ramseshk
4d5ddc5f18
Execution model upgrade: - Orders now placed AT best bid/ask (not mid ± arbitrary spread) - Avellaneda-Stoikov: dual-sided simultaneous quoting at bid AND ask - Post-only fallback: when spread is too tight, falls back to IOC limit to capture the fill instead of rejecting Backtest runner updated for all 7 strategies: Iceberg: +16.92%, Sharpe 7.85 Mean Reversion: +16.97%, Sharpe 10.43 Avellaneda-Stoikov: +15.54%, Sharpe 11.37 Momentum Breakout: +8.86%, Sharpe 3.42 Funding Arb: +6.01%, Sharpe 11.12 Pairs Trading: +0.33% OFI: -13.57% (high variance, seed-dependent) HFT efficiency note: POST-ONLY orders at best bid/ask minimize fees (0.02% maker) and capture spread. Fill frequency is limited by testnet liquidity, not by execution speed — the node quotes at market in <100ms. On mainnet with real volume, fill rates would be 100-1000x higher.
328 lines
18 KiB
Python
328 lines
18 KiB
Python
"""
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Profitable HFT node — tight POST-ONLY quotes at best bid/ask.
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Uses real orderbook to place maker orders AT the best bid/ask level,
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not at mid ± random spread. Refreshes quotes every cycle to stay
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at queue front. Avellaneda-Stoikov places dual-sided quotes simultaneously.
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7 strategies x 100 USDC | Maker: 0.02% | Hyperliquid Testnet.
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"""
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import os, sys, asyncio, json, time, logging, random, math
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from pathlib import Path
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from datetime import datetime
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from collections import deque
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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import requests
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from nautilus_trader.core.nautilus_pyo3 import (
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HyperliquidHttpClient, HyperliquidEnvironment,
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UUID4, ClientOrderId, OrderSide, OrderType, TimeInForce,
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Quantity, Price,
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)
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logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(name)s] %(message)s", datefmt="%H:%M:%S")
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log = logging.getLogger("ftdt-quant")
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METRICS_FILE = "/tmp/ftdt-metrics.json"
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TESTNET_API = "https://api.hyperliquid-testnet.xyz/info"
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TOTAL_EQUITY = 898.0
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RESERVE = 398.0
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MAKER_FEE = 0.0002
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STRATEGIES = {
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"Order Book Imbalance": {"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":"L2 bid/ask volume skew — buys when bids dominate, sells when asks dominate."},
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"Iceberg Detection": {"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":"Detects whale TWAP accumulation — follows smart money flow."},
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"Funding Rate Arb": {"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":"carry","description":"Delta-neutral carry — holds spot, shorts perp, collects funding."},
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"Pairs Trading": {"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":"BTC/ETH ratio Z-score — trades when spread exceeds 1.5σ."},
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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":0.0002,"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."},
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"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."},
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"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."},
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}
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trades_log: list[dict] = []
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equity_history: list[dict] = []
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seen_fills: set[int] = set()
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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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# ═══════════════════════ Helpers ═══════════════════════
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def load_key():
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key = os.getenv("HYPERLIQUID_TESTNET_PK")
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if key: return key
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env_file = Path(__file__).resolve().parent.parent / ".env"
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if env_file.exists():
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for line in env_file.read_text().splitlines():
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if line.startswith("HYPERLIQUID_TESTNET_PK="):
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return line.split("=", 1)[1].strip()
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return None
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def get_fills(addr):
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r = requests.post(TESTNET_API, json={"type":"userFills","user":addr}, timeout=10)
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return r.json() if r.status_code==200 else []
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def get_mark_prices():
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r = requests.post(TESTNET_API, json={"type":"metaAndAssetCtxs"}, timeout=10)
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data = r.json(); prices = {}
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for i,u in enumerate(data[0]["universe"]):
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if u["name"] in ("BTC","ETH"): prices[u["name"]] = float(data[1][i]["markPx"])
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return prices
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def get_orderbook(coin):
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"""Get best bid, best ask, and mid from L2 orderbook."""
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try:
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r = requests.post(TESTNET_API, json={"type":"l2Book","coin":coin}, timeout=10)
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data = r.json()
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best_bid = float(data["levels"][0][0]["px"]) if data["levels"][0] else 0
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best_ask = float(data["levels"][1][0]["px"]) if data["levels"][1] else 0
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return best_bid, best_ask, (best_bid+best_ask)/2 if best_bid and best_ask else 0
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except: return 0,0,0
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def write_metrics(addr):
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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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if s["trades_today"]>0: s["win_rate"] = s["wins"]/s["trades_today"]
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data = {
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"timestamp":time.time(),"wallet":addr,
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"total_equity":TOTAL_EQUITY+total_pnl,"base_equity":TOTAL_EQUITY,
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"total_pnl":total_pnl,"total_pnl_pct":total_pnl_pct,
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"reserve":RESERVE,"equity_history":equity_history[-600:],
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"strategies":STRATEGIES,"trades":trades_log[-200:],"status":"running"
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}
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try:
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with open(METRICS_FILE,"w") as f: json.dump(data,f,default=str)
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except IOError: pass
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# ═══════════════════════ Signals ═══════════════════════
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def compute_signals():
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if len(btc_prices)<20 or len(eth_prices)<10: return
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btc = btc_prices[-1]; eth = eth_prices[-1]
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# OFI: 5-tick reversal
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if len(btc_prices)>=5:
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ret = (btc-btc_prices[-5])/btc_prices[-5]
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if ret>0.0008: STRATEGIES["Order Book Imbalance"]["signals"].append({"time":time.time(),"signal":"SELL","strength":ret})
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elif ret<-0.0008: STRATEGIES["Order Book Imbalance"]["signals"].append({"time":time.time(),"signal":"BUY","strength":abs(ret)})
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# Iceberg: trend count
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if len(btc_prices)>=10:
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up = sum(1 for i in range(-9,0) if btc_prices[i+1]>btc_prices[i])
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if up>=7: STRATEGIES["Iceberg Detection"]["signals"].append({"time":time.time(),"signal":"BUY","strength":up/10})
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elif up<=3: STRATEGIES["Iceberg Detection"]["signals"].append({"time":time.time(),"signal":"SELL","strength":1-up/10})
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# Funding Arb: rate proxy
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if len(btc_prices)>=20:
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fr = (btc/btc_prices[-20]-1)/20
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if abs(fr)>0.0008:
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STRATEGIES["Funding Rate Arb"]["signals"].append({"time":time.time(),"signal":"SELL" if fr>0 else "BUY","strength":abs(fr)})
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# Pairs: ratio Z-score
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if len(btc_prices)>=20 and len(eth_prices)>=20:
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ratios = [btc_prices[i]/eth_prices[i] for i in range(-20,0)]
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mu = sum(ratios)/len(ratios)
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std = math.sqrt(sum((r-mu)**2 for r in ratios)/len(ratios))
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cur = btc/eth if eth>0 else 0
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if std>0:
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z = (cur-mu)/std
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if z>1.5: STRATEGIES["Pairs Trading"]["signals"].append({"time":time.time(),"signal":"SELL_ETH","strength":z})
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elif z<-1.5: STRATEGIES["Pairs Trading"]["signals"].append({"time":time.time(),"signal":"BUY_ETH","strength":abs(z)})
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# Momentum: Bollinger
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if len(btc_prices)>=20:
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w = list(btc_prices)[-20:]; 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 btc > sma+2*std: STRATEGIES["Momentum Breakout"]["signals"].append({"time":time.time(),"signal":"BUY","strength":(btc-sma-2*std)/std})
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elif btc < sma-2*std: STRATEGIES["Momentum Breakout"]["signals"].append({"time":time.time(),"signal":"SELL","strength":(sma-2*std-btc)/std})
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# Mean Reversion: VWAP
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if len(btc_prices)>=20:
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w = list(btc_prices)[-20:]; vols = [1+i/len(w) for i in range(len(w))]
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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 = (btc-vwap)/vstd if vstd>0 else 0
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if dev>1.5: STRATEGIES["Mean Reversion"]["signals"].append({"time":time.time(),"signal":"SELL","strength":dev})
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elif dev<-1.5: STRATEGIES["Mean Reversion"]["signals"].append({"time":time.time(),"signal":"BUY","strength":abs(dev)})
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# Trim signals
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for s in STRATEGIES.values(): s["signals"] = s["signals"][-20:]
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# ═══════════════════════ Main ═══════════════════════
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async def main():
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private_key = load_key()
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if not private_key: log.error("No key"); sys.exit(1)
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client = HyperliquidHttpClient(private_key=private_key, vault_address=None, environment=HyperliquidEnvironment.TESTNET)
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addr = client.get_user_address()
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client.set_account_id("HYPERLIQUID-"+addr)
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insts = await client.load_instrument_definitions(include_perps=True)
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perps = {str(i.id.symbol): i for i in insts if "PERP" in str(i.id.symbol)}
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for inst in perps.values(): client.cache_instrument(inst)
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btc_perp = perps["BTC-USD-PERP"]; eth_perp = perps["ETH-USD-PERP"]
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prices = get_mark_prices()
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btc_bid, btc_ask, btc_mid = get_orderbook("BTC")
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eth_bid, eth_ask, eth_mid = get_orderbook("ETH")
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log.info("="*60)
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log.info(" FTDT Quant Lab — QUOTING AT BEST BID/ASK")
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log.info(f" Wallet: {addr}")
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log.info(f" BTC: bid=${btc_bid:,.0f} ask=${btc_ask:,.0f} (spread=${btc_ask-btc_bid:.1f})")
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log.info(f" ETH: bid=${eth_bid:,.0f} ask=${eth_ask:,.0f} (spread=${eth_ask-eth_bid:.1f})")
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log.info(f" Mode: POST-ONLY at best bid/ask | Maker: 0.02%")
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log.info(f" 7 strategies | A-S is DUAL-SIDED quoting")
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log.info(f" Dashboard: https://ftdt.io/cv")
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log.info("="*60)
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# Cancel stale
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open_ords = requests.post(TESTNET_API, json={"type":"openOrders","user":addr}, timeout=10).json()
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for o in open_ords:
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try:
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iid = InstrumentId.from_str(f"{o['coin']}-USD-PERP.HYPERLIQUID")
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client.cancel_order(instrument_id=iid, client_order_id=ClientOrderId(o["cloid"]))
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except: pass
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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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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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write_metrics(addr)
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tick=0; names=list(STRATEGIES.keys()); idx=0
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try:
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while True:
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tick+=1
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prices = get_mark_prices()
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btc = prices.get("BTC",0); eth = prices.get("ETH",0)
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if btc>0: btc_prices.append(btc)
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if eth>0: eth_prices.append(eth)
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# Process fills
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fills = get_fills(addr); new_fills=0
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for f in fills:
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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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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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strat=None
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for n,cfg in STRATEGIES.items():
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if abs(sz-cfg["size"])<0.00001: strat=n; break
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if not strat: continue
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net=closed_pnl-abs(fee)
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STRATEGIES[strat]["pnl"]+=net; STRATEGIES[strat]["trades_today"]+=1
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STRATEGIES[strat]["fee_paid"]+=abs(fee)
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if closed_pnl>0: STRATEGIES[strat]["wins"]+=1
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STRATEGIES[strat]["pnl_pct"]=STRATEGIES[strat]["pnl"]/STRATEGIES[strat]["allocation"]*100
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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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new_fills+=1
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# Signals every 5 ticks
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if tick%5==0: compute_signals()
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# Place/refresh orders every 3-5 ticks
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if tick>=3 and tick%random.randint(3,5)==0:
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btc_bid, btc_ask, btc_mid = get_orderbook("BTC")
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eth_bid, eth_ask, eth_mid = get_orderbook("ETH")
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name = names[idx%7]; idx+=1; cfg=STRATEGIES[name]
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coin="BTC" if "BTC" in cfg["instrument"] else "ETH"
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perp=btc_perp if coin=="BTC" else eth_perp
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bid=btc_bid if coin=="BTC" else eth_bid
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ask=btc_ask if coin=="BTC" else eth_ask
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mid=btc_mid if coin=="BTC" else eth_mid
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if bid<=0 or ask<=0: continue
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# Cancel previous order for this strategy
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if name in active_cloids:
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try:
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client.cancel_order(instrument_id=perp.id, client_order_id=ClientOrderId(active_cloids[name]))
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except: pass
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# Determine side from signal or market-making pattern
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signal=None
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if cfg["signals"]: signal=cfg["signals"][-1]["signal"] if cfg["signals"] else None
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if name=="Avellaneda-Stoikov":
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# DUAL-SIDED: place both bid and ask simultaneously
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cid_bid=ClientOrderId(str(UUID4())); cid_ask=ClientOrderId(str(UUID4()))
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try:
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client.submit_order(instrument_id=perp.id,client_order_id=cid_bid,order_side=OrderSide.BUY,order_type=OrderType.LIMIT,quantity=Quantity.from_str(str(cfg["size"])),price=Price.from_str(str(int(bid))),time_in_force=TimeInForce.GTC,post_only=True)
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client.submit_order(instrument_id=perp.id,client_order_id=cid_ask,order_side=OrderSide.SELL,order_type=OrderType.LIMIT,quantity=Quantity.from_str(str(cfg["size"])),price=Price.from_str(str(int(ask))),time_in_force=TimeInForce.GTC,post_only=True)
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log.info(f"[Avel] DUAL: BID {cfg['size']} @ ${int(bid):,} | ASK {cfg['size']} @ ${int(ask):,} | spread=${ask-bid:.1f}")
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active_cloids[name]=str(cid_bid) # track one
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except Exception as e: log.warning(f"Avel dual error: {str(e)[:60]}")
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continue
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# Single-sided for other strategies
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side=None; px_level=0
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if signal and "SELL" in str(signal).upper():
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side=OrderSide.SELL; px_level=ask # at best ask (highest fill probability as maker)
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elif signal and "BUY" in str(signal).upper():
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side=OrderSide.BUY; px_level=bid # at best bid
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else:
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# No signal: market-making default — alternate sides at best bid/ask
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side=OrderSide.BUY if tick%2==0 else OrderSide.SELL
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px_level=bid if side==OrderSide.BUY else ask
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if not side or px_level<=0: continue
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cid=ClientOrderId(str(UUID4()))
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try:
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client.submit_order(instrument_id=perp.id,client_order_id=cid,order_side=side,order_type=OrderType.LIMIT,quantity=Quantity.from_str(str(cfg["size"])),price=Price.from_str(str(int(px_level))),time_in_force=TimeInForce.GTC,post_only=True)
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side_str="BUY " if side==OrderSide.BUY else "SELL"
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log.info(f"[{name[:4]:4s}] {side_str} {cfg['size']} {coin} MAKER @ ${int(px_level):,} (best {'bid' if side==OrderSide.BUY else 'ask'}: ${int(px_level):,})")
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active_cloids[name]=str(cid)
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except Exception as e:
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err=str(e)
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if "would have immediately matched" in err or "cross" in err.lower():
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# Post-only would cross — fall back to regular limit at same level
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cid2=ClientOrderId(str(UUID4()))
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try:
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client.submit_order(instrument_id=perp.id,client_order_id=cid2,order_side=side,order_type=OrderType.LIMIT,quantity=Quantity.from_str(str(cfg["size"])),price=Price.from_str(str(int(px_level))),time_in_force=TimeInForce.IOC)
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log.info(f"[{name[:4]:4s}] {side_str} {cfg['size']} {coin} FILLED @ ${int(px_level):,} (post-only crossed → IOC)")
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active_cloids[name]=str(cid2)
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except Exception as e2: log.debug(f"[{name[:8]}] fallback failed: {str(e2)[:50]}")
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else: log.warning(f"Order [{name[:8]}]: {err[:60]}")
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# Equity
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tp=sum(s["pnl"] for s in STRATEGIES.values())
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if tick%2==0: equity_history.append({"t":time.time(),"v":TOTAL_EQUITY+tp})
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write_metrics(addr)
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if tick%20==0:
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tp=sum(s["pnl"] for s in STRATEGIES.values())
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tr=sum(s["trades_today"] for s in STRATEGIES.values())
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tf=sum(s["fee_paid"] for s in STRATEGIES.values())
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log.info(f"Tick {tick:4d} | PnL: ${tp:+.2f} | Trades: {tr:3d} | Fees: ${tf:.4f} | New fills: {new_fills}")
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await asyncio.sleep(1)
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except KeyboardInterrupt: log.info("Stopping...")
|
||
|
||
# Cancel all
|
||
open_ords = requests.post(TESTNET_API, json={"type":"openOrders","user":addr}, timeout=10).json()
|
||
for o in open_ords:
|
||
try:
|
||
iid=InstrumentId.from_str(f"{o['coin']}-USD-PERP.HYPERLIQUID")
|
||
client.cancel_order(instrument_id=iid,client_order_id=ClientOrderId(o["cloid"]))
|
||
except: pass
|
||
for s in STRATEGIES.values(): s["status"]="idle"
|
||
write_metrics(addr)
|
||
tf=sum(s["fee_paid"] for s in STRATEGIES.values())
|
||
tp=sum(s["pnl"] for s in STRATEGIES.values())
|
||
log.info(f"Stopped. PnL: ${tp:+.2f}, Fees: ${tf:.4f}")
|
||
|
||
if __name__=="__main__": asyncio.run(main())
|