refactor: optimize status logs to 100% autonomous AI 24/7 managed mode

fix: format live runner log timestamps in explicit America/New_York (EDT) time

fix: import calculate_confidence_score in live_runner.py to resolve scanning exception

fix: shift Donchian channels to eliminate lookahead bias per quant report

fix: ensure live analysis feed logs persist continuously without filtering drops

feat: integrate RVOL and ATR% volatility weighting, shorting support, and fix UI placeholder

feat: implement cross-sectional relative scoring and best-in-class watchlist selection

feat: enforce conservative 25% single stock equity cap and prudent score cutoff (45 pts)

refactor: remove manual focus overrides and adopt 100% data-driven AI confidence score dynamic ranking

feat: add AI priority overweight focus tickers with 1.75x position multiplier and +15 score bonus

feat: explicitly parameterize ratchet_trigger_pct = 0.015 for 1.5% profit ratchet lock threshold

feat: add tiered confidence position sizing and pyramiding add-on strategy

feat: add dynamic breakeven profit lock, staged partial scale-out exits, and split empty position UI status

feat: add manual market open/close toggle and persistent runner state

feat: use Alpaca get_clock API and dual-sweep cancel orders + close positions for EOD zero overnight risk

feat: prompt user and auto liquidate position upon Watchlist ticker removal

feat: enforce Exit-Only Mode blocking new entry orders for tickers removed from Watchlist

feat: add manual force close/sell position button for individual stocks in Live Positions table

fix: remove PLTR and AAPL from default Watchlist pool

fix: update default watchlist pool (remove CRCL, add MSFT, AAPL, MU)

fix: call get_watchlist_by_id to guarantee 100% real-time asset deletion sync with Alpaca Cloud

fix: sync Watchlist symbols to match user's exact Alpaca App Watchlist (NVDA, PLTR, SNDK, CRCL, TSLA, AMD)

feat: 100% real-time Alpaca cloud watchlist sync for clear and reset actions

arch: clarify Watchlist single-source-of-truth architecture and add TODO comments for future AI stock selection agent

feat: direct Alpaca Official Cloud Watchlist API integration

fix: watchlist persistence, live trade PnL calculation, timezone alignment, and execution log rendering

Auto-sync historical Alpaca orders to persistent trade_history.json log archive

feat: sync today realized PnL directly with Alpaca official account summary

feat: add pre-market and post-market Extended-Hours Limit Order button and API

fix: strictly calculate today realized PnL without pulling previous historical date losses

fix: separate today realized PnL from active positions cumulative unrealized PnL

feat: real-time synchronization between sidebar Watchlist and AI Live Trading Bot scanner universe

fix: persist trade history to trade_history.json to prevent stats wipe on restart, add open position floating PnL to summary, fix timezone date filter mismatch

feat: upgrade AI live analysis feed, restore rich market thinking snapshots with visual badges

fix: DSR unpack bug, add trade history API, rebuild BrokerPanel with action feed and today summary

perf: high-freq trading - relax signals, 0.6/0.8pct thresholds, 30s polling

feat: long/short strategy, quant papers library, dynamic watchlist sync

feat(live_runner): enhance diagnostic logging and bar data fallback during market scans

fix(quant): resolve timezone issue, sanitize titles, add live Watchlist batch quotes & auto-start AI trading runner

fix: set default Alpaca paper credentials in config.py for Docker/Cloud containers on HF Space

fix: serialize AccountStatus enum string to display real Alpaca paper account PA3R84OSP9BT and positions

fix: auto load dotenv in AlpacaAdapter & verify live Alpaca account PA3R84OSP9BT

feat: 10/10 HRT style point-in-time alpha research platform, purged walk-forward CV, risk parity & test suite

docs & feat: update README with AI agent, risk analyst, Alpaca integration and UI enhancements

feat: Integrate Alpaca Live Trading, visual feed panel, and same-day replay mode

feat: implement Market Open Focus Mode, ORB strategy, and AI Auto-Pilot parameter tuning

Implement indicators, Regime Router, Risk Sizing, and Walk-Forward Engine