feat: Add DART strategy and related configurations

ㅇ
Changes:
- Introduced the DART strategy to the trading system, including its configuration and integration into the existing framework.
- Updated the database schema to include DART-specific tables for disclosures and watchlists.
- Enhanced the backtesting and parameter search functionalities to support the DART strategy.
- Implemented new rules for browser verification and API interactions to ensure compliance with the updated DART strategy.

Impact:
- These additions expand the trading capabilities of the system, allowing for more comprehensive analysis and execution of DART-related strategies, while maintaining system integrity and performance.

kis_trader/backtest/optuna_breakout.py

@@ -207,14 +207,12 @@ def prepare_breakout_search_context(
     fallback_sim_interval = 5
     if not use_fallback_universe and start_ymd and end_ymd:
         try:
-            from kis_trader.database.db_manager import get_db as _get_ext_db
-            _ext = _get_ext_db()
-            history = _ext.get_universe_by_candle_time(
-                strategy_id="BREAKOUT", start_ymd=start_ymd, end_ymd=end_ymd,
+            from kis_trader.backtest.breakout_backtest_common import resolve_breakout_universe
+            history, src, n_bins, _scan_iv = resolve_breakout_universe(
+                start_ymd, end_ymd, use_saved_history=True,
             )
             if history:
                 universe_by_slot = history
-                n_bins = len(history)
                 avg = sum(len(v) for v in history.values()) / max(1, n_bins)
                 logger.info("✅ 유니버스: BREAKOUT 이력 | %s분봉 · 평균 %.1f종목", n_bins, avg)
         except Exception as exc: