Add real historical backtesting with Hyperliquid mainnet candle data

backtests/historical_runner.py: Fetches real 1h candles from Hyperliquid
mainnet API (candleSnapshot endpoint). Runs all 7 strategies against
actual BTC price history (721 candles, 30 days, $63,024→$63,605).
Each strategy's signal logic operates on real OHLCV data with
configurable fee tiers. Saves to backtests/results/historical/.

Results on 30d BTC data at VIP0:
  Mean Reversion: +93.87% net (Sharpe 0.94)
  Order Book Imbalance: +54.31% net (Sharpe 1.03)
  Avellaneda-Stoikov: -1.02% net (Sharpe -0.13)
  Iceberg Detection: -33.20% net
  Momentum Breakout: -54.72% net

Server: Added /api/backtests/historical (list) and
/api/backtest/historical/{name} (full data) endpoints.

Dashboard: Added "Historical" tab with "Real Data" badge. Cards show
coin + mainnet source. Click opens the same detail panel with fee
tier dropdown and equity chart.

dashboard/server.py

@@ -28,6 +28,7 @@ from fastapi.responses import FileResponse, JSONResponse
 import sys
 sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
 from config.fee_tiers import get_perp_fees, PERPS_TIERS, STAKING_TIERS, STRATEGY_FEE_MODELS
+from common.risk import risk_summary
 import uvicorn
 
 # ═══════════════════════════════════════════════════════════
@@ -37,6 +38,7 @@ import uvicorn
 METRICS_FILE = "/tmp/ftdt-metrics.json"
 PAPER_METRICS_FILE = "/tmp/ftdt-paper-metrics.json"
 BACKTEST_DIR = "/home/debian/ftdt-quant-lab/backtests/results"
+HISTORICAL_DIR = "/home/debian/ftdt-quant-lab/backtests/results/historical"
 STATIC_DIR = Path(__file__).parent / "static"
 
 # Ensure backtest dir exists
@@ -257,6 +259,47 @@ async def recalc_backtest(name: str, fee_tier: int = 0, staking_tier: str = "non
     })
 
 
+@app.get("/api/backtests/historical")
+async def list_historical_backtests():
+    """List historical (real data) backtest results."""
+    results = []
+    d = HISTORICAL_DIR
+    if os.path.isdir(d):
+        for fname in sorted(os.listdir(d), reverse=True):
+            if fname.endswith(".json"):
+                fpath = os.path.join(d, fname)
+                try:
+                    with open(fpath) as f:
+                        data = json.load(f)
+                    results.append({
+                        "name": fname.replace(".json", ""),
+                        "strategy": data.get("strategy", "unknown"),
+                        "coin": data.get("coin", "?"),
+                        "start": data.get("start_time"),
+                        "end": data.get("end_time"),
+                        "sharpe": data.get("sharpe", 0),
+                        "sortino": data.get("sortino", 0),
+                        "pnl_pct": data.get("pnl_pct", 0),
+                        "max_dd": data.get("max_dd", 0),
+                        "win_rate": data.get("win_rate", 0),
+                        "total_trades": data.get("total_trades", 0),
+                        "data_source": "Hyperliquid Mainnet",
+                    })
+                except (json.JSONDecodeError, IOError):
+                    pass
+    return JSONResponse(results)
+
+
+@app.get("/api/backtest/historical/{name}")
+async def get_historical_backtest(name: str):
+    """Get full historical backtest result."""
+    fpath = os.path.join(HISTORICAL_DIR, f"{name}.json")
+    if os.path.exists(fpath):
+        with open(fpath) as f:
+            return JSONResponse(json.load(f))
+    return JSONResponse({"error": "not found"}, status_code=404)
+
+
 @app.get("/api/backtest/{name}/csv")
 async def get_backtest_csv(name: str):
     """Download backtest trades as CSV."""
@@ -280,6 +323,48 @@ async def get_backtest_csv(name: str):
     )
 
 
+@app.get("/api/risk")
+async def get_risk_metrics():
+    """Compute risk analytics from the latest paper metrics."""
+    paper = read_paper_metrics()
+    equity_history = paper.get("equity_history", [])
+    strategy_equity = paper.get("strategy_equity", {})
+
+    if not equity_history:
+        return JSONResponse({"error": "no equity history available"}, status_code=404)
+
+    summary = risk_summary(equity_history, strategy_equity)
+
+    # Build a compact correlation text summary for the frontend
+    corr = summary.get("correlation", {})
+    corr_summary = []
+    names = sorted(corr.keys())
+    for i, n1 in enumerate(names):
+        for n2 in names[i + 1:]:
+            val = corr.get(n1, {}).get(n2, 0)
+            if abs(val) > 0.3:  # only show meaningful correlations
+                corr_summary.append({
+                    "pair": f"{n1} ↔ {n2}",
+                    "correlation": round(val, 3),
+                    "level": "high" if abs(val) > 0.7 else "medium",
+                })
+    corr_summary.sort(key=lambda x: -abs(x["correlation"]))
+
+    return JSONResponse({
+        "portfolio": {
+            "var_95": summary["var_95"],
+            "cvar_95": summary["cvar_95"],
+            "max_drawdown": summary["max_drawdown"],
+            "calmar_ratio": summary["calmar_ratio"],
+            "sharpe": summary["sharpe"],
+            "sortino": summary["sortino"],
+            "num_observations": summary["num_observations"],
+        },
+        "per_strategy": summary.get("per_strategy", {}),
+        "correlation_summary": corr_summary,
+        "correlation_matrix": corr,
+    })
+
 # ═══════════════════════════════════════════════════════════
 # Static
 # ═══════════════════════════════════════════════════════════