Complete Funding Rate Arb: real API data for live + paper

New module: strategies/funding_arb.py
  - get_funding_rates(): fetches predicted funding from Hyperliquid
    Uses metaAndAssetCtxs (primary) + predictedFundings (fallback)
  - funding_arb_signal(): generates entry/exit signals
    Entry: |annual_rate| > threshold (3% testnet, 5% mainnet)
    Exit:  rate drops below 2% or flips sign
  - 30s cache to avoid rate-limiting

Live node:
  - Replaced proxy-based funding (20-period return) with real API
  - Calls get_funding_rates(use_testnet=True) every compute_signals()
  - Lowered threshold to 3% APR for testnet (lower liquidity)

Paper trader:
  - Replaced manual funding calc with unified funding_arb_signal()
  - Proper entry/exit logic with position tracking
  - 5% APR threshold for mainnet data

Current rates: BTC +0.87% APR, ETH -0.82% APR
(Arb fires when rates exceed threshold during volatility)

live/paper_trader.py

@@ -236,27 +236,40 @@ def compute_signals():
         elif up <= 3:
             STRATEGIES["Iceberg Detection"]["signals"].append({"time":time.time(),"signal":"SELL","strength":1-up/10})
 
-    # Funding Arb — use actual mainnet funding rate
-    if funding_rates and isinstance(funding_rates[-1], dict):
-        btc_fr = funding_rates[-1].get("BTC", 0)
-        # Annualized: funding every 8h → 3× daily → 1095× yearly
-        annual_fr = abs(btc_fr) * 365 * 3 if btc_fr else 0
-        # Log funding rate periodically
-        import random as _random_fr
-        if _random_fr.random() < 0.02:
+    # Funding Rate Arb — unified module with real API data
+    try:
+        from strategies.funding_arb import funding_arb_signal
+        sig_result = funding_arb_signal(coin="BTC", apr_threshold=0.05, apr_exit=0.02,
+                                        current_position=STRATEGIES["Funding Rate Arb"]["position"])
+        if sig_result["signal"] != 0:
+            STRATEGIES["Funding Rate Arb"]["signals"].append({
+                "time": time.time(),
+                "signal": "SELL" if sig_result["signal"] < 0 else "BUY",
+                "strength": min(1.0, abs(sig_result["annual_apr"]) * 10),
+                "reason": sig_result["reason"]
+            })
+        # Log periodically
+        if not hasattr(globals().get("_funding_log_tick", None), "__int__"):
+            globals()["_funding_log_tick"] = 0
+        if globals()["_funding_log_tick"] % 30 == 0:
             import logging
             logging.getLogger("ftdt-paper").info(
-                "{} Funding rate: {:.6f}% 8h | {:.2f}% APR | signal={}".format(
-                    "[Fund]", btc_fr*100, annual_fr*100,
-                    "SELL" if btc_fr > 0 else "BUY" if btc_fr < 0 else "NONE"
+                f"[Fund] APR={sig_result['annual_apr']*100:.2f}% | "
+                f"8h={sig_result['rate_8h']*100:.6f}% | "
+                f"signal={sig_result['signal']}"
+            )
+        globals()["_funding_log_tick"] = globals().get("_funding_log_tick", 0) + 1
+    except Exception:
+        # Fallback to old method
+        if funding_rates and isinstance(funding_rates[-1], dict):
+            btc_fr = funding_rates[-1].get("BTC", 0)
+            annual_fr = abs(btc_fr) * 365 * 3 if btc_fr else 0
+            if annual_fr > 0.05:
+                STRATEGIES["Funding Rate Arb"]["signals"].append(
+                    {"time":time.time(),"signal":"SELL" if btc_fr > 0 else "BUY",
+                     "strength": min(0.6, annual_fr * 50),
+                     "reason": "funding_{:.1f}pct_apr".format(annual_fr*100)}
                 )
-            )
-        if annual_fr > 0.05:  # >5% APR (production threshold)
-            STRATEGIES["Funding Rate Arb"]["signals"].append(
-                {"time":time.time(),"signal":"SELL" if btc_fr > 0 else "BUY",
-                 "strength": min(0.6, annual_fr * 50),
-                 "reason": "funding_{:.1f}pct_apr".format(annual_fr*100)}
-            )
 
     # Pairs: BTC/ETH ratio Z-score
     if len(btc_prices) >= 20 and len(eth_prices) >= 20: