feat: Add backtesting parameter sweep support and related functionality

README.md

@@ -104,7 +104,7 @@ Minimum `.env` values:
 ```env
 APP_ENV=dev
 APP_HOST=0.0.0.0
-APP_PORT=8000
+APP_PORT=9090
 LOG_LEVEL=INFO
 LOG_JSON=true
 DUCKDB_PATH=./data/arbitrade.duckdb
@@ -132,8 +132,8 @@ python -m arbitrade.main
 
 Health endpoints:
 
-- HTML: `http://localhost:8000/`
-- JSON: `http://localhost:8000/health`
+- HTML: `http://localhost:9090/`
+- JSON: `http://localhost:9090/health`
 
 ## Database
 
@@ -283,12 +283,12 @@ Set these in Coolify application settings:
 - Build Command: leave empty.
 - Install Command: leave empty.
 - Start Command: leave empty unless you explicitly want to override the image default.
-- Port: `8000`
+- Port: `9090` (coolify uses `8000` internally)
 
 ### 3) Configure health check and networking
 
 - Health Check Path: `/health`
-- Exposed Port: `8000`
+- Exposed Port: `9090`
 - Use Coolify-generated domain or attach your own domain.
 
 ### 4) Configure persistent storage
@@ -305,7 +305,7 @@ Add runtime environment variables in Coolify (UI: Environment Variables):
 
 - `APP_ENV=prod`
 - `APP_HOST=0.0.0.0`
-- `APP_PORT=8000`
+- `APP_PORT=9090`
 - `DUCKDB_PATH=/app/data/arbitrade.duckdb`
 - `LOG_LEVEL=INFO`
 - `LOG_JSON=true`
@@ -431,6 +431,12 @@ Run a deterministic replay backtest from a JSONL event stream:
 python scripts/backtest_replay.py --events path\to\replay.jsonl --starting-balances USD=1000.0
 ```
 
+Run parameter sweep with train/test split and promotion scoring:
+
+```powershell
+python scripts/backtest_sweep.py --events path\to\replay.jsonl --starting-balances USD=1000.0 --output ops/backtesting/parameter_sweep_results.json
+```
+
 Replay event format:
 
 ```json
@@ -447,7 +453,9 @@ Notes:
 - Events are replayed in timestamp order.
 - The replay engine reuses the production detector, pre-trade validation, trade limits, and execution sequencer.
 - The simulated execution path applies configurable slippage and execution latency so reports include deterministic trade/miss statistics.
-  Latency baseline and threshold artifacts:
+- Parameter sweep splits replay data into in-sample and out-of-sample windows, ranks configurations by out-of-sample score, and flags overfit via train/test generalization-gap checks.
+- Sweep output persists ranked combinations and promotion-ready candidates for paper-trading canary promotion decisions.
+- Latency baseline and threshold artifacts:
 
 - `ops/performance/latency_baseline.json`
 - `ops/performance/latency_thresholds.json`