai_trade.config.load_dotenv", lambda *a, **k: None)
+    monkeypatch.setenv("WEBAI_API_KEY", "")
+    monkeypatch.setenv("STOCK_API_URL", "https://test.stock.local")
+    import importlib
+    from ai_trade import config as cfg
+    importlib.reload(cfg)
+    # After reload, load_dotenv reference is fresh — re-patch
+    monkeypatch.setattr("ai_trade.config.load_dotenv", lambda *a, **k: None)
+    from ai_trade import main as main_mod
+    importlib.reload(main_mod)
+    with caplog.at_level(logging.WARNING, logger="ai_trade.main"):
+        with TestClient(main_mod.app) as client:
+            client.get("/health")
+        assert any("WEBAI_API_KEY" in rec.message for rec in caplog.records)
+
+
+def test_startup_warns_if_kis_app_key_missing(monkeypatch, caplog):
+    """KIS app_key 미설정 시 startup WARNING (KIS 호출 disabled) — V1 패턴."""
+    monkeypatch.setattr("ai_trade.config.load_dotenv", lambda *a, **k: None)
+    monkeypatch.setenv("STOCK_API_URL", "https://test.stock.local")
+    monkeypatch.setenv("WEBAI_API_KEY", "test-secret")
+    # V1 pattern: kis_env_type=virtual, both virtual keys empty
+    monkeypatch.setenv("KIS_ENV_TYPE", "virtual")
+    monkeypatch.setenv("KIS_VIRTUAL_APP_KEY", "")
+    monkeypatch.setenv("KIS_REAL_APP_KEY", "")
+
+    import importlib
+    from ai_trade import config as cfg
+    importlib.reload(cfg)
+    monkeypatch.setattr("ai_trade.config.load_dotenv", lambda *a, **k: None)
+    from ai_trade import main as main_mod
+    importlib.reload(main_mod)
+    with caplog.at_level(logging.WARNING, logger="ai_trade.main"):
+        with TestClient(main_mod.app) as client:
+            client.get("/health")
+        assert any("KIS" in rec.message and "app_key" in rec.message.lower() for rec in caplog.records)

ai_trade/tests/test_momentum_classifier.py

@@ -0,0 +1,92 @@
+"""Tests for minute momentum classifier."""
+from collections import deque
+
+from ai_trade.momentum_classifier import (
+    aggregate_1min_to_5min, classify_minute_momentum,
+    STRONG_UP, WEAK_UP, NEUTRAL, WEAK_DOWN, STRONG_DOWN,
+)
+
+
+def _bar(open_, high, low, close, volume):
+    return {
+        "datetime": "2026-05-18T09:00:00+09:00",
+        "open": open_, "high": high, "low": low, "close": close, "volume": volume,
+    }
+
+
+def _make_chunks(num_chunks_up: int, num_chunks_total: int, base_vol: int = 1000):
+    """num_chunks_total 개의 5-bar 청크. num_chunks_up 청크는 양봉, 나머지는 음봉.
+    각 청크는 5개 1분봉. 거래량 = base_vol per bar.
+    """
+    bars = []
+    for i in range(num_chunks_total):
+        is_up = i < num_chunks_up
+        o, c = (100, 110) if is_up else (110, 100)
+        for j in range(5):
+            bars.append(_bar(o, max(o, c) + 5, min(o, c) - 5, c, base_vol))
+    return bars
+
+
+def test_strong_up_5_consecutive_green_with_high_volume():
+    """직전 5개 5분봉 모두 양봉 + 거래량 1.5x → STRONG_UP."""
+    # 60분 (12 5분봉) 데이터: 7 normal + 5 high-vol up
+    older = _make_chunks(num_chunks_up=3, num_chunks_total=7, base_vol=1000)
+    recent = _make_chunks(num_chunks_up=5, num_chunks_total=5, base_vol=2500)
+    minute_bars = deque(older + recent, maxlen=60)
+    assert classify_minute_momentum(minute_bars) == STRONG_UP
+
+
+def test_weak_up_3of5_green_normal_volume():
+    """직전 5개 5분봉 중 3-4개 양봉 + 거래량 ≥ 1.0x → WEAK_UP."""
+    older = _make_chunks(num_chunks_up=3, num_chunks_total=7, base_vol=1000)
+    # 5 chunks: 3 up + 2 down, normal vol
+    recent_up = _make_chunks(num_chunks_up=3, num_chunks_total=3, base_vol=1000)
+    recent_down = _make_chunks(num_chunks_up=0, num_chunks_total=2, base_vol=1000)
+    minute_bars = deque(older + recent_up + recent_down, maxlen=60)
+    assert classify_minute_momentum(minute_bars) == WEAK_UP
+
+
+def test_neutral_mixed():
+    """up_count=2, vol normal → NEUTRAL (rule 미해당)."""
+    older = _make_chunks(num_chunks_up=3, num_chunks_total=7, base_vol=1000)
+    recent_up = _make_chunks(num_chunks_up=2, num_chunks_total=2, base_vol=1000)
+    recent_down = _make_chunks(num_chunks_up=0, num_chunks_total=3, base_vol=1000)
+    minute_bars = deque(older + recent_up + recent_down, maxlen=60)
+    # up_count=2, vol_mult=1.0 → 어느 분기 조건도 만족 안 함 → NEUTRAL
+    assert classify_minute_momentum(minute_bars) == NEUTRAL
+
+
+def test_weak_down_low_green_low_volume():
+    """up_count <= 2 + vol < 1.0 → WEAK_DOWN."""
+    older = _make_chunks(num_chunks_up=3, num_chunks_total=7, base_vol=1000)
+    recent_up = _make_chunks(num_chunks_up=1, num_chunks_total=1, base_vol=500)
+    recent_down = _make_chunks(num_chunks_up=0, num_chunks_total=4, base_vol=500)
+    minute_bars = deque(older + recent_up + recent_down, maxlen=60)
+    # recent 5 chunks avg vol = 500, long 12 avg ≈ (7*1000 + 5*500) / 12 ≈ 791 → vol_mult ≈ 0.63
+    assert classify_minute_momentum(minute_bars) == WEAK_DOWN
+
+
+def test_strong_down_5_consecutive_red_high_volume():
+    """직전 5개 5분봉 모두 음봉 + 거래량 1.5x → STRONG_DOWN."""
+    older = _make_chunks(num_chunks_up=3, num_chunks_total=7, base_vol=1000)
+    recent = _make_chunks(num_chunks_up=0, num_chunks_total=5, base_vol=2500)
+    minute_bars = deque(older + recent, maxlen=60)
+    assert classify_minute_momentum(minute_bars) == STRONG_DOWN
+
+
+def test_aggregate_1min_to_5min_correctness():
+    """5 1분봉 → 1개 5분봉 — open/close/high/low/volume 정확."""
+    bars = [
+        _bar(100, 105, 99, 102, 1000),
+        _bar(102, 108, 101, 107, 1500),
+        _bar(107, 110, 105, 106, 800),
+        _bar(106, 109, 104, 108, 1200),
+        _bar(108, 112, 107, 111, 900),
+    ]
+    result = aggregate_1min_to_5min(bars)
+    assert len(result) == 1
+    assert result[0]["open"] == 100  # 첫 bar
+    assert result[0]["close"] == 111  # 마지막 bar
+    assert result[0]["high"] == 112  # max
+    assert result[0]["low"] == 99    # min
+    assert result[0]["volume"] == 5400  # sum

ai_trade/tests/test_pull_worker.py

@@ -0,0 +1,131 @@
+"""Tests for pull_worker (Phase 3a additions)."""
+from collections import deque
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from ai_trade.state import PollState
+
+
+async def test_minute_polling_cycle_updates_state_minute_bars():
+    """KIS REST mock 의 분봉 데이터가 state.minute_bars[ticker] deque 에 들어간다."""
+    from ai_trade.pull_worker import _run_kis_minute_cycle
+
+    state = PollState()
+    state.portfolio = {"holdings": [{"ticker": "005930"}, {"ticker": "000660"}]}
+    state.screener_preview = {
+        "items": [{"ticker": "005930"}, {"ticker": "035720"}]
+    }
+
+    kis_client_mock = MagicMock()
+    kis_client_mock.get_minute_ohlcv = AsyncMock(side_effect=[
+        [{"datetime": "2026-05-18T09:00:00+09:00", "open": 78000,
+          "high": 78500, "low": 77900, "close": 78300, "volume": 12345}],
+        [{"datetime": "2026-05-18T09:00:00+09:00", "open": 180000,
+          "high": 181000, "low": 179800, "close": 180500, "volume": 5000}],
+        [{"datetime": "2026-05-18T09:00:00+09:00", "open": 51000,
+          "high": 51200, "low": 50800, "close": 51100, "volume": 8000}],
+    ])
+    kis_client_mock.get_asking_price = AsyncMock(return_value={
+        "bid_total": 600, "ask_total": 400, "bid_ratio": 0.6,
+        "current_price": 51100, "as_of": "2026-05-18T09:00:30+09:00",
+    })
+
+    await _run_kis_minute_cycle(kis_client_mock, state)
+
+    # 3 unique tickers (005930, 000660, 035720)
+    assert "005930" in state.minute_bars
+    assert "000660" in state.minute_bars
+    assert "035720" in state.minute_bars
+    assert len(state.minute_bars["005930"]) >= 1
+    # asking_price 만 screener-only ticker (035720) 에 들어가야 함
+    # (portfolio = 005930, 000660 는 WebSocket 으로 들어옴)
+    assert "035720" in state.asking_price
+
+
+def test_websocket_message_updates_state_asking_price():
+    """WebSocket callback factory → state.asking_price 갱신."""
+    from ai_trade.pull_worker import make_asking_price_callback
+
+    state = PollState()
+    cb = make_asking_price_callback(state)
+    cb("005930", {"bid_total": 1000, "ask_total": 800, "bid_ratio": 0.555,
+                  "current_price": 78500, "as_of": "2026-05-18T10:00:00+09:00"})
+    assert state.asking_price["005930"]["bid_total"] == 1000
+    assert "asking_price/005930" in state.last_updated
+
+
+async def test_post_close_cycle_updates_chronos_predictions():
+    """mock kis + mock chronos → state.chronos_predictions + state.daily_ohlcv 갱신."""
+    from unittest.mock import AsyncMock, MagicMock
+    from ai_trade.pull_worker import _run_post_close_cycle
+    from ai_trade.chronos_predictor import ChronosPrediction
+    from ai_trade.state import PollState
+
+    state = PollState()
+    state.portfolio = {"holdings": [{"ticker": "005930"}]}
+    state.screener_preview = {"items": [{"ticker": "000660"}]}
+
+    kis_mock = MagicMock()
+    daily_005930 = [{"datetime": f"2026-05-{i+1:02d}", "open": 100, "high": 105,
+                     "low": 95, "close": 100 + i, "volume": 1000} for i in range(60)]
+    daily_000660 = [{"datetime": f"2026-05-{i+1:02d}", "open": 200, "high": 210,
+                     "low": 190, "close": 200 + i, "volume": 2000} for i in range(60)]
+    # _run_post_close_cycle iterates tickers and calls get_daily_ohlcv per ticker.
+    # Order depends on set() so use side_effect mapping if possible, otherwise list.
+    async def fake_daily(ticker, days=60):
+        if ticker == "005930":
+            return daily_005930
+        if ticker == "000660":
+            return daily_000660
+        return []
+    kis_mock.get_daily_ohlcv = AsyncMock(side_effect=fake_daily)
+
+    chronos_mock = MagicMock()
+    chronos_mock.predict_batch = MagicMock(return_value={
+        "005930": ChronosPrediction(0.02, -0.01, 0.04, 0.85, "2026-05-18T16:00:00+09:00"),
+        "000660": ChronosPrediction(0.03, -0.02, 0.06, 0.75, "2026-05-18T16:00:00+09:00"),
+    })
+
+    await _run_post_close_cycle(kis_mock, chronos_mock, state)
+
+    assert "005930" in state.chronos_predictions
+    assert "000660" in state.chronos_predictions
+    assert state.chronos_predictions["005930"]["median"] == 0.02
+    assert state.chronos_predictions["005930"]["conf"] == 0.85
+    assert "005930" in state.daily_ohlcv
+    assert "chronos/005930" in state.last_updated
+
+
+def test_poll_loop_calls_generate_signals_after_cycle(monkeypatch):
+    """Phase 4: generate_signals 가 cycle 후 state.signals 를 갱신한다."""
+    from unittest.mock import MagicMock
+    from ai_trade.state import PollState
+    from ai_trade.signal_generator import generate_signals
+
+    state = PollState()
+    state.portfolio = {"holdings": [{
+        "ticker": "005930", "name": "삼성전자",
+        "avg_price": 75000, "current_price": 69000,
+        "pnl_pct": -0.08, "profit_rate": -8.0,
+        "quantity": 100, "broker": "키움",
+    }]}
+    state.screener_preview = {"items": []}
+
+    dedup = MagicMock()
+    dedup.is_recent.return_value = False
+
+    settings = MagicMock()
+    settings.stop_loss_pct = -0.07
+    settings.take_profit_pct = 0.15
+    settings.chronos_spread_threshold = 0.6
+    settings.asking_bid_ratio_threshold = 0.6
+    settings.confidence_threshold = 0.7
+    settings.min_momentum_for_buy = "strong_up"
+
+    generate_signals(state, dedup, settings)
+
+    assert "005930" in state.signals
+    assert state.signals["005930"]["action"] == "sell"
+    assert state.signals["005930"]["confidence_webai"] == 1.0
+    dedup.record.assert_called_with("005930", "sell", confidence=1.0)

ai_trade/tests/test_rate_limit.py

@@ -0,0 +1,34 @@
+"""Tests for SignalDedup."""
+from datetime import datetime, timedelta
+from zoneinfo import ZoneInfo
+
+from ai_trade.rate_limit import SignalDedup
+
+KST = ZoneInfo("Asia/Seoul")
+
+
+def test_is_recent_returns_false_for_new_ticker_action(tmp_dedup_db):
+    dedup = SignalDedup(tmp_dedup_db)
+    assert dedup.is_recent("005930", "buy") is False
+
+
+def test_is_recent_returns_true_within_24h(tmp_dedup_db):
+    dedup = SignalDedup(tmp_dedup_db)
+    dedup.record("005930", "buy", confidence=0.82)
+    assert dedup.is_recent("005930", "buy") is True
+
+
+def test_is_recent_returns_false_after_24h(tmp_dedup_db, monkeypatch):
+    dedup = SignalDedup(tmp_dedup_db)
+    # Record with a timestamp 25 hours ago
+    now = datetime.now(KST)
+    fake_now = now - timedelta(hours=25)
+    monkeypatch.setattr(
+        "ai_trade.rate_limit._now_iso", lambda: fake_now.isoformat()
+    )
+    dedup.record("005930", "buy", confidence=0.82)
+    # Reset to real now for is_recent check
+    monkeypatch.setattr(
+        "ai_trade.rate_limit._now_iso", lambda: now.isoformat()
+    )
+    assert dedup.is_recent("005930", "buy", within_hours=24) is False

ai_trade/tests/test_scheduler.py

@@ -0,0 +1,81 @@
+"""Tests for scheduler interval logic."""
+from datetime import datetime
+
+import pytest
+
+from ai_trade.scheduler import _next_interval, _is_market_day, KST
+
+
+def _kst(year, month, day, hour, minute=0):
+    return datetime(year, month, day, hour, minute, tzinfo=KST)
+
+
+def test_next_interval_pre_market_5min():
+    now = _kst(2026, 5, 18, 8, 30)  # Monday 08:30
+    assert _next_interval(now) == 300
+
+
+def test_next_interval_market_open_1min():
+    now = _kst(2026, 5, 18, 10, 0)  # Monday 10:00
+    assert _next_interval(now) == 60
+
+
+def test_next_interval_post_market_5min():
+    now = _kst(2026, 5, 18, 17, 0)  # Monday 17:00
+    assert _next_interval(now) == 300
+
+
+def test_next_interval_overnight_skip_to_next_morning():
+    now = _kst(2026, 5, 18, 2, 30)  # Monday 02:30 (dead zone, not NXT window)
+    interval = _next_interval(now)
+    # Dead zone 23:30-04:30 → next 04:30 is ~2h away
+    assert 2 * 3600 - 60 < interval < 2 * 3600 + 60
+
+
+def test_next_interval_holiday_skip():
+    # 2026-05-05 어린이날 (Tuesday holiday)
+    now = _kst(2026, 5, 5, 10, 0)
+    assert _is_market_day(now) is False
+    interval = _next_interval(now)
+    # Next: 2026-05-06 (Wed) 07:00, ~21h away
+    assert 20 * 3600 < interval < 22 * 3600
+
+
+def test_next_interval_at_market_open_boundary():
+    """09:00:00 정확 second → 60초 (market 구간 진입)."""
+    now = _kst(2026, 5, 18, 9, 0)  # Monday 09:00:00
+    assert _next_interval(now) == 60
+
+
+def test_next_interval_at_market_close_boundary():
+    """15:30:00 정확 second → 300초 (post-market 구간 진입)."""
+    now = _kst(2026, 5, 18, 15, 30)  # Monday 15:30:00
+    assert _next_interval(now) == 300
+
+
+def test_next_interval_at_polling_window_end_boundary():
+    """23:30:00 정확 second → dead zone skip (다음 04:30 까지)."""
+    now = _kst(2026, 5, 18, 23, 30)  # Monday 23:30:00 (NXT_PRE_END boundary)
+    interval = _next_interval(now)
+    # Dead zone 23:30-04:30 → next 04:30 is ~5h away
+    assert 5 * 3600 - 60 < interval < 5 * 3600 + 60
+
+
+def test_next_interval_nxt_evening_5min():
+    """22:00 평일 (NXT 야간) → 300 (5분)."""
+    now = _kst(2026, 5, 18, 22, 0)
+    assert _next_interval(now) == 300
+
+
+def test_next_interval_nxt_dawn_5min():
+    """05:30 평일 (NXT 새벽) → 300 (5분)."""
+    now = _kst(2026, 5, 18, 5, 30)
+    assert _next_interval(now) == 300
+
+
+def test_next_interval_dead_zone_skip():
+    """02:00 평일 (dead zone 23:30-04:30) → 다음 04:30 까지 (~9000s)."""
+    now = _kst(2026, 5, 18, 2, 0)
+    interval = _next_interval(now)
+    # 02:00 → 04:30 = 2.5h = 9000s
+    assert 9000 - 60 < interval < 9000 + 60

ai_trade/tests/test_signal_generator.py

@@ -0,0 +1,172 @@
+"""Tests for signal_generator."""
+from unittest.mock import MagicMock
+
+import pytest
+
+from ai_trade.signal_generator import generate_signals
+from ai_trade.state import PollState
+
+
+def _settings(**overrides):
+    """Build a Settings-like object for tests (avoid env)."""
+    defaults = dict(
+        stop_loss_pct=-0.07,
+        take_profit_pct=0.15,
+        chronos_spread_threshold=0.6,
+        asking_bid_ratio_threshold=0.6,
+        confidence_threshold=0.7,
+        min_momentum_for_buy="strong_up",
+    )
+    defaults.update(overrides)
+    m = MagicMock()
+    for k, v in defaults.items():
+        setattr(m, k, v)
+    return m
+
+
+def _make_state_with_buy_candidate(
+    ticker="005930", name="삼성전자",
+    chronos_median=0.02, chronos_q10=-0.01, chronos_q90=0.04, chronos_conf=0.85,
+    momentum="strong_up", bid_ratio=0.7, current_price=78500,
+):
+    state = PollState()
+    state.screener_preview = {"items": [{"ticker": ticker, "name": name}]}
+    state.chronos_predictions[ticker] = {
+        "median": chronos_median, "q10": chronos_q10, "q90": chronos_q90,
+        "conf": chronos_conf, "as_of": "2026-05-17T16:00:00+09:00",
+    }
+    state.minute_momentum[ticker] = momentum
+    state.asking_price[ticker] = {
+        "bid_total": int(bid_ratio * 1000),
+        "ask_total": int((1 - bid_ratio) * 1000),
+        "bid_ratio": bid_ratio,
+        "current_price": current_price,
+        "as_of": "2026-05-17T16:00:01+09:00",
+    }
+    return state
+
+
+def _make_state_with_holding(
+    ticker="005930", name="삼성전자",
+    pnl_pct=0.0, avg_price=75000, current_price=75000,
+):
+    state = PollState()
+    state.portfolio = {"holdings": [{
+        "ticker": ticker, "name": name,
+        "avg_price": avg_price, "current_price": current_price,
+        "pnl_pct": pnl_pct, "profit_rate": pnl_pct * 100,
+        "quantity": 100, "broker": "키움",
+    }]}
+    state.screener_preview = {"items": []}
+    return state
+
+
+@pytest.fixture
+def dedup_mock():
+    d = MagicMock()
+    d.is_recent.return_value = False
+    return d
+
+
+def test_buy_signal_when_all_conditions_pass_and_confidence_high(dedup_mock):
+    state = _make_state_with_buy_candidate()
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" in state.signals
+    sig = state.signals["005930"]
+    assert sig["action"] == "buy"
+    assert sig["confidence_webai"] > 0.7
+    dedup_mock.record.assert_called()
+
+
+def test_silent_when_chronos_median_negative(dedup_mock):
+    state = _make_state_with_buy_candidate(chronos_median=-0.01)
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" not in state.signals
+
+
+def test_silent_when_distribution_spread_too_wide(dedup_mock):
+    # spread = q90 - q10 = 0.5 - (-0.5) = 1.0 > 0.6 → hard gate fails
+    state = _make_state_with_buy_candidate(
+        chronos_median=0.001, chronos_q10=-0.5, chronos_q90=0.5,
+    )
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" not in state.signals
+
+
+def test_silent_when_momentum_not_strong_up(dedup_mock):
+    state = _make_state_with_buy_candidate(momentum="weak_up")
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" not in state.signals
+
+
+def test_silent_when_bid_ratio_below_threshold(dedup_mock):
+    state = _make_state_with_buy_candidate(bid_ratio=0.5)
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" not in state.signals
+
+
+def test_silent_when_confidence_below_threshold(dedup_mock):
+    # chronos_conf low + rank=20 → confidence < 0.7
+    state = _make_state_with_buy_candidate(chronos_conf=0.3)
+    # add 19 fake items to push 005930 rank to 20
+    state.screener_preview["items"] = (
+        [{"ticker": f"FAKE{i:03d}"} for i in range(19)]
+        + [{"ticker": "005930", "name": "삼성전자"}]
+    )
+    generate_signals(state, dedup_mock, _settings())
+    # confidence_webai = 0.3*0.5 + 1.0*0.3 + 0.05*0.2 = 0.46 < 0.7
+    assert "005930" not in state.signals
+
+
+def test_sell_signal_when_stop_loss_triggered(dedup_mock):
+    state = _make_state_with_holding(pnl_pct=-0.08, current_price=69000, avg_price=75000)
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" in state.signals
+    sig = state.signals["005930"]
+    assert sig["action"] == "sell"
+    assert sig["confidence_webai"] == 1.0
+    assert sig["pnl_pct"] == -0.08
+
+
+def test_sell_signal_when_take_profit_triggered(dedup_mock):
+    state = _make_state_with_holding(pnl_pct=0.16, current_price=87000, avg_price=75000)
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" in state.signals
+    sig = state.signals["005930"]
+    assert sig["action"] == "sell"
+    assert sig["confidence_webai"] == 0.6
+
+
+def test_silent_when_dedup_recently_sent(dedup_mock):
+    state = _make_state_with_buy_candidate()
+    dedup_mock.is_recent.return_value = True
+    generate_signals(state, dedup_mock, _settings())
+    assert "005930" not in state.signals
+    dedup_mock.record.assert_not_called()
+
+
+def test_sell_signal_triggers_on_anomaly_path(dedup_mock):
+    """Anomaly sell: median < -1%, momentum strong_down, low bid_ratio, confidence > threshold."""
+    state = PollState()
+    state.portfolio = {"holdings": [{
+        "ticker": "005930", "name": "삼성전자",
+        "avg_price": 75000, "current_price": 70000,
+        "pnl_pct": -0.067,  # within stop_loss tolerance (default -0.07): NOT triggering stop_loss
+        "quantity": 100, "broker": "키움",
+    }]}
+    state.screener_preview = {"items": []}
+    state.chronos_predictions["005930"] = {
+        "median": -0.025, "q10": -0.05, "q90": 0.005, "conf": 0.85,
+    }
+    state.minute_momentum["005930"] = "strong_down"
+    state.asking_price["005930"] = {"current_price": 70000, "bid_ratio": 0.30}
+    # bid_ratio 0.30 < (1 - 0.6) = 0.4 → anomaly bid_ratio gate passes
+    # confidence = 0.85*0.5 + 1.0*0.3 + 1.0*0.2 = 0.425 + 0.3 + 0.2 = 0.925 > 0.7
+
+    generate_signals(state, dedup_mock, _settings())
+
+    assert "005930" in state.signals
+    sig = state.signals["005930"]
+    assert sig["action"] == "sell"
+    assert sig["context"]["sell_reason"] == "anomaly"
+    assert sig["confidence_webai"] > 0.7

ai_trade/tests/test_stock_client.py

@@ -0,0 +1,168 @@
+"""Tests for stock_client.StockClient."""
+import asyncio
+import logging
+import pytest
+import httpx
+
+from ai_trade.stock_client import StockClient
+
+
+BASE_URL = "https://test.stock.local"
+API_KEY = "test-secret"
+
+
+async def test_get_portfolio_normal_returns_dict_with_pnl_pct(mock_stock_api):
+    """정상 200 응답 + cache 저장."""
+    mock_stock_api.get("/api/webai/portfolio").mock(
+        return_value=httpx.Response(
+            200,
+            json={
+                "holdings": [{"ticker": "005930", "pnl_pct": 0.047}],
+                "cash": [],
+                "summary": {},
+            },
+        )
+    )
+    client = StockClient(BASE_URL, API_KEY)
+    try:
+        result = await client.get_portfolio()
+        assert result["holdings"][0]["pnl_pct"] == 0.047
+        # Cache populated
+        assert len(client._cache) >= 1
+    finally:
+        await client.close()
+
+
+async def test_get_portfolio_uses_cache_within_ttl(mock_stock_api):
+    """180s TTL 내 두번째 호출 = mock 콜 1회."""
+    route = mock_stock_api.get("/api/webai/portfolio").mock(
+        return_value=httpx.Response(
+            200, json={"holdings": [], "cash": [], "summary": {}}
+        )
+    )
+    client = StockClient(BASE_URL, API_KEY)
+    try:
+        await client.get_portfolio()
+        await client.get_portfolio()  # second call within TTL
+        assert route.call_count == 1
+    finally:
+        await client.close()
+
+
+async def test_get_portfolio_refetches_after_ttl_expiry(mock_stock_api, monkeypatch):
+    """TTL 만료 후 재호출 = mock 콜 2회. time.monotonic 모킹."""
+    route = mock_stock_api.get("/api/webai/portfolio").mock(
+        return_value=httpx.Response(
+            200, json={"holdings": [], "cash": [], "summary": {}}
+        )
+    )
+    # Fake clock: starts at 0, jumps past portfolio TTL (180s) between calls
+    fake_time = [0.0]
+    monkeypatch.setattr(
+        "ai_trade.stock_client.time.monotonic", lambda: fake_time[0]
+    )
+
+    client = StockClient(BASE_URL, API_KEY)
+    try:
+        await client.get_portfolio()
+        fake_time[0] = 181.0  # 180s TTL 만료
+        await client.get_portfolio()
+        assert route.call_count == 2
+    finally:
+        await client.close()
+
+
+async def test_get_portfolio_retries_3_times_on_timeout(mock_stock_api, monkeypatch):
+    """timeout 2번 + 200 1번 → 최종 성공. exponential sleep 호출 검증."""
+    sleep_calls = []
+
+    async def fake_sleep(s):
+        sleep_calls.append(s)
+
+    monkeypatch.setattr("asyncio.sleep", fake_sleep)
+
+    mock_stock_api.get("/api/webai/portfolio").mock(
+        side_effect=[
+            httpx.TimeoutException("timeout 1"),
+            httpx.TimeoutException("timeout 2"),
+            httpx.Response(
+                200, json={"holdings": [], "cash": [], "summary": {}}
+            ),
+        ]
+    )
+    client = StockClient(BASE_URL, API_KEY)
+    try:
+        result = await client.get_portfolio()
+        assert result["holdings"] == []
+        assert sleep_calls == [1, 2]  # exponential 1s, 2s
+    finally:
+        await client.close()
+
+
+async def test_get_portfolio_429_triggers_backoff(mock_stock_api, monkeypatch):
+    """429 → 1s backoff → 200."""
+    sleep_calls = []
+
+    async def fake_sleep(s):
+        sleep_calls.append(s)
+
+    monkeypatch.setattr("asyncio.sleep", fake_sleep)
+
+    mock_stock_api.get("/api/webai/portfolio").mock(
+        side_effect=[
+            httpx.Response(429, text="rate limit"),
+            httpx.Response(
+                200, json={"holdings": [], "cash": [], "summary": {}}
+            ),
+        ]
+    )
+    client = StockClient(BASE_URL, API_KEY)
+    try:
+        result = await client.get_portfolio()
+        assert result["holdings"] == []
+        assert sleep_calls == [1]
+    finally:
+        await client.close()
+
+
+async def test_get_portfolio_falls_back_to_stale_on_all_failures(
+    mock_stock_api, monkeypatch, caplog
+):
+    """cache 에 이전 성공 응답 + 모든 retry 5xx → stale 반환 + logger.warning."""
+    # No-op sleep for fast test
+    async def fake_sleep(s):
+        return None
+    monkeypatch.setattr("asyncio.sleep", fake_sleep)
+
+    # Patch time.monotonic BEFORE first call so cached timestamp uses fake clock
+    fake_time = [0.0]
+    monkeypatch.setattr(
+        "ai_trade.stock_client.time.monotonic", lambda: fake_time[0]
+    )
+
+    # First call succeeds
+    route1 = mock_stock_api.get("/api/webai/portfolio").mock(
+        return_value=httpx.Response(
+            200,
+            json={"holdings": [{"ticker": "005930"}], "cash": [], "summary": {}},
+        )
+    )
+    client = StockClient(BASE_URL, API_KEY)
+    try:
+        first = await client.get_portfolio()
+        assert first["holdings"][0]["ticker"] == "005930"
+
+        # Advance fake clock past TTL (180s) so cache is stale
+        fake_time[0] = 181.0
+
+        # Now mock to return 500s persistently
+        route1.mock(return_value=httpx.Response(500, text="server error"))
+
+        with caplog.at_level(logging.WARNING, logger="ai_trade.stock_client"):
+            result = await client.get_portfolio()
+            assert result["holdings"][0]["ticker"] == "005930"  # stale data returned
+            assert any(
+                "stale" in rec.message.lower() for rec in caplog.records
+            )
+    finally:
+        await client.close()

ai_trade/tests/test_stock_client_ttl.py

@@ -0,0 +1,18 @@
+# tests/test_stock_client_ttl.py
+"""SP-A1 회귀 — _TTL이 NAS 부담 완화를 위한 값으로 설정되어 있어야 함."""
+from ai_trade.stock_client import _TTL
+
+
+def test_portfolio_ttl_is_180s():
+    """portfolio TTL은 180초 이상 (3분 폴링에서 1회 fetch가 3 폴링 커버)."""
+    assert _TTL["portfolio"] >= 180.0
+
+
+def test_news_sentiment_ttl_is_600s():
+    """news-sentiment TTL은 600초 이상 (10분, 뉴스 sentiment는 자주 안 바뀜)."""
+    assert _TTL["news-sentiment"] >= 600.0
+
+
+def test_screener_preview_ttl_is_300s():
+    """screener-preview TTL은 300초 이상 (5분, Top-20은 분 단위로 거의 안 바뀜)."""
+    assert _TTL["screener-preview"] >= 300.0