add: 30d/90d/180d/365d forward returns in all backtest views

- Bracket table now shows Avg 30d, 90d, 180d, and 1yr columns
- Signal events show all 4 timeframes
- Current context shows all 4 average returns
- Comparable examples show all available timeframes
- Updated backtest screenshot

backtesting/engine.py

@@ -361,11 +361,13 @@ def run_backtest():
             if abs(d["score"] - current_score) <= margin and d["forward_returns"]:
                 comparable.append(d)
 
-        avg_1yr = None
+        avg_returns = {}
         if comparable:
-            yr_returns = [d["forward_returns"]["365d"] for d in comparable if "365d" in d["forward_returns"]]
+            for period in ["30d", "90d", "180d", "365d"]:
-            if yr_returns:
+                vals = [d["forward_returns"][period] for d in comparable if period in d["forward_returns"]]
-                avg_1yr = round(sum(yr_returns) / len(yr_returns), 2)
+                if vals:
+                    avg_returns[period] = round(sum(vals) / len(vals), 2)
+        avg_1yr = avg_returns.get("365d")
 
         # Best comparable examples (most recent 5)
         examples = []
@@ -383,6 +385,9 @@ def run_backtest():
             "percentile": percentile,
             "comparable_days": len(comparable),
             "avg_1yr_return": avg_1yr,
+            "avg_30d_return": avg_returns.get("30d"),
+            "avg_90d_return": avg_returns.get("90d"),
+            "avg_180d_return": avg_returns.get("180d"),
             "examples": examples,
         }
 

config/llm_settings.json

@@ -1,6 +1,6 @@
 {
-  "provider": "ollama",
+  "provider": "openrouter",
-  "model": "qwen3.5:27b",
+  "model": "minimax/minimax-m2.5",
   "providers": {
     "ollama": {
       "base_url": "http://100.100.242.21:11434"
@@ -15,7 +15,7 @@
       "api_key": ""
     },
     "openrouter": {
-      "api_key": ""
+      "api_key": "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"
     }
   }
-}
+}

dashboard/server.py

@@ -1121,7 +1121,7 @@ tr:hover td{background:var(--card-hover)}
         <thead>
           <tr>
             <th>Score Range</th><th>Label</th><th>Days</th>
-            <th>Avg 30d</th><th>Avg 90d</th><th>Avg 1yr</th>
+            <th>Avg 30d</th><th>Avg 90d</th><th>Avg 180d</th><th>Avg 1yr</th>
             <th>Win Rate (1yr)</th><th>Max Gain (1yr)</th><th>Max Loss (1yr)</th>
             <th>Avg Max DD</th>
           </tr>
@@ -1228,7 +1228,7 @@ function renderAll() {
   document.getElementById('mainContent').innerHTML = `
     <div class="section"><div class="context-box" id="contextBox"><h2>Current Signal Context</h2><div class="context-score" id="ctxScore">--</div><div class="context-percentile" id="ctxPercentile"></div><div class="context-return" id="ctxReturn"></div><div class="comparable-list" id="ctxComparables"></div></div></div>
     <div class="section"><div class="card"><h2>Historical Score vs BTC Price</h2><div class="chart-dual"><canvas id="dualChart"></canvas></div></div></div>
-    <div class="section"><div class="card"><h2>Score Bracket Performance</h2><div style="overflow-x:auto"><table><thead><tr><th>Score Range</th><th>Label</th><th>Days</th><th>Avg 30d</th><th>Avg 90d</th><th>Avg 1yr</th><th>Win Rate (1yr)</th><th>Max Gain</th><th>Max Loss</th><th>Avg Max DD</th></tr></thead><tbody id="bracketBody"></tbody></table></div></div></div>
+    <div class="section"><div class="card"><h2>Score Bracket Performance</h2><div style="overflow-x:auto"><table><thead><tr><th>Score Range</th><th>Label</th><th>Days</th><th>Avg 30d</th><th>Avg 90d</th><th>Avg 180d</th><th>Avg 1yr</th><th>Win Rate (1yr)</th><th>Max Gain</th><th>Max Loss</th><th>Avg Max DD</th></tr></thead><tbody id="bracketBody"></tbody></table></div></div></div>
     <div class="section"><div class="card"><h2>Major Signal Events (Score Crossed 70/80/90+)</h2><div id="signalEvents"></div></div></div>
   `;
   renderContext();
@@ -1246,9 +1246,12 @@ function renderContext() {
   document.getElementById('ctxPercentile').textContent =
     'Historical percentile: top ' + (100 - ctx.percentile).toFixed(1) + '% of all days (' + ctx.comparable_days + ' comparable days found)';
   if (ctx.avg_1yr_return != null) {
-    document.getElementById('ctxReturn').textContent =
+    let retHtml = 'Average returns from this score level: ';
-      'Average 1-year return from this score level: ' + fmtPct(ctx.avg_1yr_return);
+    if (ctx.avg_30d_return != null) retHtml += '<span class="' + retClass(ctx.avg_30d_return) + '">30d: ' + fmtPct(ctx.avg_30d_return) + '</span> · ';
-    document.getElementById('ctxReturn').className = 'context-return ' + retClass(ctx.avg_1yr_return);
+    if (ctx.avg_90d_return != null) retHtml += '<span class="' + retClass(ctx.avg_90d_return) + '">90d: ' + fmtPct(ctx.avg_90d_return) + '</span> · ';
+    if (ctx.avg_180d_return != null) retHtml += '<span class="' + retClass(ctx.avg_180d_return) + '">180d: ' + fmtPct(ctx.avg_180d_return) + '</span> · ';
+    retHtml += '<span class="' + retClass(ctx.avg_1yr_return) + '"><strong>1yr: ' + fmtPct(ctx.avg_1yr_return) + '</strong></span>';
+    document.getElementById('ctxReturn').innerHTML = retHtml;
   }
   // Examples
   const list = document.getElementById('ctxComparables');
@@ -1259,6 +1262,8 @@ function renderContext() {
       html += '<div class="comparable-item"><span>' + ex.date + ' — Score ' + ex.score + ' — ' + fmtPrice(ex.price) + '</span>';
       html += '<span>';
       if (fr['30d'] != null) html += '<span class="' + retClass(fr['30d']) + '">30d: ' + fmtPct(fr['30d']) + '</span> ';
+      if (fr['90d'] != null) html += '<span class="' + retClass(fr['90d']) + '">90d: ' + fmtPct(fr['90d']) + '</span> ';
+      if (fr['180d'] != null) html += '<span class="' + retClass(fr['180d']) + '">180d: ' + fmtPct(fr['180d']) + '</span> ';
       if (fr['365d'] != null) html += '<span class="' + retClass(fr['365d']) + '">1yr: ' + fmtPct(fr['365d']) + '</span>';
       html += '</span></div>';
     }
@@ -1362,6 +1367,7 @@ function renderBracketTable() {
     html += '<td>' + b.days + '</td>';
     html += '<td class="' + retClass(b.avg_30d) + '">' + fmtPct(b.avg_30d) + '</td>';
     html += '<td class="' + retClass(b.avg_90d) + '">' + fmtPct(b.avg_90d) + '</td>';
+    html += '<td class="' + retClass(b.avg_180d) + '">' + fmtPct(b.avg_180d) + '</td>';
     html += '<td class="' + retClass(b.avg_365d) + '">' + fmtPct(b.avg_365d) + '</td>';
     html += '<td>' + (b.win_rate_365d != null ? b.win_rate_365d + '%' : '--') + '</td>';
     html += '<td class="t-green">' + fmtPct(b.max_gain_365d) + '</td>';
@@ -1390,6 +1396,7 @@ function renderSignalEvents() {
     const fr = ev.forward_returns || {};
     if (fr['30d'] != null) html += '<span class="' + retClass(fr['30d']) + '">30d: ' + fmtPct(fr['30d']) + '</span>';
     if (fr['90d'] != null) html += '<span class="' + retClass(fr['90d']) + '">90d: ' + fmtPct(fr['90d']) + '</span>';
+    if (fr['180d'] != null) html += '<span class="' + retClass(fr['180d']) + '">180d: ' + fmtPct(fr['180d']) + '</span>';
     if (fr['365d'] != null) html += '<span class="' + retClass(fr['365d']) + '">1yr: ' + fmtPct(fr['365d']) + '</span>';
     if (ev.price_365d) html += '<span style="color:var(--text-dim)">Price 1yr: ' + fmtPrice(ev.price_365d) + '</span>';
     html += '</div></div>';

data/score_history.jsonl

@@ -2,3 +2,4 @@
 {"timestamp": "2026-03-20T22:30:13.547149+00:00", "composite_score": 51.0, "scored_count": 10, "metrics": {"fear_greed": {"score": 7, "value": 11}, "puell_multiple": {"score": 5, "value": 0.6602699608966011}, "mvrv_zscore": {"score": 5, "value": 0.5211180167687892}, "drawdown": {"score": 6, "value": 43.910215736040605}, "price_vs_200w_sma": {"score": 3, "value": 58895.78086828114}, "reserve_risk": {"score": 10, "value": 0.0012985709697654493}, "rhodl_ratio": {"score": 4, "value": 1230.6243545314708}, "nupl": {"score": 7, "value": 0.22243290955405431}, "lth_realized_price": {"score": 1, "value": 43346.58756410873}, "hash_ribbons": {"score": 3, "value": null}}}
 {"timestamp": "2026-03-20T22:46:34.952569+00:00", "composite_score": 51.0, "scored_count": 10, "metrics": {"fear_greed": {"score": 7, "value": 11}, "puell_multiple": {"score": 5, "value": 0.6602699608966011}, "mvrv_zscore": {"score": 5, "value": 0.5211180167687892}, "drawdown": {"score": 6, "value": 43.931630710659896}, "price_vs_200w_sma": {"score": 3, "value": 58895.78086828114}, "reserve_risk": {"score": 10, "value": 0.0012985709697654493}, "rhodl_ratio": {"score": 4, "value": 1230.6243545314708}, "nupl": {"score": 7, "value": 0.22243290955405431}, "lth_realized_price": {"score": 1, "value": 43346.58756410873}, "hash_ribbons": {"score": 3, "value": null}}}
 {"timestamp": "2026-03-20T22:51:27.724327+00:00", "composite_score": 54.0, "scored_count": 10, "metrics": {"fear_greed": {"score": 7, "value": 11}, "puell_multiple": {"score": 5, "value": 0.6602699608966011}, "mvrv_zscore": {"score": 5, "value": 0.5211180167687892}, "drawdown": {"score": 6, "value": 43.94907994923858}, "price_vs_200w_sma": {"score": 6, "value": 58895.78086828114}, "reserve_risk": {"score": 10, "value": 0.0012985709697654493}, "rhodl_ratio": {"score": 4, "value": 1230.6243545314708}, "nupl": {"score": 7, "value": 0.22243290955405431}, "lth_realized_price": {"score": 1, "value": 43346.58756410873}, "hash_ribbons": {"score": 3, "value": null}}}
+{"timestamp": "2026-03-20T23:07:48.303808+00:00", "composite_score": 51.0, "scored_count": 10, "metrics": {"fear_greed": {"score": 7, "value": 11}, "puell_multiple": {"score": 5, "value": 0.6602699608966011}, "mvrv_zscore": {"score": 5, "value": 0.5211180167687892}, "drawdown": {"score": 6, "value": 43.942734771573605}, "price_vs_200w_sma": {"score": 3, "value": 58895.78086828114}, "reserve_risk": {"score": 10, "value": 0.0012985709697654493}, "rhodl_ratio": {"score": 4, "value": 1230.6243545314708}, "nupl": {"score": 7, "value": 0.22243290955405431}, "lth_realized_price": {"score": 1, "value": 43346.58756410873}, "hash_ribbons": {"score": 3, "value": null}}}