Add Kalman Pairs to all three systems: live, paper, historical

Live node:
  - Registered in STRATEGIES dict (8th strategy)
  - Signal: KalmanPairsTrader.step(eth, btc) every compute_signals()
  - Adaptive hedge ratio updates with every tick

Paper trader:
  - Registered in STRATEGIES dict
  - Signal: KalmanPairsTrader integrated into compute_signals()
  - Falls back gracefully if kalman_pairs module not importable

Historical backtests:
  - Ran for BTC, ETH, HYPE, VVV (4 files)
  - kalman_pairs_{TICKER}_*.json in results/historical/
  - Visible on dashboard under Historical tab (8 strategies x 4 coins)

Dashboard: now shows Kalman Pairs card on all three tabs.

live/node.py

@@ -38,6 +38,7 @@ STRATEGIES = {
     "Avellaneda-Stoikov": {"allocation":100.0,"instrument":"BTC-USD-PERP","pnl":0.0,"pnl_pct":0.0,"position":0.0,"trades_today":0,"wins":0,"win_rate":0.0,"status":"idle","size":0.0002,"fee_paid":0.0,"signals":[],"type":"market_making","description":"Dual-sided quoting at best bid/ask — captures spread via stochastic control. Places both sides simultaneously."},
     "Momentum Breakout": {"allocation":100.0,"instrument":"BTC-USD-PERP","pnl":0.0,"pnl_pct":0.0,"position":0.0,"trades_today":0,"wins":0,"win_rate":0.0,"status":"idle","size":0.0002,"fee_paid":0.0,"signals":[],"type":"momentum","description":"Bollinger Band (2σ) breakout — enters with volume confirmation."},
     "Mean Reversion": {"allocation":100.0,"instrument":"BTC-USD-PERP","pnl":0.0,"pnl_pct":0.0,"position":0.0,"trades_today":0,"wins":0,"win_rate":0.0,"status":"idle","size":0.0002,"fee_paid":0.0,"signals":[],"type":"reversal","description":"VWAP deviation — buys below VWAP, sells above. Oscillates around fair value."},
+    "Kalman Pairs": {"allocation":100.0,"instrument":"ETH-USD-PERP","pnl":0.0,"pnl_pct":0.0,"position":0.0,"trades_today":0,"wins":0,"win_rate":0.0,"status":"idle","size":0.006,"fee_paid":0.0,"signals":[],"type":"stat_arb","description":"Kalman-filter adaptive hedge ratio — tracks evolving BTC/ETH beta with every tick."}
 }
 
 trades_log: list[dict] = []
@@ -149,6 +150,23 @@ def compute_signals():
             z = (cur-mu)/std
             if z>1.5: STRATEGIES["Pairs Trading"]["signals"].append({"time":time.time(),"signal":"SELL_ETH","strength":z})
             elif z<-1.5: STRATEGIES["Pairs Trading"]["signals"].append({"time":time.time(),"signal":"BUY_ETH","strength":abs(z)})
+    # Kalman Pairs: adaptive hedge via Kalman filter (falls back to Pairs logic)
+    if len(btc_prices)>=20 and len(eth_prices)>=20:
+        try:
+            from strategies.kalman_pairs import KalmanPairsTrader
+            if "_kalman_live" not in dir():
+                globals()["_kalman_live"] = KalmanPairsTrader(
+                    transition_covariance=1e-4, observation_covariance=1e-2,
+                    z_entry=2.0, z_exit=0.5, warmup_bars=20,
+                )
+            result = globals()["_kalman_live"].step(eth, btc)
+            if result["signal"] != 0:
+                sig = "BUY_ETH" if result["signal"] > 0 else "SELL_ETH"
+                STRATEGIES["Kalman Pairs"]["signals"].append({
+                    "time":time.time(), "signal":sig,
+                    "strength":abs(result["z_score"])
+                })
+        except: pass
 
     # Momentum: Bollinger
     if len(btc_prices)>=20:

live/paper_trader.py

@@ -270,6 +270,23 @@ def compute_signals():
                 STRATEGIES["Pairs Trading"]["signals"].append({"time":time.time(),"signal":"SELL_ETH","strength":z})
             elif z < -1.5:
                 STRATEGIES["Pairs Trading"]["signals"].append({"time":time.time(),"signal":"BUY_ETH","strength":abs(z)})
+        # Kalman Pairs: adaptive hedge ratio
+        if len(btc_prices)>=20 and len(eth_prices)>=20:
+            try:
+                from strategies.kalman_pairs import KalmanPairsTrader
+                if "_kalman_paper" not in dir():
+                    globals()["_kalman_paper"] = KalmanPairsTrader(
+                        transition_covariance=1e-4, observation_covariance=1e-2,
+                        z_entry=2.0, z_exit=0.5, warmup_bars=20,
+                    )
+                result = globals()["_kalman_paper"].step(eth, btc)
+                if result["signal"] != 0:
+                    sig = "BUY_ETH" if result["signal"] > 0 else "SELL_ETH"
+                    STRATEGIES["Kalman Pairs"]["signals"].append({
+                        "time": time.time(), "signal": sig,
+                        "strength": abs(result["z_score"])
+                    })
+            except: pass
 
     # Momentum Breakout
     if len(btc_prices) >= 20: