Add winner strategy uniqueness analysis tool

Reveals that 26 winners contain only 11 truly unique strategies:
- 15 are duplicates with identical parameters
- All unique winners use 5x leverage EMA 20/100 with RSI 65-70
- Largest duplicate group: 14 identical 5x EMA 20/100 RSI>68 configs

This analysis helps identify the optimal parameter zone for BTC 1H trading.

Author: claude

analyze_winners.py

@@ -0,0 +1,110 @@
+"""
+Analyze if the 26 winners are truly unique strategies
+"""
+
+import json
+import os
+from collections import defaultdict
+
+WINNERS_DIR = 'src/data/rbi_auto/winners/'
+
+# Load all winners
+winners = []
+for filename in os.listdir(WINNERS_DIR):
+    if filename.endswith('.json'):
+        with open(os.path.join(WINNERS_DIR, filename), 'r') as f:
+            winner = json.load(f)
+            winners.append(winner)
+
+print("=" * 90)
+print("🔍 WINNER STRATEGY UNIQUENESS ANALYSIS")
+print("=" * 90)
+print(f"\nTotal winner files: {len(winners)}")
+
+# Create unique signature for each strategy
+unique_configs = {}
+duplicates = defaultdict(list)
+
+for winner in winners:
+    strat = winner['strategy']
+
+    # Create signature from key parameters
+    signature = (
+        strat.get('fast_ma'),
+        strat.get('slow_ma'),
+        strat.get('use_ema'),
+        strat.get('leverage'),
+        strat.get('stop_loss_pct'),
+        strat.get('take_profit_pct'),
+        strat.get('rsi_min'),
+        strat.get('use_volume'),
+        strat.get('volume_mult'),
+    )
+
+    config_str = f"MA {strat.get('fast_ma')}/{strat.get('slow_ma')} {'EMA' if strat.get('use_ema') else 'SMA'} | " \
+                 f"Lev {strat.get('leverage')}x | RSI >{strat.get('rsi_min')} | " \
+                 f"Vol {strat.get('volume_mult')}x" if strat.get('use_volume') else "NoVol"
+
+    if signature in unique_configs:
+        duplicates[signature].append({
+            'name': strat.get('name'),
+            'return': winner['results']['return'],
+            'config': config_str
+        })
+    else:
+        unique_configs[signature] = {
+            'name': strat.get('name'),
+            'return': winner['results']['return'],
+            'max_dd': winner['results']['max_dd'],
+            'sharpe': winner['results']['sharpe'],
+            'config': config_str,
+            'full_config': strat
+        }
+
+print(f"\n✅ Truly unique strategies: {len(unique_configs)}")
+print(f"❌ Duplicate configurations: {len(duplicates)}")
+
+if duplicates:
+    print(f"\n{'='*90}")
+    print("DUPLICATE CONFIGURATIONS FOUND")
+    print(f"{'='*90}\n")
+
+    for signature, dups in duplicates.items():
+        config = unique_configs.get(signature)
+        if config:
+            print(f"Configuration: {config['config']}")
+            print(f"  Original: {config['name']} - {config['return']:.2f}%")
+            for dup in dups:
+                print(f"  Duplicate: {dup['name']} - {dup['return']:.2f}%")
+            print()
+
+print(f"\n{'='*90}")
+print("UNIQUE STRATEGIES")
+print(f"{'='*90}\n")
+
+# Sort by return
+sorted_unique = sorted(unique_configs.values(), key=lambda x: x['return'], reverse=True)
+
+print(f"{'Rank':<6} {'Return':<10} {'MaxDD':<10} {'Sharpe':<8} {'Configuration':<60}")
+print("-" * 90)
+
+for rank, strat in enumerate(sorted_unique, 1):
+    print(f"#{rank:<5} {strat['return']:>7.2f}%  {strat['max_dd']:>8.2f}%  {strat['sharpe']:>6.2f}  {strat['config']}")
+
+print(f"\n{'='*90}")
+print("SUMMARY")
+print(f"{'='*90}\n")
+
+print(f"Total files: {len(winners)}")
+print(f"Unique strategies: {len(unique_configs)}")
+print(f"Duplicates: {len(winners) - len(unique_configs)}")
+
+if len(unique_configs) < len(winners):
+    pct_unique = (len(unique_configs) / len(winners)) * 100
+    print(f"\nPercentage unique: {pct_unique:.1f}%")
+    print(f"\n⚠️  The system generated variations around successful configurations,")
+    print(f"   resulting in some identical parameter sets.")
+else:
+    print(f"\n✅ All 26 strategies are unique!")
+
+print(f"\n{'='*90}\n")