Commit Graph

13 Commits

Author SHA1 Message Date
TPTBusiness ca003cd0f2 fix: close log file handle, fix RiskMgmt equity double-count, remove bare except 2026-05-03 00:17:02 +02:00
TPTBusiness afe1823e85 fix(security): whitelist-validate metric column in get_top_factors (B608)
The metric parameter was passed directly into an f-string SQL query.
Add explicit validation against _ALLOWED_METRICS before use, raising
ValueError on unknown values. Raises ValueError on injection attempt
instead of silently accepting arbitrary column names.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-30 07:25:14 +02:00
TPTBusiness 942266f24d fix(security): validate SQL identifiers in _add_column_if_not_exists (B608)
Replace f-string SQL queries with whitelist validation:
- Table name must be in _ALLOWED_TABLES
- Column name must be alphanumeric+underscore
- Column type must be in _ALLOWED_COL_TYPES
- Use pragma_table_info() for existence check instead of SELECT f-string

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-30 07:21:13 +02:00
TPTBusiness dfbbffd7ea fix(backtest): replace broken MC permutation test with binomial win-rate test
The previous monte_carlo_trade_pvalue() used sum(permuted_trades) as test
statistic, which is permutation-invariant (sum is commutative), so beat/n
was always 1.0 and MC_p was always 1.00 for every strategy.

Replace with a one-sided binomial test on trade win rate vs 50% baseline.
Tests whether the observed win rate could occur by chance under H0: p=0.5.

Also add _shift_daily_constant_factor_if_needed() to predix_full_eval.py
so re-evaluations apply the look-ahead bias correction for daily factors.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-24 09:55:45 +02:00
TPTBusiness b0490c5f0d feat(backtest): add rolling walk-forward validation and Monte Carlo trade permutation test
- monte_carlo_trade_pvalue(): shuffles trade P&L N times, returns fraction of
  permuted sequences that beat real total return (p<0.05 = genuine edge)
- walk_forward_rolling(): multiple IS/OOS windows (IS=3yr, OOS=1yr, step=1yr),
  computes wf_oos_sharpe_mean, wf_oos_consistency (% profitable windows)
- backtest_signal_riskmgmt(): new wf_rolling and mc_n_permutations params
- Strategy generator: enables both (200 MC permutations), adds mc_ok and wf_ok
  to acceptance filter (mc_p<0.20, wf_consistency>=50%)
- Rebacktest script: enables both, stores all wf_*/mc_* fields in write-back
- 6 new tests covering MC pvalue, disabled-by-default, zero-trades edge case,
  rolling WF key presence and consistency range

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-19 18:59:00 +02:00
TPTBusiness f166cc3326 feat(backtest): add walk-forward OOS validation to backtest_signal_riskmgmt
Split IS (2020-2023) and OOS (2024-2026) periods with independent RiskMgmt
simulations. Strategy acceptance now requires OOS sharpe > 0 and
OOS monthly return > 0 to prevent overfitting. OOS metrics stored in
strategy JSON summary and CSV reports.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-19 12:53:00 +02:00
TPTBusiness 6c100170bd feat(backtest): add RiskMgmt-realistic backtest mode with leverage, daily/total loss limits and realistic EUR/USD costs 2026-04-18 15:27:41 +02:00
TPTBusiness 22e638af86 feat: unified backtest engine, LLM error handling, strategy refactor
- Add vbt_backtest.py as single source of truth for all metric formulas
  (Sharpe, drawdown, IC, transaction costs) — backtest_engine.py and
  strategy_orchestrator.py now delegate to it
- Add LLMUnavailableError to exception.py; rd_loop.py catches it at the
  proposal stage and raises LoopResumeError to avoid corrupting trace
  history with None hypotheses
- Guard record() against None exp/hypothesis so loop resets leave
  trace.hist in a consistent state
- Refactor strategy_orchestrator and optuna_optimizer to use unified
  backtest path; remove duplicate metric calculation code
- Add predix_rebacktest_unified.py script for offline re-evaluation
- Update tests and README

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-17 22:52:07 +02:00
TPTBusiness 574a9cb75e fix: Resolve 88% empty backtest results + path fixes
Root Cause: Qlib configs used cn_data (Chinese stocks) instead of eurusd
- provider_uri: cn_data → eurusd_1min_data
- market: csi300 → eurusd
- topk: 50 → 1 (single-asset EURUSD, was opening 0 positions)
- n_drop: 5 → 0, limit_threshold: 0.095 → 0.0

Add failed run tracking and validation:
- factor_runner.py: Validate results before DB save, track failed runs
- model_runner.py: Same validation and tracking
- results_db.py: generate_results_summary() → RESULTS_SUMMARY.md
- extract_results.py: Failed run tracking, progress indicators

Fix project root paths in all modules:
- ResultsDatabase: correct path from rdagent/results/ → results/
- factor_runner: db, factors, failed_runs paths
- model_runner: failed_runs path

All 246 tests passing.
2026-04-03 16:21:59 +02:00
TPTBusiness 633b5639de fix: Add nosec comments for schema migration SQL in results_db.py
Bandit false positive B608: Schema migration uses controlled column names,
not user input. Add nosec comments to suppress warning.
2026-04-03 14:37:22 +02:00
TPTBusiness 5ce86c824e feat: Full system integration - RL + Protections + Backtesting + CLI
Connect all Predix components into unified trading system:

INTEGRATION (ALL 295 TESTS PASS):
- RL Trading connected with Protection Manager
- RL Trading connected with Backtesting Engine
- CLI command 'rdagent rl_trading' added (train/backtest/live modes)
- Graceful fallback for users without stable-baselines3

OPEN SOURCE COMPATIBILITY:
- System works WITHOUT stable-baselines3 (momentum fallback)
- System works WITHOUT local models/prompts (uses standard)
- Clear warning messages when optional deps missing
- GitHub users get FULLY WORKING system

CLOSED SOURCE PROTECTION:
- models/local/, prompts/local/, .env stay local only
- .gitignore properly configured
- Our alpha (best models/prompts) remains private

DOCUMENTATION:
- QWEN.md: Open/closed source strategy
- QWEN.md: Development guidelines for AI assistant
- QWEN.md: Open source compatibility principle
- README.md: RL Trading CLI commands and examples
- requirements/rl.txt: Optional RL dependencies

Modified files:
- rdagent/app/cli.py: Added rl_trading command
- rdagent/components/backtesting/backtest_engine.py: RL backtest support
- rdagent/components/coder/rl/costeer.py: Protection Manager integration
- rdagent/components/coder/rl/__init__.py: Conditional imports + fallback
- rdagent/components/coder/rl/fallback.py: NEW - Simple momentum fallback
- requirements.txt: Optional RL deps commented
- requirements/rl.txt: NEW - Full RL dependencies
- test/integration/test_all_features.py: 7 new integration tests
- QWEN.md: Open source strategy + development guidelines
- README.md: RL Trading documentation

295 tests pass: 67 integration + 89 RL + 139 backtesting
2026-04-03 13:53:32 +02:00
TPTBusiness bd025e50dc feat: Add Trading Protection System with 4 protections + comprehensive tests
Implement automatic trading protection system to prevent excessive losses:

PROTECTIONS (100% original code, NOT copied from Freqtrade):
- Max Drawdown Protection: Blocks trading when DD > 15% (configurable)
- Cooldown Period: 4h mandatory rest after 5% loss
- Stoploss Guard: Detects stoploss clusters (>5 per day)
- Low Performance Filter: Filters factors with Sharpe < 0.5, Win Rate < 40%

ARCHITECTURE:
- Base protection interface with common utilities
- 4 specialized protection implementations
- ProtectionManager orchestrates all active protections
- Time-based blocking with automatic expiry

TESTS (32 total, ALL PASS):
- 25 unit tests in test/backtesting/test_protections.py
- 7 integration tests in test/integration/test_all_features.py
- Tests cover: normal operation, edge cases, error handling

DOCUMENTATION:
- Update QWEN.md with development guidelines for AI assistant
  * Mandatory rules: Update QWEN.md, README, requirements.txt, tests
  * Pre-commit checklist
  * Example workflow
- Update README.md with protection system features
- Update project structure with new modules

All code is 100% original - NO license issues with Freqtrade GPLv3.
2026-04-03 13:01:56 +02:00
TPTBusiness 4690b01042 feat: Backtesting Engine + Risk Management + Results DB
Kompakte Implementierung:

1. backtest_engine.py
   - IC, Sharpe, Max Drawdown, Win Rate
   - FactorBacktester mit JSON-Export

2. results_db.py
   - SQLite DB: factors, backtest_runs, loop_results
   - Top-Faktoren, Aggregate Stats

3. risk_management.py
   - Correlation Matrix
   - Mean-Variance & Risk Parity Optimizer
   - Risk-Limit Checks

4. results/ Ordner (in .gitignore)
   - backtests/, db/, factors/, runs/, logs/
   - README.md mit Dokumentation

Status:
- Backtesting: 10% → 90% 
- Risk Management: 60% → 95% 
2026-04-02 19:23:14 +02:00