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

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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.
This commit is contained in:
ramseshk
2026-08-05 07:05:00 +00:00
parent 5004b23331
commit 84efb4014a
6 changed files with 11691 additions and 0 deletions
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live/node.py
+18
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@@ -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: