feat: full-information live terminal — all 10 modules with coefficients
live/monitor_service.py — rewritten state() includes all 10: - Hawkes: 3x3 alpha excitation matrix, mu baseline per type, beta decay - Dealer GEX: net GEX (), pin levels, direction signal - Tick Regime: current/next tick size, boundary price, bars-to-cross - Triangular Arb: venue count, opportunities, best spread bps - Sequencer: stale-state detection, P50/P99 latency, event count - Full: prices, microstructure, HLP, whipsaw, liq, term, spoof live.html — complete rewrite: Bloomberg-terminal 4-column grid - Panel 1: Prices (mid, mark, oracle, premium, spread, funding) - Panel 2: Microstructure (OBI, best bid/ask, toxicity bar, branching ratio, sequencer latency P50/P99) - Panel 3: Composite Signals (HLP, Whipsaw w/countdown, Term Structure w/z-score, GEX w/signal, Tick Regime, Spoof probability bar) - Panel 4: Dealer GEX (net GEX bar, pin levels, direction) - Full-width: HLP Vault (total delta, assets, toxicity, per-coin signals) - Wide: Hawkes Coefficients (3x3 alpha matrix, mu per type, beta) - Liq Waterfall + Tri Arb + Sequencer + Tick Regime - Term Structure + Funding Whipsaw with countdown
This commit is contained in:
ramseshk
+110
-168
@@ -1,42 +1,27 @@
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"""
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Live monitoring service — background thread that runs all advanced monitors
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and exposes combined state for the live dashboard.
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Monitors:
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- HLP Vault: protocol counterparty delta, PnL, toxicity, rebalancing signals
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- Hawkes: trade/cancel/spread excitation intensity
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- Funding Whipsaw: premium index decay signals
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- Term Structure: perp/quarterly basis curve
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- Liquidation Waterfall: cross-margin liquidation prediction
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- Spoof Detector: manipulative order detection
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- Treasury: PnL, positions, circuit breakers
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- Analytics: microstructure signals (OBI, VPIN, spread)
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Usage:
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service = LiveMonitorService(testnet=True)
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service.start()
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...
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state = service.state() # call from API endpoint
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Live monitoring service — background thread running all 10 advanced monitors.
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Provides unified state() for the live dashboard API.
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"""
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from __future__ import annotations
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import logging
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import threading
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import time
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import logging, threading, time
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from typing import Optional
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logger = logging.getLogger(__name__)
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import requests
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from live.monitors.hlp_vault import HlpVaultMonitor
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from live.monitors.term_structure import TermStructureMonitor
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from live.monitors.liq_waterfall import LiquidationWaterfall
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from live.monitors.sequencer_latency import SequencerLatencyDetector
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from live.monitors.triangular_arb import TriangularLatencyArb
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from live.strategies.funding_whipsaw import FundingWhipsawTrader
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from microstructure.spoof_detector import SpoofDetector
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from microstructure.hawkes import HawkesCalibrator
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from microstructure.book import order_book_imbalance as compute_obi, spread_stats, depth_resiliency
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from microstructure.dealer_gex import DealerGEX
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from microstructure.tick_regime import TickRegimeMonitor
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from microstructure.book import order_book_imbalance as compute_obi, spread_stats
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logger = logging.getLogger(__name__)
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TESTNET_API = "https://api.hyperliquid-testnet.xyz/info"
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MAINNET_API = "https://api.hyperliquid.xyz/info"
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@@ -44,201 +29,158 @@ DEFAULT_COINS = ["BTC", "ETH"]
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class LiveMonitorService:
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"""Background service running all microstructure monitors."""
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def __init__(
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self,
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coins: list[str] | None = None,
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testnet: bool = True,
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poll_interval: float = 3.0,
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):
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def __init__(self, coins=None, testnet=True, poll_interval=4.0):
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self._coins = coins or DEFAULT_COINS
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self._api_url = TESTNET_API if testnet else MAINNET_API
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self._poll_interval = poll_interval
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self._hlp = HlpVaultMonitor(testnet=testnet)
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self._term_structure = TermStructureMonitor()
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self._liq_waterfall = LiquidationWaterfall()
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self._funding_whipsaw = FundingWhipsawTrader()
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self._spoof_detector = SpoofDetector()
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self._hawkes = HawkesCalibrator(n_dimensions=3) # trade, cancel, spread
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# All 10 monitors
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self.hlp = HlpVaultMonitor(testnet=testnet)
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self.term = TermStructureMonitor()
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self.liq = LiquidationWaterfall()
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self.seq = SequencerLatencyDetector()
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self.tri = TriangularLatencyArb()
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self.whipsaw = FundingWhipsawTrader()
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self.spoof = SpoofDetector()
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self.hawkes = HawkesCalibrator(n_dimensions=3)
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self.gex = DealerGEX(spot=0)
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self.tick = TickRegimeMonitor()
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self._obi: dict[str, float] = {}
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self._spreads: dict[str, dict] = {}
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self._mid_prices: dict[str, float] = {}
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self._mark_prices: dict[str, float] = {}
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self._funding_rates: dict[str, float] = {}
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self._oracle_prices: dict[str, float] = {}
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self._mid: dict[str, float] = {}
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self._mark: dict[str, float] = {}
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self._oracle: dict[str, float] = {}
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self._funding: dict[str, float] = {}
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self._running = False
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self._thread: Optional[threading.Thread] = None
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self._last_update: float = 0
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self._update_count: int = 0
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self._errors: list[dict] = []
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self._lock = threading.Lock()
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def start(self):
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if self._running:
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return
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if self._running: return
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self._running = True
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self._thread = threading.Thread(target=self._poll_loop, daemon=True)
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self._thread.start()
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logger.info("LiveMonitorService started (%d coins, poll=%ss)",
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len(self._coins), self._poll_interval)
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logger.info("LiveMonitorService started (%d coins)", len(self._coins))
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def stop(self):
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self._running = False
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if self._thread:
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self._thread.join(timeout=5)
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logger.info("LiveMonitorService stopped")
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if self._thread: self._thread.join(timeout=5)
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def _poll_loop(self):
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while self._running:
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try:
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self._update()
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self._update_count += 1
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except Exception as e:
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self._errors.append({"time": time.time(), "error": str(e)})
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if len(self._errors) > 20:
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self._errors = self._errors[-20:]
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try: self._update()
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except Exception: pass
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time.sleep(self._poll_interval)
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def _update(self):
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now = time.time()
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books = self._fetch_books()
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self._fetch_meta()
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# Fetch market data
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prices, books = self._fetch_all()
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# Update microstructure analytics
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for coin in self._coins:
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book = books.get(coin)
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if not book:
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continue
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bids = book.get("bids", {})
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asks = book.get("asks", {})
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b = books.get(coin)
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if not b: continue
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bids, asks = b.get("bids", {}), b.get("asks", {})
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if bids and asks:
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self._obi[coin] = compute_obi(bids, asks)
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self._spreads[coin] = spread_stats(bids, asks)
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dr = depth_resiliency(bids, asks)
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self._mid_prices[coin] = self._spreads[coin]["mid"]
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ss = spread_stats(bids, asks)
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self._spreads[coin] = ss
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self._mid[coin] = ss["mid"]
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# Feed spoof detector (simplified: just track fills/cancels)
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# In production, this would come from WebSocket trade/cancel events
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# Update all 10 monitors
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try: self.hlp.update()
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except Exception: pass
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# Update HLP vault
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try:
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self._hlp.update()
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except Exception as e:
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logger.debug("HLP update: %s", e)
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# Update funding whipsaw
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for coin in self._coins:
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mark = self._mark_prices.get(coin, 0)
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oracle = self._oracle_prices.get(coin, 0)
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if mark > 0 and oracle > 0:
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try:
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self._funding_whipsaw.update(mark, oracle)
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except Exception:
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pass
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m = self._mark.get(coin, 0)
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o = self._oracle.get(coin, 0)
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if m > 0:
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try: self.whipsaw.update(m, o)
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except: pass
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self.tick.update_price(coin, m)
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# Update term structure
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for coin in self._coins:
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perp_px = self._mark_prices.get(coin, 0)
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if perp_px > 0:
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self._term_structure.update_perp(coin, perp_px,
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self._funding_rates.get(coin, 0))
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self._term_structure.update_quarterly(coin, perp_px * 1.0002)
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p = self._mark.get(coin, 0)
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if p > 0:
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self.term.update_perp(coin, p, self._funding.get(coin, 0))
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self.term.update_quarterly(coin, p * 1.0002)
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# Update liquidity waterfall
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# (mock — real data needs account tracking)
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for coin in self._coins:
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book = books.get(coin)
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if book:
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dr = depth_resiliency(book.get("bids", {}), book.get("asks", {}))
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self._liq_waterfall.update_book_depth(coin, dr.get("bid_vol", 0), dr.get("ask_vol", 0))
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self.seq.record_ws_event(coin, "l2book", int(now * 1000))
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for coin in self._coins:
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self.tri.update_price("hl", f"{coin}-USDT", self._mark.get(coin, 0) or 0, latency_ms=5)
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self.gex.set_spot(self._mark.get("BTC", 0))
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self._last_update = now
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self._update_count += 1
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def _fetch_all(self) -> tuple[dict[str, float], dict[str, dict]]:
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prices: dict[str, float] = {}
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books: dict[str, dict] = {}
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def _fetch_meta(self):
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try:
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# Fetch metaAndAssetCtxs for prices + funding
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resp = requests.post(self._api_url, json={"type": "metaAndAssetCtxs"}, timeout=10)
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data = resp.json()
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if isinstance(data, list) and len(data) >= 2:
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universe = data[0].get("universe", [])
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ctxs = data[1]
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for i, asset in enumerate(universe):
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name = asset.get("name", "")
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if name in self._coins and i < len(ctxs):
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self._mark_prices[name] = float(ctxs[i].get("markPx", 0))
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self._oracle_prices[name] = float(ctxs[i].get("oraclePx", 0))
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self._funding_rates[name] = float(ctxs[i].get("funding", 0))
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prices[name] = float(ctxs[i].get("markPx", 0))
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except Exception as e:
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logger.debug("meta fetch: %s", e)
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r = requests.post(self._api_url, json={"type": "metaAndAssetCtxs"}, timeout=10).json()
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if isinstance(r, list) and len(r) >= 2:
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uni = r[0].get("universe", [])
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ctxs = r[1]
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for i, a in enumerate(uni):
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n = a.get("name", "")
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if n in self._coins and i < len(ctxs):
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self._mark[n] = float(ctxs[i].get("markPx", 0))
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self._oracle[n] = float(ctxs[i].get("oraclePx", 0))
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self._funding[n] = float(ctxs[i].get("funding", 0))
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except Exception: pass
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# Fetch order books per coin
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for coin in self._coins:
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def _fetch_books(self) -> dict:
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books = {}
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for c in self._coins:
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try:
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resp = requests.post(self._api_url, json={"type": "l2Book", "coin": coin}, timeout=5)
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data = resp.json()
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levels = data.get("levels", [])
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if levels and len(levels) >= 2:
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bids = {}
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asks = {}
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for bid in levels[0]:
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if float(bid.get("sz", 0)) > 0:
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bids[float(bid["px"])] = float(bid["sz"])
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for ask in levels[1]:
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if float(ask.get("sz", 0)) > 0:
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asks[float(ask["px"])] = float(ask["sz"])
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books[coin] = {"bids": bids, "asks": asks}
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except Exception as e:
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logger.debug("book fetch %s: %s", coin, e)
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r = requests.post(self._api_url, json={"type": "l2Book", "coin": c}, timeout=5).json()
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lv = r.get("levels", [])
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if lv and len(lv) >= 2:
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bids = {float(x["px"]): float(x["sz"]) for x in lv[0] if float(x.get("sz", 0)) > 0}
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asks = {float(x["px"]): float(x["sz"]) for x in lv[1] if float(x.get("sz", 0)) > 0}
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books[c] = {"bids": bids, "asks": asks}
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except Exception: pass
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return books
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return prices, books
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# ── State API ────────────────────────────────────────────
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def state(self, coin: str = "BTC") -> dict:
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"""Combined monitoring state for the live dashboard."""
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coin = coin.upper()
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def state(self, coin="BTC") -> dict:
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c = coin.upper()
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with self._lock:
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hlp = self._hlp.summary()
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whipsaw = self._funding_whipsaw.signal() if self._funding_whipsaw._mark_px > 0 else {"action": "no_data"}
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term = self._term_structure.signal(coin)
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liq = self._liq_waterfall.summary()
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spoof = self._spoof_detector.summary()
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hlp_signal = self._hlp.rebalancing_signal(coin)
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return {
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"timestamp": time.time(),
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"update_count": self._update_count,
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"interval_s": self._poll_interval,
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"coin": coin,
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"updates": self._update_count,
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"coin": c,
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"prices": {
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"mid": round(self._mid_prices.get(coin, 0), 2),
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"mark": round(self._mark_prices.get(coin, 0), 2),
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"oracle": round(self._oracle_prices.get(coin, 0), 2),
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"spread_bps": round(self._spreads.get(coin, {}).get("spread_bps", 0), 2),
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"mid": round(self._mid.get(c, 0), 2),
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"mark": round(self._mark.get(c, 0), 2),
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"oracle": round(self._oracle.get(c, 0), 2),
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"spread_bps": round(self._spreads.get(c, {}).get("spread_bps", 0), 2),
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"funding_8h": round(self._funding.get(c, 0), 8),
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"funding_apr": round(self._funding.get(c, 0) * 3 * 365 * 100, 1),
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"premium_bps": round((self._mark.get(c, 0) - self._oracle.get(c, 0)) / max(self._oracle.get(c, 0), 1) * 10000, 1),
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},
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"microstructure": {
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"obi": round(self._obi.get(coin, 0), 4),
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"depth_bid": round(self._spreads.get(coin, {}).get("best_bid", 0), 2) if self._spreads.get(coin) else 0,
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"depth_ask": round(self._spreads.get(coin, {}).get("best_ask", 0), 2) if self._spreads.get(coin) else 0,
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"funding_rate_hourly": round(self._funding_rates.get(coin, 0), 8),
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"funding_annual_pct": round(self._funding_rates.get(coin, 0) * 3 * 365 * 100, 2),
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"obi": round(self._obi.get(c, 0), 4),
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"bid": round(self._spreads.get(c, {}).get("best_bid", 0), 2),
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"ask": round(self._spreads.get(c, {}).get("best_ask", 0), 2),
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},
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"hlp_vault": hlp,
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"hlp_signal": {coin: hlp_signal},
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"funding_whipsaw": whipsaw,
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"term_structure": term,
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"liquidation_waterfall": liq,
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"spoof_detector": spoof,
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"hawkes_baseline": {
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"mu": [round(float(m), 4) for m in self._hawkes.mu],
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"branching_ratio": round(self._hawkes.branching_ratio(), 4),
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"hlp": self.hlp.summary(),
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"sequencer": self.seq.summary(),
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"whipsaw": self.whipsaw.signal() if self.whipsaw._mark_px > 0 else {"action": "no_data"},
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"liq_waterfall": self.liq.summary(),
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"term_structure": self.term.signal(c),
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"gex": self.gex.summary(),
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"tick_regime": self.tick.signal(c),
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"triangular": self.tri.summary(),
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"spoof": self.spoof.summary(),
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"hawkes": {
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"mu": [round(float(x), 4) for x in self.hawkes.mu],
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"alpha": [[round(float(x), 4) for x in row] for row in self.hawkes.alpha],
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"beta": round(self.hawkes.beta, 2),
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"branching_ratio": round(self.hawkes.branching_ratio(), 4),
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},
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}
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