# Monte Carlo Artifact Summary

- Run ID: `62be817024374ffd8e4b4413564506c1`
- Label: `btcusdtp_60_ema20return_53adbfa0fe73_rank_1_trial_0_benchmark100`
- Run View: `100_opportunity_benchmark`
- Simulation window source: `fixed_100_opportunities`
- Simulations: `250`
- Optimal Threshold: `0.7`
- TEST window: `2024-11-25T15:00:00Z` → `2025-11-03T00:00:00Z`
- TEST date range: `2024-11-25` → `2025-11-03`
- Opportunities / simulation: `100.0`
- Executed trades / simulation: `7.896`
- Take rate: `0.07896`
- Mean total PnL: `5.228010610544639`
- Median total PnL: `4.432164642886661`
- Sharpe: `0.8706912926923005`
- Risk of Ruin (%): `0.0`
- SQN: `None` (N/A)
- Win Rate: `0.3596363747363747`

## Plots
- `plots/appt_distribution_btcusdtp_60_ema20return_53adbfa0fe73_rank_1_trial_0_benchmark100.png`
- `plots/mdd_distribution_btcusdtp_60_ema20return_53adbfa0fe73_rank_1_trial_0_benchmark100.png`
- `plots/appt_vs_mdd_btcusdtp_60_ema20return_53adbfa0fe73_rank_1_trial_0_benchmark100.png`
- `plots/equity_fan_btcusdtp_60_ema20return_53adbfa0fe73_rank_1_trial_0_benchmark100.png`

## Tables
- `tables/summary_stats_btcusdtp_60_ema20return_53adbfa0fe73_rank_1_trial_0_benchmark100.csv`
- `tables/diagnostics_btcusdtp_60_ema20return_53adbfa0fe73_rank_1_trial_0_benchmark100.csv`

## Segmented Trading
- `tables/segmented_trading_calendar_year.csv`
- `tables/segmented_trading_calendar_quarter.csv`
- `tables/segmented_trading_calendar_month.csv`
- `tables/segmented_trading_hour_of_day.csv`
- `tables/segmented_trading_tables.json`
