trading_bot_v4/docs/analysis/DIAGNOSTIC_RESULTS_SUMMARY.md

V9 Diagnostic Results Summary

Date: November 29, 2025
Data: 95,617 5-minute bars (SOLUSDT, Jan-Nov 2024)

🚨 CRITICAL FINDINGS

1. BASELINE IS LOSING MONEY

• Baseline PnL: -$1,532.30 (1,663 trades)
• Win Rate: 0.6% (essentially all losses!)
• This explains the "parameter insensitivity" - when strategy loses on EVERY trade, parameters don't matter much

2. momentum_min_adx Parameter BROKEN

momentum_min_adx=18.0: 1663 trades, $-1532.30 PnL
momentum_min_adx=21.0: 1663 trades, $-1532.30 PnL  ← IDENTICAL
momentum_min_adx=24.0: 1663 trades, $-1532.30 PnL  ← IDENTICAL
momentum_min_adx=27.0: 1663 trades, $-1532.30 PnL  ← IDENTICAL

Status: 🔴 NO EFFECT - Parameter is NOT being applied or is overridden

3. Other Parameters Show Minimal Effect

• flip_threshold: 1662-1663 trades (0.1% variation), PnL: -$1,185 to -$1,532
• cooldown_bars: 1660-1664 trades (0.2% variation), PnL: -$1,408 to -$1,859
• ma_gap_threshold: 1662-1663 trades (0.1% variation), PnL: -$1,185 to -$1,532

Signal counts barely change - most parameters have almost zero effect on trade generation.

📊 Comparison to Sweep Results

Exhaustive Sweep (EPYC):

• Best Result: $498.12 PnL, 568 trades, 61.09% WR
• Configuration: Different from baseline

Diagnostic Test (Local):

• Baseline: -$1,532.30 PnL, 1,663 trades, 0.6% WR
• Best: -$1,514.75 PnL, 1,663 trades, 0.6% WR

🤔 Why The Discrepancy?

Hypothesis 1: Data Mismatch

• EPYC used: Aug 1 - Nov 28, 2024 (34,273 candles - mentioned in DUAL_SWEEP_README.md)
• Local used: Jan 1 - Nov 28, 2024 (95,617 candles - full year)
• Impact: Different time periods = different market conditions = different results

Hypothesis 2: Configuration Mismatch

• EPYC sweep might be using different TradeConfig settings
• Position size, max bars per trade, or other simulator settings might differ

Hypothesis 3: Strategy Implementation Difference

• Backtester simulate_money_line() might not match live v9 indicator
• Parameters might not map correctly between TradingView and Python

🎯 Action Items

IMMEDIATE (Before Any Optimization):

1. ✅ VERIFY DATA ALIGNMENT

   # Download exact same date range as EPYC
   python3 scripts/export_binance_ohlcv.py \
     --symbol SOLUSDT --interval 5m \
     --start 2024-08-01 --end 2024-11-28 \
     --output backtester/data/solusdt_5m_aug_nov.csv
   
   # Re-run diagnostics on matched dataset
   ./run_comprehensive_diagnostics.sh backtester/data/solusdt_5m_aug_nov.csv
   

2. VERIFY SIMULATOR SETTINGS

   • Check if EPYC sweep uses different position_size or max_bars_per_trade
   • Compare TradeConfig between sweep script and diagnostic scripts

3. FIX momentum_min_adx BUG

   • Investigate money_line_signals() to find why ADX parameter is ignored
   • This is likely why all sweep configs produced similar results

4. FIX EXTREME BUGS

   • Fix load_csv() call in test_extreme_configs() (missing symbol/timeframe)
   • Fix SimulatedTrade.pnl attribute access in trade_analysis.py

AFTER VERIFICATION:

5. If Data Mismatch Confirmed:

   • Use Aug-Nov 2024 dataset for all future analysis
   • Understand why Q1-Q3 2024 was so terrible (bear market?)

6. If Simulator Bug Confirmed:

   • Fix Python backtester to match TradingView v9 exactly
   • Validate against known live trades

7. Parameter Optimization:

   • Only optimize AFTER baseline is profitable on test data
   • No point optimizing if strategy loses money fundamentally

💡 Key Insight

You can't optimize a fundamentally losing strategy.

If v9 baseline loses $1,532 on full-year data but makes $498 on Aug-Nov subset, either:

• A) Aug-Nov was a favorable period (cherry-picked results)
• B) Jan-Jul market was unfavorable for momentum strategies (bear market)
• C) Backtester doesn't match production v9 indicator

Must resolve this before any parameter tuning!