feat: US market code 정합성, Telegram 명령 4종, 손절 모니터링 (#132)

- MARKET_SHORTHAND + expand_market_codes()로 config "US" → schedule "US_NASDAQ/NYSE/AMEX" 자동 확장
- /report, /scenarios, /review, /dashboard 텔레그램 명령 추가
- price_change_pct를 trading_cycle과 run_daily_session에 주입
- HOLD시 get_open_position 기반 손절 모니터링 및 자동 SELL 오버라이드
- 대시보드 /api/status 동적 market 조회로 변경

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

pyproject.toml

@@ -9,6 +9,8 @@ dependencies = [
     "pydantic-settings>=2.1,<3",
     "google-genai>=1.0,<2",
     "scipy>=1.11,<2",
+    "fastapi>=0.110,<1",
+    "uvicorn>=0.29,<1",
 ]
 
 [project.optional-dependencies]

src/config.py

@@ -83,6 +83,11 @@ class Settings(BaseSettings):
     TELEGRAM_COMMANDS_ENABLED: bool = True
     TELEGRAM_POLLING_INTERVAL: float = 1.0  # seconds
 
+    # Dashboard (optional)
+    DASHBOARD_ENABLED: bool = False
+    DASHBOARD_HOST: str = "127.0.0.1"
+    DASHBOARD_PORT: int = Field(default=8080, ge=1, le=65535)
+
     model_config = {"env_file": ".env", "env_file_encoding": "utf-8"}
 
     @property
@@ -96,4 +101,7 @@ class Settings(BaseSettings):
     @property
     def enabled_market_list(self) -> list[str]:
         """Parse ENABLED_MARKETS into list of market codes."""
-        return [m.strip() for m in self.ENABLED_MARKETS.split(",") if m.strip()]
+        from src.markets.schedule import expand_market_codes
+
+        raw = [m.strip() for m in self.ENABLED_MARKETS.split(",") if m.strip()]
+        return expand_market_codes(raw)

src/dashboard/__init__.py

@@ -0,0 +1,5 @@
+"""FastAPI dashboard package for observability APIs."""
+
+from src.dashboard.app import create_dashboard_app
+
+__all__ = ["create_dashboard_app"]

src/dashboard/app.py

@@ -0,0 +1,361 @@
+"""FastAPI application for observability dashboard endpoints."""
+
+from __future__ import annotations
+
+import json
+import sqlite3
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+from fastapi import FastAPI, HTTPException, Query
+from fastapi.responses import FileResponse
+
+
+def create_dashboard_app(db_path: str) -> FastAPI:
+    """Create dashboard FastAPI app bound to a SQLite database path."""
+    app = FastAPI(title="The Ouroboros Dashboard", version="1.0.0")
+    app.state.db_path = db_path
+
+    @app.get("/")
+    def index() -> FileResponse:
+        index_path = Path(__file__).parent / "static" / "index.html"
+        return FileResponse(index_path)
+
+    @app.get("/api/status")
+    def get_status() -> dict[str, Any]:
+        today = datetime.now(UTC).date().isoformat()
+        with _connect(db_path) as conn:
+            market_rows = conn.execute(
+                """
+                SELECT DISTINCT market FROM (
+                    SELECT market FROM trades WHERE DATE(timestamp) = ?
+                    UNION
+                    SELECT market FROM decision_logs WHERE DATE(timestamp) = ?
+                    UNION
+                    SELECT market FROM playbooks WHERE date = ?
+                ) ORDER BY market
+                """,
+                (today, today, today),
+            ).fetchall()
+            markets = [row[0] for row in market_rows] if market_rows else []
+            market_status: dict[str, Any] = {}
+            total_trades = 0
+            total_pnl = 0.0
+            total_decisions = 0
+            for market in markets:
+                trade_row = conn.execute(
+                    """
+                    SELECT COUNT(*) AS c, COALESCE(SUM(pnl), 0.0) AS p
+                    FROM trades
+                    WHERE DATE(timestamp) = ? AND market = ?
+                    """,
+                    (today, market),
+                ).fetchone()
+                decision_row = conn.execute(
+                    """
+                    SELECT COUNT(*) AS c
+                    FROM decision_logs
+                    WHERE DATE(timestamp) = ? AND market = ?
+                    """,
+                    (today, market),
+                ).fetchone()
+                playbook_row = conn.execute(
+                    """
+                    SELECT status
+                    FROM playbooks
+                    WHERE date = ? AND market = ?
+                    LIMIT 1
+                    """,
+                    (today, market),
+                ).fetchone()
+                market_status[market] = {
+                    "trade_count": int(trade_row["c"] if trade_row else 0),
+                    "total_pnl": float(trade_row["p"] if trade_row else 0.0),
+                    "decision_count": int(decision_row["c"] if decision_row else 0),
+                    "playbook_status": playbook_row["status"] if playbook_row else None,
+                }
+                total_trades += market_status[market]["trade_count"]
+                total_pnl += market_status[market]["total_pnl"]
+                total_decisions += market_status[market]["decision_count"]
+
+            return {
+                "date": today,
+                "markets": market_status,
+                "totals": {
+                    "trade_count": total_trades,
+                    "total_pnl": round(total_pnl, 2),
+                    "decision_count": total_decisions,
+                },
+            }
+
+    @app.get("/api/playbook/{date_str}")
+    def get_playbook(date_str: str, market: str = Query("KR")) -> dict[str, Any]:
+        with _connect(db_path) as conn:
+            row = conn.execute(
+                """
+                SELECT date, market, status, playbook_json, generated_at,
+                       token_count, scenario_count, match_count
+                FROM playbooks
+                WHERE date = ? AND market = ?
+                """,
+                (date_str, market),
+            ).fetchone()
+            if row is None:
+                raise HTTPException(status_code=404, detail="playbook not found")
+            return {
+                "date": row["date"],
+                "market": row["market"],
+                "status": row["status"],
+                "playbook": json.loads(row["playbook_json"]),
+                "generated_at": row["generated_at"],
+                "token_count": row["token_count"],
+                "scenario_count": row["scenario_count"],
+                "match_count": row["match_count"],
+            }
+
+    @app.get("/api/scorecard/{date_str}")
+    def get_scorecard(date_str: str, market: str = Query("KR")) -> dict[str, Any]:
+        key = f"scorecard_{market}"
+        with _connect(db_path) as conn:
+            row = conn.execute(
+                """
+                SELECT value
+                FROM contexts
+                WHERE layer = 'L6_DAILY' AND timeframe = ? AND key = ?
+                """,
+                (date_str, key),
+            ).fetchone()
+            if row is None:
+                raise HTTPException(status_code=404, detail="scorecard not found")
+            return {"date": date_str, "market": market, "scorecard": json.loads(row["value"])}
+
+    @app.get("/api/performance")
+    def get_performance(market: str = Query("all")) -> dict[str, Any]:
+        with _connect(db_path) as conn:
+            if market == "all":
+                by_market_rows = conn.execute(
+                    """
+                    SELECT market,
+                           COUNT(*) AS total_trades,
+                           SUM(CASE WHEN pnl > 0 THEN 1 ELSE 0 END) AS wins,
+                           SUM(CASE WHEN pnl < 0 THEN 1 ELSE 0 END) AS losses,
+                           COALESCE(SUM(pnl), 0.0) AS total_pnl,
+                           COALESCE(AVG(confidence), 0.0) AS avg_confidence
+                    FROM trades
+                    GROUP BY market
+                    ORDER BY market
+                    """
+                ).fetchall()
+                combined = _performance_from_rows(by_market_rows)
+                return {
+                    "market": "all",
+                    "combined": combined,
+                    "by_market": [
+                        _row_to_performance(row)
+                        for row in by_market_rows
+                    ],
+                }
+
+            row = conn.execute(
+                """
+                SELECT market,
+                       COUNT(*) AS total_trades,
+                       SUM(CASE WHEN pnl > 0 THEN 1 ELSE 0 END) AS wins,
+                       SUM(CASE WHEN pnl < 0 THEN 1 ELSE 0 END) AS losses,
+                       COALESCE(SUM(pnl), 0.0) AS total_pnl,
+                       COALESCE(AVG(confidence), 0.0) AS avg_confidence
+                FROM trades
+                WHERE market = ?
+                GROUP BY market
+                """,
+                (market,),
+            ).fetchone()
+            if row is None:
+                return {"market": market, "metrics": _empty_performance(market)}
+            return {"market": market, "metrics": _row_to_performance(row)}
+
+    @app.get("/api/context/{layer}")
+    def get_context_layer(
+        layer: str,
+        timeframe: str | None = Query(default=None),
+        limit: int = Query(default=100, ge=1, le=1000),
+    ) -> dict[str, Any]:
+        with _connect(db_path) as conn:
+            if timeframe is None:
+                rows = conn.execute(
+                    """
+                    SELECT timeframe, key, value, updated_at
+                    FROM contexts
+                    WHERE layer = ?
+                    ORDER BY updated_at DESC
+                    LIMIT ?
+                    """,
+                    (layer, limit),
+                ).fetchall()
+            else:
+                rows = conn.execute(
+                    """
+                    SELECT timeframe, key, value, updated_at
+                    FROM contexts
+                    WHERE layer = ? AND timeframe = ?
+                    ORDER BY key
+                    LIMIT ?
+                    """,
+                    (layer, timeframe, limit),
+                ).fetchall()
+
+            entries = [
+                {
+                    "timeframe": row["timeframe"],
+                    "key": row["key"],
+                    "value": json.loads(row["value"]),
+                    "updated_at": row["updated_at"],
+                }
+                for row in rows
+            ]
+            return {
+                "layer": layer,
+                "timeframe": timeframe,
+                "count": len(entries),
+                "entries": entries,
+            }
+
+    @app.get("/api/decisions")
+    def get_decisions(
+        market: str = Query("KR"),
+        limit: int = Query(default=50, ge=1, le=500),
+    ) -> dict[str, Any]:
+        with _connect(db_path) as conn:
+            rows = conn.execute(
+                """
+                SELECT decision_id, timestamp, stock_code, market, exchange_code,
+                       action, confidence, rationale, context_snapshot, input_data,
+                       outcome_pnl, outcome_accuracy
+                FROM decision_logs
+                WHERE market = ?
+                ORDER BY timestamp DESC
+                LIMIT ?
+                """,
+                (market, limit),
+            ).fetchall()
+            decisions = []
+            for row in rows:
+                decisions.append(
+                    {
+                        "decision_id": row["decision_id"],
+                        "timestamp": row["timestamp"],
+                        "stock_code": row["stock_code"],
+                        "market": row["market"],
+                        "exchange_code": row["exchange_code"],
+                        "action": row["action"],
+                        "confidence": row["confidence"],
+                        "rationale": row["rationale"],
+                        "context_snapshot": json.loads(row["context_snapshot"]),
+                        "input_data": json.loads(row["input_data"]),
+                        "outcome_pnl": row["outcome_pnl"],
+                        "outcome_accuracy": row["outcome_accuracy"],
+                    }
+                )
+            return {"market": market, "count": len(decisions), "decisions": decisions}
+
+    @app.get("/api/scenarios/active")
+    def get_active_scenarios(
+        market: str = Query("US"),
+        date_str: str | None = Query(default=None),
+        limit: int = Query(default=50, ge=1, le=500),
+    ) -> dict[str, Any]:
+        if date_str is None:
+            date_str = datetime.now(UTC).date().isoformat()
+
+        with _connect(db_path) as conn:
+            rows = conn.execute(
+                """
+                SELECT timestamp, stock_code, action, confidence, rationale, context_snapshot
+                FROM decision_logs
+                WHERE market = ? AND DATE(timestamp) = ?
+                ORDER BY timestamp DESC
+                LIMIT ?
+                """,
+                (market, date_str, limit),
+            ).fetchall()
+            matches: list[dict[str, Any]] = []
+            for row in rows:
+                snapshot = json.loads(row["context_snapshot"])
+                scenario_match = snapshot.get("scenario_match", {})
+                if not isinstance(scenario_match, dict) or not scenario_match:
+                    continue
+                matches.append(
+                    {
+                        "timestamp": row["timestamp"],
+                        "stock_code": row["stock_code"],
+                        "action": row["action"],
+                        "confidence": row["confidence"],
+                        "rationale": row["rationale"],
+                        "scenario_match": scenario_match,
+                    }
+                )
+            return {"market": market, "date": date_str, "count": len(matches), "matches": matches}
+
+    return app
+
+
+def _connect(db_path: str) -> sqlite3.Connection:
+    conn = sqlite3.connect(db_path)
+    conn.row_factory = sqlite3.Row
+    return conn
+
+
+def _row_to_performance(row: sqlite3.Row) -> dict[str, Any]:
+    wins = int(row["wins"] or 0)
+    losses = int(row["losses"] or 0)
+    total = int(row["total_trades"] or 0)
+    win_rate = round((wins / (wins + losses) * 100), 2) if (wins + losses) > 0 else 0.0
+    return {
+        "market": row["market"],
+        "total_trades": total,
+        "wins": wins,
+        "losses": losses,
+        "win_rate": win_rate,
+        "total_pnl": round(float(row["total_pnl"] or 0.0), 2),
+        "avg_confidence": round(float(row["avg_confidence"] or 0.0), 2),
+    }
+
+
+def _performance_from_rows(rows: list[sqlite3.Row]) -> dict[str, Any]:
+    total_trades = 0
+    wins = 0
+    losses = 0
+    total_pnl = 0.0
+    confidence_weighted = 0.0
+    for row in rows:
+        market_total = int(row["total_trades"] or 0)
+        market_conf = float(row["avg_confidence"] or 0.0)
+        total_trades += market_total
+        wins += int(row["wins"] or 0)
+        losses += int(row["losses"] or 0)
+        total_pnl += float(row["total_pnl"] or 0.0)
+        confidence_weighted += market_total * market_conf
+    win_rate = round((wins / (wins + losses) * 100), 2) if (wins + losses) > 0 else 0.0
+    avg_confidence = round(confidence_weighted / total_trades, 2) if total_trades > 0 else 0.0
+    return {
+        "market": "all",
+        "total_trades": total_trades,
+        "wins": wins,
+        "losses": losses,
+        "win_rate": win_rate,
+        "total_pnl": round(total_pnl, 2),
+        "avg_confidence": avg_confidence,
+    }
+
+
+def _empty_performance(market: str) -> dict[str, Any]:
+    return {
+        "market": market,
+        "total_trades": 0,
+        "wins": 0,
+        "losses": 0,
+        "win_rate": 0.0,
+        "total_pnl": 0.0,
+        "avg_confidence": 0.0,
+    }

src/dashboard/static/index.html

@@ -0,0 +1,61 @@
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>The Ouroboros Dashboard</title>
+    <style>
+      :root {
+        --bg: #0b1724;
+        --panel: #12263a;
+        --fg: #e6eef7;
+        --muted: #9fb3c8;
+        --accent: #3cb371;
+      }
+      body {
+        margin: 0;
+        font-family: ui-monospace, SFMono-Regular, Menlo, monospace;
+        background: radial-gradient(circle at top left, #173b58, var(--bg));
+        color: var(--fg);
+      }
+      .wrap {
+        max-width: 900px;
+        margin: 48px auto;
+        padding: 0 16px;
+      }
+      .card {
+        background: color-mix(in oklab, var(--panel), black 12%);
+        border: 1px solid #28455f;
+        border-radius: 12px;
+        padding: 20px;
+      }
+      h1 {
+        margin-top: 0;
+      }
+      code {
+        color: var(--accent);
+      }
+      li {
+        margin: 6px 0;
+        color: var(--muted);
+      }
+    </style>
+  </head>
+  <body>
+    <div class="wrap">
+      <div class="card">
+        <h1>The Ouroboros Dashboard API</h1>
+        <p>Use the following endpoints:</p>
+        <ul>
+          <li><code>/api/status</code></li>
+          <li><code>/api/playbook/{date}?market=KR</code></li>
+          <li><code>/api/scorecard/{date}?market=KR</code></li>
+          <li><code>/api/performance?market=all</code></li>
+          <li><code>/api/context/{layer}</code></li>
+          <li><code>/api/decisions?market=KR</code></li>
+          <li><code>/api/scenarios/active?market=US</code></li>
+        </ul>
+      </div>
+    </div>
+  </body>
+</html>

src/db.py

@@ -214,3 +214,24 @@ def get_latest_buy_trade(
     if not row:
         return None
     return {"decision_id": row[0], "price": row[1], "quantity": row[2]}
+
+
+def get_open_position(
+    conn: sqlite3.Connection, stock_code: str, market: str
+) -> dict[str, Any] | None:
+    """Return open position if latest trade is BUY, else None."""
+    cursor = conn.execute(
+        """
+        SELECT action, decision_id, price, quantity
+        FROM trades
+        WHERE stock_code = ?
+          AND market = ?
+        ORDER BY timestamp DESC
+        LIMIT 1
+        """,
+        (stock_code, market),
+    )
+    row = cursor.fetchone()
+    if not row or row[0] != "BUY":
+        return None
+    return {"decision_id": row[1], "price": row[2], "quantity": row[3]}

src/main.py

@@ -8,8 +8,10 @@ from __future__ import annotations
 
 import argparse
 import asyncio
+import json
 import logging
 import signal
+import threading
 from datetime import UTC, datetime
 from typing import Any
 
@@ -27,8 +29,9 @@ from src.context.store import ContextStore
 from src.core.criticality import CriticalityAssessor
 from src.core.priority_queue import PriorityTaskQueue
 from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected, RiskManager
-from src.db import get_latest_buy_trade, init_db, log_trade
+from src.db import get_latest_buy_trade, get_open_position, init_db, log_trade
 from src.evolution.daily_review import DailyReviewer
+from src.evolution.optimizer import EvolutionOptimizer
 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
@@ -112,6 +115,7 @@ async def trading_cycle(
 
         current_price = safe_float(orderbook.get("output1", {}).get("stck_prpr", "0"))
         foreigner_net = safe_float(orderbook.get("output1", {}).get("frgn_ntby_qty", "0"))
+        price_change_pct = safe_float(orderbook.get("output1", {}).get("prdy_ctrt", "0"))
     else:
         # Overseas market
         price_data = await overseas_broker.get_overseas_price(
@@ -134,6 +138,7 @@ async def trading_cycle(
 
         current_price = safe_float(price_data.get("output", {}).get("last", "0"))
         foreigner_net = 0.0  # Not available for overseas
+        price_change_pct = safe_float(price_data.get("output", {}).get("rate", "0"))
 
     # Calculate daily P&L %
     pnl_pct = (
@@ -147,6 +152,7 @@ async def trading_cycle(
         "market_name": market.name,
         "current_price": current_price,
         "foreigner_net": foreigner_net,
+        "price_change_pct": price_change_pct,
     }
 
     # Enrich market_data with scanner metrics for scenario engine
@@ -238,6 +244,34 @@ async def trading_cycle(
         confidence=match.confidence,
         rationale=match.rationale,
     )
+    stock_playbook = playbook.get_stock_playbook(stock_code)
+
+    if decision.action == "HOLD":
+        open_position = get_open_position(db_conn, stock_code, market.code)
+        if open_position:
+            entry_price = safe_float(open_position.get("price"), 0.0)
+            if entry_price > 0:
+                loss_pct = (current_price - entry_price) / entry_price * 100
+                stop_loss_threshold = -2.0
+                if stock_playbook and stock_playbook.scenarios:
+                    stop_loss_threshold = stock_playbook.scenarios[0].stop_loss_pct
+
+                if loss_pct <= stop_loss_threshold:
+                    decision = TradeDecision(
+                        action="SELL",
+                        confidence=95,
+                        rationale=(
+                            f"Stop-loss triggered ({loss_pct:.2f}% <= "
+                            f"{stop_loss_threshold:.2f}%)"
+                        ),
+                    )
+                    logger.info(
+                        "Stop-loss override for %s (%s): %.2f%% <= %.2f%%",
+                        stock_code,
+                        market.name,
+                        loss_pct,
+                        stop_loss_threshold,
+                    )
     logger.info(
         "Decision for %s (%s): %s (confidence=%d)",
         stock_code,
@@ -276,6 +310,7 @@ async def trading_cycle(
     input_data = {
         "current_price": current_price,
         "foreigner_net": foreigner_net,
+        "price_change_pct": price_change_pct,
         "total_eval": total_eval,
         "total_cash": total_cash,
         "pnl_pct": pnl_pct,
@@ -505,6 +540,9 @@ async def run_daily_session(
                     foreigner_net = safe_float(
                         orderbook.get("output1", {}).get("frgn_ntby_qty", "0")
                     )
+                    price_change_pct = safe_float(
+                        orderbook.get("output1", {}).get("prdy_ctrt", "0")
+                    )
                 else:
                     price_data = await overseas_broker.get_overseas_price(
                         market.exchange_code, stock_code
@@ -513,12 +551,16 @@ async def run_daily_session(
                         price_data.get("output", {}).get("last", "0")
                     )
                     foreigner_net = 0.0
+                    price_change_pct = safe_float(
+                        price_data.get("output", {}).get("rate", "0")
+                    )
 
                 stock_data: dict[str, Any] = {
                     "stock_code": stock_code,
                     "market_name": market.name,
                     "current_price": current_price,
                     "foreigner_net": foreigner_net,
+                    "price_change_pct": price_change_pct,
                 }
                 # Enrich with scanner metrics
                 cand = candidate_map.get(stock_code)
@@ -745,6 +787,7 @@ async def _handle_market_close(
     telegram: TelegramClient,
     context_aggregator: ContextAggregator,
     daily_reviewer: DailyReviewer,
+    evolution_optimizer: EvolutionOptimizer | None = None,
 ) -> None:
     """Handle market-close tasks: notify, aggregate, review, and store context."""
     await telegram.notify_market_close(market_name, 0.0)
@@ -772,6 +815,14 @@ async def _handle_market_close(
         f"Lessons: {', '.join(scorecard.lessons) if scorecard.lessons else 'N/A'}"
     )
 
+    if evolution_optimizer is not None:
+        await _run_evolution_loop(
+            evolution_optimizer=evolution_optimizer,
+            telegram=telegram,
+            market_code=market_code,
+            market_date=market_date,
+        )
+
 
 def _run_context_scheduler(
     scheduler: ContextScheduler, now: datetime | None = None,
@@ -802,6 +853,80 @@ def _run_context_scheduler(
         )
 
 
+async def _run_evolution_loop(
+    evolution_optimizer: EvolutionOptimizer,
+    telegram: TelegramClient,
+    market_code: str,
+    market_date: str,
+) -> None:
+    """Run evolution loop once at US close (end of trading day)."""
+    if not market_code.startswith("US"):
+        return
+
+    try:
+        pr_info = await evolution_optimizer.evolve()
+    except Exception as exc:
+        logger.warning("Evolution loop failed on %s: %s", market_date, exc)
+        return
+
+    if pr_info is None:
+        logger.info("Evolution loop skipped on %s (no actionable failures)", market_date)
+        return
+
+    try:
+        await telegram.send_message(
+            "<b>Evolution Update</b>\n"
+            f"Date: {market_date}\n"
+            f"PR: {pr_info.get('title', 'N/A')}\n"
+            f"Branch: {pr_info.get('branch', 'N/A')}\n"
+            f"Status: {pr_info.get('status', 'N/A')}"
+        )
+    except Exception as exc:
+        logger.warning("Evolution notification failed on %s: %s", market_date, exc)
+
+
+def _start_dashboard_server(settings: Settings) -> threading.Thread | None:
+    """Start FastAPI dashboard in a daemon thread when enabled."""
+    if not settings.DASHBOARD_ENABLED:
+        return None
+
+    def _serve() -> None:
+        try:
+            import uvicorn
+
+            from src.dashboard import create_dashboard_app
+
+            app = create_dashboard_app(settings.DB_PATH)
+            uvicorn.run(
+                app,
+                host=settings.DASHBOARD_HOST,
+                port=settings.DASHBOARD_PORT,
+                log_level="info",
+            )
+        except Exception as exc:
+            logger.warning("Dashboard server failed to start: %s", exc)
+
+    thread = threading.Thread(
+        target=_serve,
+        name="dashboard-server",
+        daemon=True,
+    )
+    thread.start()
+    logger.info(
+        "Dashboard server started at http://%s:%d",
+        settings.DASHBOARD_HOST,
+        settings.DASHBOARD_PORT,
+    )
+    return thread
+
+
+def _apply_dashboard_flag(settings: Settings, dashboard_flag: bool) -> Settings:
+    """Apply CLI dashboard flag over environment settings."""
+    if dashboard_flag and not settings.DASHBOARD_ENABLED:
+        return settings.model_copy(update={"DASHBOARD_ENABLED": True})
+    return settings
+
+
 async def run(settings: Settings) -> None:
     """Main async loop — iterate over open markets on a timer."""
     broker = KISBroker(settings)
@@ -816,6 +941,7 @@ async def run(settings: Settings) -> None:
         aggregator=context_aggregator,
         store=context_store,
     )
+    evolution_optimizer = EvolutionOptimizer(settings)
 
     # V2 proactive strategy components
     context_selector = ContextSelector(context_store)
@@ -850,6 +976,10 @@ async def run(settings: Settings) -> None:
             "/help - Show available commands\n"
             "/status - Trading status (mode, markets, P&L)\n"
             "/positions - Current holdings\n"
+            "/report - Daily summary report\n"
+            "/scenarios - Today's playbook scenarios\n"
+            "/review - Recent scorecards\n"
+            "/dashboard - Dashboard URL/status\n"
             "/stop - Pause trading\n"
             "/resume - Resume trading"
         )
@@ -969,11 +1099,164 @@ async def run(settings: Settings) -> None:
                 "<b>⚠️ Error</b>\n\nFailed to retrieve positions."
             )
 
+    async def handle_report() -> None:
+        """Handle /report command - show daily summary metrics."""
+        try:
+            today = datetime.now(UTC).date().isoformat()
+            trade_row = db_conn.execute(
+                """
+                SELECT COUNT(*) AS trade_count,
+                       COALESCE(SUM(pnl), 0.0) AS total_pnl,
+                       SUM(CASE WHEN pnl > 0 THEN 1 ELSE 0 END) AS wins
+                FROM trades
+                WHERE DATE(timestamp) = ?
+                """,
+                (today,),
+            ).fetchone()
+            decision_row = db_conn.execute(
+                """
+                SELECT COUNT(*) AS decision_count,
+                       COALESCE(AVG(confidence), 0.0) AS avg_confidence
+                FROM decision_logs
+                WHERE DATE(timestamp) = ?
+                """,
+                (today,),
+            ).fetchone()
+
+            trade_count = int(trade_row[0] if trade_row else 0)
+            total_pnl = float(trade_row[1] if trade_row else 0.0)
+            wins = int(trade_row[2] if trade_row and trade_row[2] is not None else 0)
+            decision_count = int(decision_row[0] if decision_row else 0)
+            avg_confidence = float(decision_row[1] if decision_row else 0.0)
+            win_rate = (wins / trade_count * 100.0) if trade_count > 0 else 0.0
+
+            await telegram.send_message(
+                "<b>📈 Daily Report</b>\n\n"
+                f"<b>Date:</b> {today}\n"
+                f"<b>Trades:</b> {trade_count}\n"
+                f"<b>Total P&L:</b> {total_pnl:+.2f}\n"
+                f"<b>Win Rate:</b> {win_rate:.2f}%\n"
+                f"<b>Decisions:</b> {decision_count}\n"
+                f"<b>Avg Confidence:</b> {avg_confidence:.2f}"
+            )
+        except Exception as exc:
+            logger.error("Error in /report handler: %s", exc)
+            await telegram.send_message(
+                "<b>⚠️ Error</b>\n\nFailed to generate daily report."
+            )
+
+    async def handle_scenarios() -> None:
+        """Handle /scenarios command - show today's playbook scenarios."""
+        try:
+            today = datetime.now(UTC).date().isoformat()
+            rows = db_conn.execute(
+                """
+                SELECT market, playbook_json
+                FROM playbooks
+                WHERE date = ?
+                ORDER BY market
+                """,
+                (today,),
+            ).fetchall()
+
+            if not rows:
+                await telegram.send_message(
+                    "<b>🧠 Today's Scenarios</b>\n\nNo playbooks found for today."
+                )
+                return
+
+            lines = ["<b>🧠 Today's Scenarios</b>", ""]
+            for market, playbook_json in rows:
+                lines.append(f"<b>{market}</b>")
+                playbook_data = {}
+                try:
+                    playbook_data = json.loads(playbook_json)
+                except Exception:
+                    playbook_data = {}
+
+                stock_playbooks = playbook_data.get("stock_playbooks", [])
+                if not stock_playbooks:
+                    lines.append("- No scenarios")
+                    lines.append("")
+                    continue
+
+                for stock_pb in stock_playbooks:
+                    stock_code = stock_pb.get("stock_code", "N/A")
+                    scenarios = stock_pb.get("scenarios", [])
+                    for sc in scenarios:
+                        action = sc.get("action", "HOLD")
+                        confidence = sc.get("confidence", 0)
+                        lines.append(f"- {stock_code}: {action} ({confidence})")
+                lines.append("")
+
+            await telegram.send_message("\n".join(lines).strip())
+        except Exception as exc:
+            logger.error("Error in /scenarios handler: %s", exc)
+            await telegram.send_message(
+                "<b>⚠️ Error</b>\n\nFailed to retrieve scenarios."
+            )
+
+    async def handle_review() -> None:
+        """Handle /review command - show recent scorecards."""
+        try:
+            rows = db_conn.execute(
+                """
+                SELECT timeframe, key, value
+                FROM contexts
+                WHERE layer = 'L6_DAILY' AND key LIKE 'scorecard_%'
+                ORDER BY updated_at DESC
+                LIMIT 5
+                """
+            ).fetchall()
+
+            if not rows:
+                await telegram.send_message(
+                    "<b>📝 Recent Reviews</b>\n\nNo scorecards available."
+                )
+                return
+
+            lines = ["<b>📝 Recent Reviews</b>", ""]
+            for timeframe, key, value in rows:
+                scorecard = json.loads(value)
+                market = key.replace("scorecard_", "")
+                total_pnl = float(scorecard.get("total_pnl", 0.0))
+                win_rate = float(scorecard.get("win_rate", 0.0))
+                decisions = int(scorecard.get("total_decisions", 0))
+                lines.append(
+                    f"- {timeframe} {market}: P&L {total_pnl:+.2f}, "
+                    f"Win {win_rate:.2f}%, Decisions {decisions}"
+                )
+
+            await telegram.send_message("\n".join(lines))
+        except Exception as exc:
+            logger.error("Error in /review handler: %s", exc)
+            await telegram.send_message(
+                "<b>⚠️ Error</b>\n\nFailed to retrieve reviews."
+            )
+
+    async def handle_dashboard() -> None:
+        """Handle /dashboard command - show dashboard URL if enabled."""
+        if not settings.DASHBOARD_ENABLED:
+            await telegram.send_message(
+                "<b>🖥️ Dashboard</b>\n\nDashboard is not enabled."
+            )
+            return
+
+        url = f"http://{settings.DASHBOARD_HOST}:{settings.DASHBOARD_PORT}"
+        await telegram.send_message(
+            "<b>🖥️ Dashboard</b>\n\n"
+            f"<b>URL:</b> {url}"
+        )
+
     command_handler.register_command("help", handle_help)
     command_handler.register_command("stop", handle_stop)
     command_handler.register_command("resume", handle_resume)
     command_handler.register_command("status", handle_status)
     command_handler.register_command("positions", handle_positions)
+    command_handler.register_command("report", handle_report)
+    command_handler.register_command("scenarios", handle_scenarios)
+    command_handler.register_command("review", handle_review)
+    command_handler.register_command("dashboard", handle_dashboard)
 
     # Initialize volatility hunter
     volatility_analyzer = VolatilityAnalyzer(min_volume_surge=2.0, min_price_change=1.0)
@@ -999,6 +1282,7 @@ async def run(settings: Settings) -> None:
         low_volatility_threshold=30.0,
     )
     priority_queue = PriorityTaskQueue(max_size=1000)
+    _start_dashboard_server(settings)
 
     # Track last scan time for each market
     last_scan_time: dict[str, float] = {}
@@ -1109,6 +1393,7 @@ async def run(settings: Settings) -> None:
                                         telegram=telegram,
                                         context_aggregator=context_aggregator,
                                         daily_reviewer=daily_reviewer,
+                                        evolution_optimizer=evolution_optimizer,
                                     )
                             except Exception as exc:
                                 logger.warning("Market close notification failed: %s", exc)
@@ -1351,10 +1636,16 @@ def main() -> None:
         default="paper",
         help="Trading mode (default: paper)",
     )
+    parser.add_argument(
+        "--dashboard",
+        action="store_true",
+        help="Enable FastAPI dashboard server in background thread",
+    )
     args = parser.parse_args()
 
     setup_logging()
     settings = Settings(MODE=args.mode)  # type: ignore[call-arg]
+    settings = _apply_dashboard_flag(settings, args.dashboard)
     asyncio.run(run(settings))
 
 

src/markets/schedule.py

@@ -123,6 +123,23 @@ MARKETS: dict[str, MarketInfo] = {
     ),
 }
 
+MARKET_SHORTHAND: dict[str, list[str]] = {
+    "US": ["US_NASDAQ", "US_NYSE", "US_AMEX"],
+    "CN": ["CN_SHA", "CN_SZA"],
+    "VN": ["VN_HAN", "VN_HCM"],
+}
+
+
+def expand_market_codes(codes: list[str]) -> list[str]:
+    """Expand shorthand market codes into concrete exchange market codes."""
+    expanded: list[str] = []
+    for code in codes:
+        if code in MARKET_SHORTHAND:
+            expanded.extend(MARKET_SHORTHAND[code])
+        else:
+            expanded.append(code)
+    return expanded
+
 
 def is_market_open(market: MarketInfo, now: datetime | None = None) -> bool:
     """

tests/test_daily_review.py

@@ -16,6 +16,10 @@ from src.evolution.daily_review import DailyReviewer
 from src.evolution.scorecard import DailyScorecard
 from src.logging.decision_logger import DecisionLogger
 
+from datetime import UTC, datetime
+
+TODAY = datetime.now(UTC).strftime("%Y-%m-%d")
+
 
 @pytest.fixture
 def db_conn() -> sqlite3.Connection:
@@ -116,7 +120,7 @@ def test_generate_scorecard_market_scoped(
         exchange_code="NASDAQ",
     )
 
-    scorecard = reviewer.generate_scorecard("2026-02-14", "KR")
+    scorecard = reviewer.generate_scorecard(TODAY, "KR")
 
     assert scorecard.market == "KR"
     assert scorecard.total_decisions == 2
@@ -158,7 +162,7 @@ def test_generate_scorecard_top_winners_and_losers(
             decision_id=decision_id,
         )
 
-    scorecard = reviewer.generate_scorecard("2026-02-14", "KR")
+    scorecard = reviewer.generate_scorecard(TODAY, "KR")
     assert scorecard.top_winners == ["005930", "000660"]
     assert scorecard.top_losers == ["035420", "051910"]
 
@@ -167,7 +171,7 @@ def test_generate_scorecard_empty_day(
     db_conn: sqlite3.Connection, context_store: ContextStore,
 ) -> None:
     reviewer = DailyReviewer(db_conn, context_store)
-    scorecard = reviewer.generate_scorecard("2026-02-14", "KR")
+    scorecard = reviewer.generate_scorecard(TODAY, "KR")
 
     assert scorecard.total_decisions == 0
     assert scorecard.total_pnl == 0.0

tests/test_dashboard.py

@@ -0,0 +1,298 @@
+"""Tests for dashboard endpoint handlers."""
+
+from __future__ import annotations
+
+import json
+import sqlite3
+from collections.abc import Callable
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+import pytest
+from fastapi import HTTPException
+from fastapi.responses import FileResponse
+
+from src.dashboard.app import create_dashboard_app
+from src.db import init_db
+
+
+def _seed_db(conn: sqlite3.Connection) -> None:
+    today = datetime.now(UTC).date().isoformat()
+
+    conn.execute(
+        """
+        INSERT INTO playbooks (
+            date, market, status, playbook_json, generated_at,
+            token_count, scenario_count, match_count
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        (
+            "2026-02-14",
+            "KR",
+            "ready",
+            json.dumps({"market": "KR", "stock_playbooks": []}),
+            "2026-02-14T08:30:00+00:00",
+            123,
+            2,
+            1,
+        ),
+    )
+    conn.execute(
+        """
+        INSERT INTO playbooks (
+            date, market, status, playbook_json, generated_at,
+            token_count, scenario_count, match_count
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        (
+            today,
+            "US_NASDAQ",
+            "ready",
+            json.dumps({"market": "US_NASDAQ", "stock_playbooks": []}),
+            f"{today}T08:30:00+00:00",
+            100,
+            1,
+            0,
+        ),
+    )
+    conn.execute(
+        """
+        INSERT INTO contexts (layer, timeframe, key, value, created_at, updated_at)
+        VALUES (?, ?, ?, ?, ?, ?)
+        """,
+        (
+            "L6_DAILY",
+            "2026-02-14",
+            "scorecard_KR",
+            json.dumps({"market": "KR", "total_pnl": 1.5, "win_rate": 60.0}),
+            "2026-02-14T15:30:00+00:00",
+            "2026-02-14T15:30:00+00:00",
+        ),
+    )
+    conn.execute(
+        """
+        INSERT INTO contexts (layer, timeframe, key, value, created_at, updated_at)
+        VALUES (?, ?, ?, ?, ?, ?)
+        """,
+        (
+            "L7_REALTIME",
+            "2026-02-14T10:00:00+00:00",
+            "volatility_KR_005930",
+            json.dumps({"momentum_score": 70.0}),
+            "2026-02-14T10:00:00+00:00",
+            "2026-02-14T10:00:00+00:00",
+        ),
+    )
+    conn.execute(
+        """
+        INSERT INTO decision_logs (
+            decision_id, timestamp, stock_code, market, exchange_code,
+            action, confidence, rationale, context_snapshot, input_data
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        (
+            "d-kr-1",
+            f"{today}T09:10:00+00:00",
+            "005930",
+            "KR",
+            "KRX",
+            "BUY",
+            85,
+            "signal matched",
+            json.dumps({"scenario_match": {"rsi": 28.0}}),
+            json.dumps({"current_price": 70000}),
+        ),
+    )
+    conn.execute(
+        """
+        INSERT INTO decision_logs (
+            decision_id, timestamp, stock_code, market, exchange_code,
+            action, confidence, rationale, context_snapshot, input_data
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        (
+            "d-us-1",
+            f"{today}T21:10:00+00:00",
+            "AAPL",
+            "US_NASDAQ",
+            "NASDAQ",
+            "SELL",
+            80,
+            "no match",
+            json.dumps({"scenario_match": {}}),
+            json.dumps({"current_price": 200}),
+        ),
+    )
+    conn.execute(
+        """
+        INSERT INTO trades (
+            timestamp, stock_code, action, confidence, rationale,
+            quantity, price, pnl, market, exchange_code, selection_context, decision_id
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        (
+            f"{today}T09:11:00+00:00",
+            "005930",
+            "BUY",
+            85,
+            "buy",
+            1,
+            70000,
+            2.0,
+            "KR",
+            "KRX",
+            None,
+            "d-kr-1",
+        ),
+    )
+    conn.execute(
+        """
+        INSERT INTO trades (
+            timestamp, stock_code, action, confidence, rationale,
+            quantity, price, pnl, market, exchange_code, selection_context, decision_id
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        (
+            f"{today}T21:11:00+00:00",
+            "AAPL",
+            "SELL",
+            80,
+            "sell",
+            1,
+            200,
+            -1.0,
+            "US_NASDAQ",
+            "NASDAQ",
+            None,
+            "d-us-1",
+        ),
+    )
+    conn.commit()
+
+
+def _app(tmp_path: Path) -> Any:
+    db_path = tmp_path / "dashboard_test.db"
+    conn = init_db(str(db_path))
+    _seed_db(conn)
+    conn.close()
+    return create_dashboard_app(str(db_path))
+
+
+def _endpoint(app: Any, path: str) -> Callable[..., Any]:
+    for route in app.routes:
+        if getattr(route, "path", None) == path:
+            return route.endpoint
+    raise AssertionError(f"route not found: {path}")
+
+
+def test_index_serves_html(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    index = _endpoint(app, "/")
+    resp = index()
+    assert isinstance(resp, FileResponse)
+    assert "index.html" in str(resp.path)
+
+
+def test_status_endpoint(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_status = _endpoint(app, "/api/status")
+    body = get_status()
+    assert "KR" in body["markets"]
+    assert "US_NASDAQ" in body["markets"]
+    assert "totals" in body
+
+
+def test_playbook_found(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_playbook = _endpoint(app, "/api/playbook/{date_str}")
+    body = get_playbook("2026-02-14", market="KR")
+    assert body["market"] == "KR"
+
+
+def test_playbook_not_found(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_playbook = _endpoint(app, "/api/playbook/{date_str}")
+    with pytest.raises(HTTPException, match="playbook not found"):
+        get_playbook("2026-02-15", market="KR")
+
+
+def test_scorecard_found(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_scorecard = _endpoint(app, "/api/scorecard/{date_str}")
+    body = get_scorecard("2026-02-14", market="KR")
+    assert body["scorecard"]["total_pnl"] == 1.5
+
+
+def test_scorecard_not_found(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_scorecard = _endpoint(app, "/api/scorecard/{date_str}")
+    with pytest.raises(HTTPException, match="scorecard not found"):
+        get_scorecard("2026-02-15", market="KR")
+
+
+def test_performance_all(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_performance = _endpoint(app, "/api/performance")
+    body = get_performance(market="all")
+    assert body["market"] == "all"
+    assert body["combined"]["total_trades"] == 2
+    assert len(body["by_market"]) == 2
+
+
+def test_performance_market_filter(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_performance = _endpoint(app, "/api/performance")
+    body = get_performance(market="KR")
+    assert body["market"] == "KR"
+    assert body["metrics"]["total_trades"] == 1
+
+
+def test_performance_empty_market(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_performance = _endpoint(app, "/api/performance")
+    body = get_performance(market="JP")
+    assert body["metrics"]["total_trades"] == 0
+
+
+def test_context_layer_all(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_context_layer = _endpoint(app, "/api/context/{layer}")
+    body = get_context_layer("L7_REALTIME", timeframe=None, limit=100)
+    assert body["layer"] == "L7_REALTIME"
+    assert body["count"] == 1
+
+
+def test_context_layer_timeframe_filter(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_context_layer = _endpoint(app, "/api/context/{layer}")
+    body = get_context_layer("L6_DAILY", timeframe="2026-02-14", limit=100)
+    assert body["count"] == 1
+    assert body["entries"][0]["key"] == "scorecard_KR"
+
+
+def test_decisions_endpoint(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_decisions = _endpoint(app, "/api/decisions")
+    body = get_decisions(market="KR", limit=50)
+    assert body["count"] == 1
+    assert body["decisions"][0]["decision_id"] == "d-kr-1"
+
+
+def test_scenarios_active_filters_non_matched(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_active_scenarios = _endpoint(app, "/api/scenarios/active")
+    body = get_active_scenarios(
+        market="KR",
+        date_str=datetime.now(UTC).date().isoformat(),
+        limit=50,
+    )
+    assert body["count"] == 1
+    assert body["matches"][0]["stock_code"] == "005930"
+
+
+def test_scenarios_active_empty_when_no_matches(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_active_scenarios = _endpoint(app, "/api/scenarios/active")
+    body = get_active_scenarios(market="US", date_str="2026-02-14", limit=50)
+    assert body["count"] == 0

tests/test_db.py

@@ -0,0 +1,60 @@
+"""Tests for database helper functions."""
+
+from src.db import get_open_position, init_db, log_trade
+
+
+def test_get_open_position_returns_latest_buy() -> None:
+    conn = init_db(":memory:")
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=2,
+        price=70000.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id="d-buy-1",
+    )
+
+    position = get_open_position(conn, "005930", "KR")
+    assert position is not None
+    assert position["decision_id"] == "d-buy-1"
+    assert position["price"] == 70000.0
+    assert position["quantity"] == 2
+
+
+def test_get_open_position_returns_none_when_latest_is_sell() -> None:
+    conn = init_db(":memory:")
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=1,
+        price=70000.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id="d-buy-1",
+    )
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="SELL",
+        confidence=95,
+        rationale="exit",
+        quantity=1,
+        price=71000.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id="d-sell-1",
+    )
+
+    assert get_open_position(conn, "005930", "KR") is 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

tests/test_main.py

@@ -5,13 +5,22 @@ from unittest.mock import ANY, AsyncMock, MagicMock, patch
 
 import pytest
 
+from src.config import Settings
 from src.context.layer import ContextLayer
 from src.context.scheduler import ScheduleResult
 from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected
 from src.db import init_db, log_trade
 from src.evolution.scorecard import DailyScorecard
 from src.logging.decision_logger import DecisionLogger
-from src.main import _handle_market_close, _run_context_scheduler, safe_float, trading_cycle
+from src.main import (
+    _apply_dashboard_flag,
+    _handle_market_close,
+    _run_context_scheduler,
+    _run_evolution_loop,
+    _start_dashboard_server,
+    safe_float,
+    trading_cycle,
+)
 from src.strategy.models import (
     DayPlaybook,
     ScenarioAction,
@@ -107,6 +116,7 @@ class TestTradingCycleTelegramIntegration:
                 "output1": {
                     "stck_prpr": "50000",
                     "frgn_ntby_qty": "100",
+                    "prdy_ctrt": "1.23",
                 }
             }
         )
@@ -738,7 +748,7 @@ class TestScenarioEngineIntegration:
         broker = MagicMock()
         broker.get_orderbook = AsyncMock(
             return_value={
-                "output1": {"stck_prpr": "50000", "frgn_ntby_qty": "100"}
+                "output1": {"stck_prpr": "50000", "frgn_ntby_qty": "100", "prdy_ctrt": "2.50"}
             }
         )
         broker.get_balance = AsyncMock(
@@ -821,6 +831,7 @@ class TestScenarioEngineIntegration:
         assert market_data["rsi"] == 25.0
         assert market_data["volume_ratio"] == 3.5
         assert market_data["current_price"] == 50000.0
+        assert market_data["price_change_pct"] == 2.5
 
         # Portfolio data should include pnl
         assert "portfolio_pnl_pct" in portfolio_data
@@ -1223,6 +1234,107 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
     assert updated_buy.outcome_accuracy == 1
 
 
+@pytest.mark.asyncio
+async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
+    """HOLD decision should be overridden to SELL when stop-loss threshold is breached."""
+    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()
+    broker.get_orderbook = AsyncMock(
+        return_value={"output1": {"stck_prpr": "95", "frgn_ntby_qty": "0", "prdy_ctrt": "-5.0"}}
+    )
+    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,
+        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()
+    assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
+
+
 @pytest.mark.asyncio
 async def test_handle_market_close_runs_daily_review_flow() -> None:
     """Market close should aggregate, create scorecard, lessons, and notify."""
@@ -1298,6 +1410,82 @@ async def test_handle_market_close_without_lessons_stores_once() -> None:
     assert reviewer.store_scorecard_in_context.call_count == 1
 
 
+@pytest.mark.asyncio
+async def test_handle_market_close_triggers_evolution_for_us() -> None:
+    telegram = MagicMock()
+    telegram.notify_market_close = AsyncMock()
+    telegram.send_message = AsyncMock()
+
+    context_aggregator = MagicMock()
+    reviewer = MagicMock()
+    reviewer.generate_scorecard.return_value = DailyScorecard(
+        date="2026-02-14",
+        market="US",
+        total_decisions=2,
+        buys=1,
+        sells=1,
+        holds=0,
+        total_pnl=3.0,
+        win_rate=50.0,
+        avg_confidence=80.0,
+        scenario_match_rate=100.0,
+    )
+    reviewer.generate_lessons = AsyncMock(return_value=[])
+
+    evolution_optimizer = MagicMock()
+    evolution_optimizer.evolve = AsyncMock(return_value=None)
+
+    await _handle_market_close(
+        market_code="US",
+        market_name="United States",
+        market_timezone=UTC,
+        telegram=telegram,
+        context_aggregator=context_aggregator,
+        daily_reviewer=reviewer,
+        evolution_optimizer=evolution_optimizer,
+    )
+
+    evolution_optimizer.evolve.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_handle_market_close_skips_evolution_for_kr() -> None:
+    telegram = MagicMock()
+    telegram.notify_market_close = AsyncMock()
+    telegram.send_message = AsyncMock()
+
+    context_aggregator = MagicMock()
+    reviewer = MagicMock()
+    reviewer.generate_scorecard.return_value = DailyScorecard(
+        date="2026-02-14",
+        market="KR",
+        total_decisions=1,
+        buys=1,
+        sells=0,
+        holds=0,
+        total_pnl=1.0,
+        win_rate=100.0,
+        avg_confidence=90.0,
+        scenario_match_rate=100.0,
+    )
+    reviewer.generate_lessons = AsyncMock(return_value=[])
+
+    evolution_optimizer = MagicMock()
+    evolution_optimizer.evolve = AsyncMock(return_value=None)
+
+    await _handle_market_close(
+        market_code="KR",
+        market_name="Korea",
+        market_timezone=UTC,
+        telegram=telegram,
+        context_aggregator=context_aggregator,
+        daily_reviewer=reviewer,
+        evolution_optimizer=evolution_optimizer,
+    )
+
+    evolution_optimizer.evolve.assert_not_called()
+
+
 def test_run_context_scheduler_invokes_scheduler() -> None:
     """Scheduler helper should call run_if_due with provided datetime."""
     scheduler = MagicMock()
@@ -1306,3 +1494,110 @@ def test_run_context_scheduler_invokes_scheduler() -> None:
     _run_context_scheduler(scheduler, now=datetime(2026, 2, 14, tzinfo=UTC))
 
     scheduler.run_if_due.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_run_evolution_loop_skips_non_us_market() -> None:
+    optimizer = MagicMock()
+    optimizer.evolve = AsyncMock()
+    telegram = MagicMock()
+    telegram.send_message = AsyncMock()
+
+    await _run_evolution_loop(
+        evolution_optimizer=optimizer,
+        telegram=telegram,
+        market_code="KR",
+        market_date="2026-02-14",
+    )
+
+    optimizer.evolve.assert_not_called()
+    telegram.send_message.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_run_evolution_loop_notifies_when_pr_generated() -> None:
+    optimizer = MagicMock()
+    optimizer.evolve = AsyncMock(
+        return_value={
+            "title": "[Evolution] New strategy: v20260214_050000",
+            "branch": "evolution/v20260214_050000",
+            "status": "ready_for_review",
+        }
+    )
+    telegram = MagicMock()
+    telegram.send_message = AsyncMock()
+
+    await _run_evolution_loop(
+        evolution_optimizer=optimizer,
+        telegram=telegram,
+        market_code="US_NASDAQ",
+        market_date="2026-02-14",
+    )
+
+    optimizer.evolve.assert_called_once()
+    telegram.send_message.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_run_evolution_loop_notification_error_is_ignored() -> None:
+    optimizer = MagicMock()
+    optimizer.evolve = AsyncMock(
+        return_value={
+            "title": "[Evolution] New strategy: v20260214_050000",
+            "branch": "evolution/v20260214_050000",
+            "status": "ready_for_review",
+        }
+    )
+    telegram = MagicMock()
+    telegram.send_message = AsyncMock(side_effect=RuntimeError("telegram down"))
+
+    await _run_evolution_loop(
+        evolution_optimizer=optimizer,
+        telegram=telegram,
+        market_code="US_NYSE",
+        market_date="2026-02-14",
+    )
+
+    optimizer.evolve.assert_called_once()
+    telegram.send_message.assert_called_once()
+
+
+def test_apply_dashboard_flag_enables_dashboard() -> None:
+    settings = Settings(
+        KIS_APP_KEY="test_key",
+        KIS_APP_SECRET="test_secret",
+        KIS_ACCOUNT_NO="12345678-01",
+        GEMINI_API_KEY="test_gemini_key",
+        DASHBOARD_ENABLED=False,
+    )
+    updated = _apply_dashboard_flag(settings, dashboard_flag=True)
+    assert updated.DASHBOARD_ENABLED is True
+
+
+def test_start_dashboard_server_disabled_returns_none() -> None:
+    settings = Settings(
+        KIS_APP_KEY="test_key",
+        KIS_APP_SECRET="test_secret",
+        KIS_ACCOUNT_NO="12345678-01",
+        GEMINI_API_KEY="test_gemini_key",
+        DASHBOARD_ENABLED=False,
+    )
+    thread = _start_dashboard_server(settings)
+    assert thread is None
+
+
+def test_start_dashboard_server_enabled_starts_thread() -> None:
+    settings = Settings(
+        KIS_APP_KEY="test_key",
+        KIS_APP_SECRET="test_secret",
+        KIS_ACCOUNT_NO="12345678-01",
+        GEMINI_API_KEY="test_gemini_key",
+        DASHBOARD_ENABLED=True,
+    )
+    mock_thread = MagicMock()
+    with patch("src.main.threading.Thread", return_value=mock_thread) as mock_thread_cls:
+        thread = _start_dashboard_server(settings)
+
+    assert thread == mock_thread
+    mock_thread_cls.assert_called_once()
+    mock_thread.start.assert_called_once()

tests/test_market_schedule.py

@@ -7,6 +7,7 @@ import pytest
 
 from src.markets.schedule import (
     MARKETS,
+    expand_market_codes,
     get_next_market_open,
     get_open_markets,
     is_market_open,
@@ -199,3 +200,28 @@ class TestGetNextMarketOpen:
             enabled_markets=["INVALID", "KR"], now=test_time
         )
         assert market.code == "KR"
+
+
+class TestExpandMarketCodes:
+    """Test shorthand market expansion."""
+
+    def test_expand_us_shorthand(self) -> None:
+        assert expand_market_codes(["US"]) == ["US_NASDAQ", "US_NYSE", "US_AMEX"]
+
+    def test_expand_cn_shorthand(self) -> None:
+        assert expand_market_codes(["CN"]) == ["CN_SHA", "CN_SZA"]
+
+    def test_expand_vn_shorthand(self) -> None:
+        assert expand_market_codes(["VN"]) == ["VN_HAN", "VN_HCM"]
+
+    def test_expand_mixed_codes(self) -> None:
+        assert expand_market_codes(["KR", "US", "JP"]) == [
+            "KR",
+            "US_NASDAQ",
+            "US_NYSE",
+            "US_AMEX",
+            "JP",
+        ]
+
+    def test_expand_preserves_unknown_code(self) -> None:
+        assert expand_market_codes(["KR", "UNKNOWN"]) == ["KR", "UNKNOWN"]

tests/test_telegram_commands.py

@@ -682,6 +682,10 @@ class TestBasicCommands:
                 "/help - Show available commands\n"
                 "/status - Trading status (mode, markets, P&L)\n"
                 "/positions - Current holdings\n"
+                "/report - Daily summary report\n"
+                "/scenarios - Today's playbook scenarios\n"
+                "/review - Recent scorecards\n"
+                "/dashboard - Dashboard URL/status\n"
                 "/stop - Pause trading\n"
                 "/resume - Resume trading"
             )
@@ -707,10 +711,106 @@ class TestBasicCommands:
             assert "/help" in payload["text"]
             assert "/status" in payload["text"]
             assert "/positions" in payload["text"]
+            assert "/report" in payload["text"]
+            assert "/scenarios" in payload["text"]
+            assert "/review" in payload["text"]
+            assert "/dashboard" in payload["text"]
             assert "/stop" in payload["text"]
             assert "/resume" in payload["text"]
 
 
+class TestExtendedCommands:
+    """Test additional bot commands."""
+
+    @pytest.mark.asyncio
+    async def test_report_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_report() -> None:
+            await client.send_message("<b>📈 Daily Report</b>\n\nTrades: 1")
+
+        handler.register_command("report", mock_report)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/report"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Daily Report" in payload["text"]
+
+    @pytest.mark.asyncio
+    async def test_scenarios_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_scenarios() -> None:
+            await client.send_message("<b>🧠 Today's Scenarios</b>\n\n- AAPL: BUY (85)")
+
+        handler.register_command("scenarios", mock_scenarios)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/scenarios"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Today's Scenarios" in payload["text"]
+
+    @pytest.mark.asyncio
+    async def test_review_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_review() -> None:
+            await client.send_message("<b>📝 Recent Reviews</b>\n\n- 2026-02-14 KR")
+
+        handler.register_command("review", mock_review)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/review"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Recent Reviews" in payload["text"]
+
+    @pytest.mark.asyncio
+    async def test_dashboard_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_dashboard() -> None:
+            await client.send_message("<b>🖥️ Dashboard</b>\n\nURL: http://127.0.0.1:8080")
+
+        handler.register_command("dashboard", mock_dashboard)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/dashboard"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Dashboard" in payload["text"]
+
+
 class TestGetUpdates:
     """Test getUpdates API interaction."""