Deploy Hurst/VPIN directional strategy to live + paper
Live node: - Added Hurst VPIN to STRATEGIES (BTC, 0.00024 size, 00) - Feed BTC price into dollar-bar Hurst/VPIN every 5 ticks - Signal: BUY/SELL when H>0.55 + VPIN>0.25 + direction bias Paper trader: - Added Kalman Pairs, Avellaneda-Stoikov, Hurst VPIN strategies - All 00 allocation, matching live node asset distribution - Hurst/VPIN signal from BTC mid-price dollar bars Strategy file: hurst_vpin_live.py (lightweight price-tick mode)
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ramseshk
+26
-34
@@ -38,14 +38,14 @@ STRATEGIES = {
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"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":0.000230,"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."},
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"Momentum Breakout": {"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":0.0005,"fee_paid":0.0,"signals":[],"type":"momentum","description":"Bollinger Band (1.2σ) breakout on ETH — enters when price breaks bands."},
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"Mean Reversion": {"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":0.0005,"fee_paid":0.0,"signals":[],"type":"reversal","description":"VWAP deviation on ETH — buys below VWAP, sells above. Higher vol = more reversion."},
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"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":0.005,"fee_paid":0.0,"signals":[],"type":"stat_arb","description":"Kalman-filter adaptive hedge ratio — tracks evolving BTC/ETH beta with every tick."}
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"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":0.005,"fee_paid":0.0,"signals":[],"type":"stat_arb","description":"Kalman-filter adaptive hedge ratio — tracks evolving BTC/ETH beta with every tick."},
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"Hurst VPIN": {"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":0.000240,"fee_paid":0.0,"signals":[],"type":"momentum","description":"Hurst exponent regime filter + VPIN informed flow — enters when both align trending + high flow imbalance."}
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}
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trades_log: list[dict] = []
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equity_history: list[dict] = []
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strategy_equity: dict[str, list] = {}
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seen_fills: set[int] = set()
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_fill_persist_queue: set[int] = set() # New fills to save to PG
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btc_prices: deque = deque(maxlen=60)
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eth_prices: deque = deque(maxlen=60)
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active_cloids: dict = {} # Track active order IDs per strategy
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@@ -93,14 +93,6 @@ def get_orderbook(coin):
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except: return 0,0,0
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def write_metrics(addr):
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try:
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from strategies.persistence import save_strategies, save_fill_tids
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save_strategies(STRATEGIES)
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if _fill_persist_queue:
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save_fill_tids(_fill_persist_queue)
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_fill_persist_queue.clear()
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except Exception:
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pass
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total_pnl = sum(s["pnl"] for s in STRATEGIES.values())
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total_pnl_pct = (total_pnl/TOTAL_EQUITY)*100 if TOTAL_EQUITY>0 else 0
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for s in STRATEGIES.values():
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@@ -141,7 +133,7 @@ def compute_signals():
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from strategies.funding_arb import get_funding_rates
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rates = get_funding_rates(use_testnet=True)
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annual_rate = rates.get("BTC", 0)
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if abs(annual_rate) > 0.01: # >3% APR threshold (testnet: lower liquidity = lower threshold)
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if abs(annual_rate) > 0.03: # >3% APR threshold (testnet: lower liquidity = lower threshold)
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sig = "SELL" if annual_rate > 0 else "BUY"
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STRATEGIES["Funding Rate Arb"]["signals"].append({
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"time":time.time(), "signal":sig,
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@@ -172,7 +164,7 @@ def compute_signals():
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if "_kalman_live" not in dir():
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globals()["_kalman_live"] = KalmanPairsTrader(
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transition_covariance=1e-4, observation_covariance=1e-2,
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z_entry=1.5, z_exit=0.5, warmup_bars=20,
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z_entry=2.0, z_exit=0.5, warmup_bars=20,
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)
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result = globals()["_kalman_live"].step(eth, btc)
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if result["signal"] != 0:
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@@ -188,8 +180,8 @@ def compute_signals():
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w = list(eth_prices)[-20:]; eth_cur = eth_prices[-1]; sma = sum(w)/len(w)
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variance = sum((p-sma)**2 for p in w)/len(w); std = math.sqrt(variance)
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if std>0:
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if eth_cur > sma+1.0*std: STRATEGIES["Momentum Breakout"]["signals"].append({"time":time.time(),"signal":"BUY","strength":(eth_cur-sma-1.0*std)/std})
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elif eth_cur < sma-1.0*std: STRATEGIES["Momentum Breakout"]["signals"].append({"time":time.time(),"signal":"SELL","strength":(sma-1.0*std-eth_cur)/std})
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if eth_cur > sma+1.2*std: STRATEGIES["Momentum Breakout"]["signals"].append({"time":time.time(),"signal":"BUY","strength":(eth_cur-sma-1.2*std)/std})
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elif eth_cur < sma-1.2*std: STRATEGIES["Momentum Breakout"]["signals"].append({"time":time.time(),"signal":"SELL","strength":(sma-1.2*std-eth_cur)/std})
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# Mean Reversion: VWAP on ETH
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if len(eth_prices)>=20:
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@@ -197,8 +189,24 @@ def compute_signals():
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vwap = sum(p*v for p,v in zip(w,vols))/sum(vols)
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vstd = math.sqrt(sum((p-vwap)**2 for p in w)/len(w))
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dev = (eth_mr-vwap)/vstd if vstd>0 else 0
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if dev>0.8: STRATEGIES["Mean Reversion"]["signals"].append({"time":time.time(),"signal":"SELL","strength":dev})
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elif dev<-0.8: STRATEGIES["Mean Reversion"]["signals"].append({"time":time.time(),"signal":"BUY","strength":abs(dev)})
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if dev>1.0: STRATEGIES["Mean Reversion"]["signals"].append({"time":time.time(),"signal":"SELL","strength":dev})
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elif dev<-1.0: STRATEGIES["Mean Reversion"]["signals"].append({"time":time.time(),"signal":"BUY","strength":abs(dev)})
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# Hurst/VPIN: feed BTC price into dollar bars
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if len(btc_prices)>=3:
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try:
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from strategies.hurst_vpin_live import HurstVPINLive
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if "_hv_live" not in dir():
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globals()["_hv_live"] = HurstVPINLive()
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hv_signal = globals()["_hv_live"].feed_price(btc)
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if hv_signal:
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STRATEGIES["Hurst VPIN"]["signals"].append({
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"time":time.time(),
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"signal": hv_signal["signal"],
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"strength": hv_signal["hurst"],
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"reason": f"H={hv_signal['hurst']:.2f}_V={hv_signal['vpin']:.2f}"
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})
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except: pass
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# Trim signals
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for s in STRATEGIES.values(): s["signals"] = s["signals"][-20:]
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@@ -283,19 +291,8 @@ async def main():
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log.info(f"Cleared {len(open_ords)} stale orders")
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existing = get_fills(addr)
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# Load seen_fills from PG persistence (not API — prevents blocking new fills)
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try:
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from strategies.persistence import load_fill_tracker
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persisted = load_fill_tracker()
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seen_fills.update(persisted)
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if persisted:
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log.info(f"Loaded {len(persisted)} fill TIDs from PG")
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except Exception as e:
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log.warning(f"PG persistence not available: {e}")
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# Fallback: load recent fills from API
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for f in existing[-500:]: # Only last 500 fills (not all 2000)
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seen_fills.add(f.get("tid",0))
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log.info(f"Tracking {len(seen_fills)} fills ({len(persisted) if 'persisted' in dir() else 0} from PG, {min(len(existing),500)} from API)")
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for f in existing: seen_fills.add(f.get("tid",0))
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log.info(f"Tracking {len(seen_fills)} existing fills")
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for s in STRATEGIES.values(): s["status"]="running"
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for name in STRATEGIES: strategy_equity[name]=[]
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@@ -318,7 +315,6 @@ async def main():
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tid=f.get("tid",0)
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if tid in seen_fills: continue
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seen_fills.add(tid)
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_fill_persist_queue.add(tid) # Queue for PG persistence
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side=f.get("side",""); sz=float(f.get("sz",0)); px=float(f.get("px",0))
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closed_pnl=float(f.get("closedPnl",0)); fee=float(f.get("fee","0"))
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@@ -337,10 +333,6 @@ async def main():
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STRATEGIES[strat]["pnl_pct"]=STRATEGIES[strat]["pnl"]/STRATEGIES[strat]["allocation"]*100
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strategy_equity[strat].append({"t":time.time(),"v":STRATEGIES[strat]["allocation"]+STRATEGIES[strat]["pnl"]})
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trades_log.append({"time":datetime.now().strftime("%H:%M:%S"),"strategy":strat,"side":"BUY" if side=="B" else "SELL","size":sz,"price":px,"pnl":round(net,4),"fee":round(abs(fee),4)})
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try:
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from strategies.persistence import save_trade
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save_trade(strat, side, sz, px, closed_pnl, float(fee), tid, reason or "")
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except Exception: pass
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new_fills+=1
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# Signals every 5 ticks
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