Luke Mosoti a89156b402 feat: add strategy backtesting module for live model evaluation ...

- Introduced `strategy_backtest.py` as a single source of truth for scoring and backtesting.
- Implemented functions to load live model bundles, build feature frames, and execute backtests.
- Ensured consistency between optimized models and their validation/trading counterparts.
- Added functionality for generating trading signals and retrieving the latest trading decision.

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..

adaptive_filter_candidate_funnels.csv

Add lot escalation what-if analysis CSV report

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adaptive_filter_hourly_candidates.csv

Add lot escalation what-if analysis CSV report

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adaptive_filter_hourly_trades.csv

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adaptive_filter_lab_results.csv

Add lot escalation what-if analysis CSV report

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Explorer_Diagnostics_M5.csv

Update pipeline reports and diagnostics for M15 and M5 timeframes

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Explorer_Diagnostics_M15.csv

Update pipeline reports and diagnostics for M15 and M5 timeframes

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explorer_runtime_config.json

Refactor code structure for improved readability and maintainability

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Explorer_Timeframe_Comparison.csv

chore: clean up code structure and remove unused code blocks

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Explorer_Timeframe_Report.csv

Update pipeline reports and diagnostics for M15 and M5 timeframes

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filter_lab_attribution_M5.csv

Refactor code structure for improved readability and maintainability

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filter_lab_attribution_M15.csv

Refactor code structure for improved readability and maintainability

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filter_lab_comparison_M5.csv

Refactor code structure for improved readability and maintainability

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filter_lab_comparison_M15.csv

Refactor code structure for improved readability and maintainability

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live_simulation_summary.csv

feat: add strategy backtesting module for live model evaluation

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live_trades_M5.csv

feat: add strategy backtesting module for live model evaluation

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live_trades_M15.csv

Add lot escalation what-if analysis CSV report

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lot_escalation_whatif.csv

feat: add strategy backtesting module for live model evaluation

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ml_readiness_scores.csv

chore: clean up code structure and remove unused code blocks

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monte_carlo_summary.csv

feat: add strategy backtesting module for live model evaluation

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pipeline_certification_strategy_tester.json

Add pipeline certification and profiling modules with self-validation

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pipeline_manifest_strategy_tester.json

chore: clean up code structure and remove unused code blocks

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pipeline_waterfall_M5.csv

chore: clean up code structure and remove unused code blocks

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pipeline_waterfall_M15.csv

chore: clean up code structure and remove unused code blocks

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probability_drift.csv

chore: clean up code structure and remove unused code blocks

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profit_per_trade_sizing.csv

Add lot escalation what-if analysis CSV report

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regime_diagnostics_M5.json

feat: add strategy backtesting module for live model evaluation

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root_cause_ranking.csv

chore: clean up code structure and remove unused code blocks

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root_cause_v2_M5.csv

chore: clean up code structure and remove unused code blocks

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root_cause_v2_M15.csv

chore: clean up code structure and remove unused code blocks

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signal_loss_report_M5_explorer.csv

Update pipeline reports and diagnostics for M15 and M5 timeframes

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signal_loss_report_M5_strategy_tester.csv

chore: clean up code structure and remove unused code blocks

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signal_loss_report_M15_explorer.csv

Update pipeline reports and diagnostics for M15 and M5 timeframes

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signal_loss_report_M15_strategy_tester.csv

chore: clean up code structure and remove unused code blocks

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st_explorer_consistency.csv

Update pipeline reports and diagnostics for M15 and M5 timeframes

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strategy_focus_partialtp_mr.csv

Add lot escalation what-if analysis CSV report

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strategy_full_results.csv

Add lot escalation what-if analysis CSV report

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strategy_leaderboard.csv

Add lot escalation what-if analysis CSV report

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strategy_summary.csv

Add lot escalation what-if analysis CSV report

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strategy_winners_for_explorer.csv

Add lot escalation what-if analysis CSV report

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