# Changelog ## [Unreleased] - 2026-06-01 ### Added - Added stop-condition risk controls for abnormal source/apply latency and repeated execution failures. - Added a new stop-conditions guard and integration in market feed processing. - Added multi-channel alerting infrastructure with Telegram, Discord webhook, and SMTP channel clients. - Added alert configuration settings for severity threshold, category routing, and dedup cooldown. - Added dashboard alert status surfacing with configured channels and last-send delivery outcome. - Added append-only `audit_events` schema plus repository support for insert/query of recent audit records. - Added dashboard audit fragment and protected API endpoint for recent audit entries. - Added runtime lifecycle manager with startup recovery and graceful shutdown orchestration. - Added `runtime_state_snapshots` persistence for control flags, open trade count, and last known balances. - Added CI security gates for dependency auditing (`pip-audit --strict`) and a repository/worktree secret scan script. - Added strict settings validators for auth pairing, Kraken credential pairing, alert severity bounds, and key-scope policy. - Added synthetic latency profiler scenarios and CLI scripts for baseline generation and regression checks. - Added latency baseline/threshold artifacts and CI latency guardrail enforcement. - Added deterministic replay backtesting engine, CLI script, and unit coverage for JSONL event replay. - Added backtesting parameter sweep support (`scripts/backtest_sweep.py`) for theta, trade-capital, pair-universe, and staleness-threshold grid search. - Added persisted sweep artifacts with ranked in-sample/out-of-sample results and promotion-ready candidate reporting. - Added out-of-sample overfit guards via train/test time-window split and generalization-gap checks. - Added dashboard controls for tradable pair universe selection and strategy mode/parameter configuration. - Added feature-flagged statistical arbitrage experiment scaffold (`src/arbitrade/strategy/stat_arb.py`) with mean-reversion signal lifecycle. - Added strategy feature-flag settings for statistical arbitrage experiment activation and z-score/holding-window controls. - Added unit coverage for statistical arbitrage experiment behavior and new strategy settings validation rules. - Added dedicated backtesting dashboard page (`/dashboard/backtesting`) with run controls for replay path, fee profile, balances, slippage, and execution latency. - Added backtesting run/report endpoints (`/dashboard/backtesting/run`, `/dashboard/api/backtesting/reports`) and recent-report history surfaced in UI. ### Changed - Live execution path now auto-activates the kill switch when configured stop conditions are breached. - Added configuration env keys for stop-condition thresholds. - WebSocket client now emits system alerts for disconnect/reconnect and heartbeat staleness timeout events. - Added explicit Kraken API key permission configuration (`KRAKEN_API_KEY_PERMISSIONS`) and docs for least-privilege key usage. - Optimized dashboard metrics aggregation to use DuckDB SQL aggregates/quantiles instead of Python row scans. - Added backtesting usage and replay format documentation to README. - Dashboard controls now surface tradable pairs and strategy config snapshot values. - CI now publishes `git.allucanget.biz/allucanget/arbitrade:latest`, and README now documents Coolify image deployment with runtime environment variables managed in Coolify. - Dashboard strategy-mode validation now allows `stat_arb_experiment` only when feature flag is enabled. - README now documents deferred cross-exchange architecture requirements, risk assumptions, and promotion milestones for strategy expansion. ### Removed - None. ### Fixed - Added/expanded unit coverage for risk limits and kill-switch enforcement, including stop-condition scenarios. - Added partial-fill recovery logic that cancels open orders when possible and hedges residual exposure on timeout or failure. - Added deterministic order idempotency via Kraken userref plus reconciliation helpers for Kraken order history responses. - Added execution journaling for trades, orders, and estimated P&L, plus a DuckDB startup fallback when the default file path is unavailable. - Added a mocked execution integration test that drives the triangular sequencer through the execution journal and DuckDB persistence. - Added a DuckDB-backed performance metrics calculator for realized P&L, win rate, trade duration, opportunities/min, fill rate, and latency percentiles. - Added dashboard page plus HTMX metrics fragment and SSE metrics stream. - Added dashboard live overview panel for status, balances, open trades, realized P&L, and opportunity feed with HTMX refresh and SSE updates. - Added dashboard controls for start/stop, config edits, and manual kill-switch triggering via HTMX POST forms. - Added Alpine.js interactivity and a Chart.js opportunity trend panel to the dashboard. - Added optional HTTP Basic authentication for dashboard routes, fragments, streams, and control endpoints. - Added alert wiring for dashboard control actions, execution success/failure, and threshold breaches in risk guards. - Added unit/integration tests covering alert notifier behavior and alert emission paths. - Added critical system alert emission when live opportunity executor raises an unhandled exception. - Added WebSocket and market-feed tests for system-event alerting paths. - Added notifier status snapshot tracking and protected alert-status API endpoint for operational visibility. - Added audit event writes for dashboard controls and detector/risk/execution decision points. - Added tests for audit repository and dashboard audit route coverage. - Added startup restart safety guard that halts execution when open trades are detected after restart. - Added lifecycle tests for snapshot persistence, worker draining, recovery restore, and startup reconciliation hook. - Added unit coverage for security-related settings validation paths. - Added latency guardrail unit coverage and documented measured metrics aggregation speedup (`1.14x`). - Added deterministic replay tests that exercise the backtesting path without depending on live services.