ramseshk
e0be9f4d40
4 new modules with 20 tests: #22 Sequencer Latency Detector (live/monitors/sequencer_latency.py): Detects stale-state windows between WebSocket and REST API. - WebSocket vs REST timestamp delta tracking - Transport latency percentiles (p50, p99) - Liquidation-triggered stale-state detection - Stale asset identification for cross-margin arbitrage #25 Dealer GEX (microstructure/dealer_gex.py): Dealer Gamma Exposure estimation via Black-Scholes. - Per-strike gamma × OI × spot² GEX computation - Pin level detection (strikes where dealers are long gamma) - Net GEX aggregation - Signal: fade_breakout (long gamma pinning) vs ride_momentum (short gamma amplification) - nearest_pin() for distance-to-magnet calculation #30 Tick-Size Regime Exploitation (microstructure/tick_regime.py): Detects when asset price approaches tick-size boundaries. - Hyperliquid tick schedule (BTC 0.1/0.5, ETH 0.01/0.05, SOL 0.001/0.005) - Boundary approach detection with configurable threshold - Linear trend estimation for expected bars-to-cross - Signal: widen_quotes or tighten_quotes with urgency classification - Per-coin state tracking #33 Triangular Latency Arb (live/monitors/triangular_arb.py): Cross-venue A→B→C triangular arbitrage detection. - Internal triangular: BTC-USDT → ETH-BTC → ETH-USDT - Cross-venue: price discrepancy across slow/fast venues - Latency gap detection between venue pairs - Implied cross-rate computation vs direct quote - Minimum spread threshold gating
174 lines
6.9 KiB
Python
174 lines
6.9 KiB
Python
"""
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Tests for sequencer latency, dealer GEX, tick regime, triangular arb.
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"""
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from live.monitors.sequencer_latency import SequencerLatencyDetector
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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 live.monitors.triangular_arb import TriangularLatencyArb
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class TestSequencerLatency:
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def test_initial_state(self):
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sld = SequencerLatencyDetector()
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lat = sld.avg_transport_latency()
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assert lat["count"] == 0
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def test_ws_event_recording(self):
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sld = SequencerLatencyDetector()
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now = 1705312800000
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sld.record_ws_event("BTC", "l2book", now)
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lat = sld.avg_transport_latency()
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assert lat["count"] == 1
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def test_stale_detection(self):
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sld = SequencerLatencyDetector(stale_threshold_ms=100)
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sld.record_ws_event("BTC", "l2book", 1705312800000)
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sld.record_rest_event("BTC", "l2book", 1705312800200) # 200ms later
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lat = sld.ws_rest_latency("BTC", "l2book")
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assert lat is not None
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assert lat["is_stale"]
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def test_not_stale_when_close(self):
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sld = SequencerLatencyDetector(stale_threshold_ms=100)
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sld.record_ws_event("BTC", "l2book", 1705312800000)
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sld.record_rest_event("BTC", "l2book", 1705312800050) # 50ms later
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lat = sld.ws_rest_latency("BTC", "l2book")
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assert lat is not None
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assert not lat["is_stale"]
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def test_liquidation_triggers_stale_check(self):
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sld = SequencerLatencyDetector(stale_threshold_ms=10)
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sld.record_ws_event("BTC", "l2book", 1705312800000)
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sld.record_rest_event("BTC", "l2book", 1705312800100) # 100ms lag
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sld.record_liquidation("BTC", 10.0, 64000, 1705312800050)
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sig = sld.stale_state_signal()
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assert sig["signal"] == "stale_state_detected"
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assert "BTC" in sig["stale_assets"]
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def test_no_stale_without_liquidation(self):
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sld = SequencerLatencyDetector()
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sig = sld.stale_state_signal()
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assert sig["signal"] == "none"
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class TestDealerGEX:
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def test_initial_state(self):
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gex = DealerGEX(spot=64500)
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s = gex.summary()
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assert s["strikes_tracked"] == 0
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assert s["net_gex_usd"] == 0
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def test_add_strike_computes_gex(self):
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gex = DealerGEX(spot=64500)
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gex.add_strike(strike=65000, call_oi=500, put_oi=300, expiry_days=7, iv=0.60)
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gex.compute()
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s = gex.summary()
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assert s["strikes_tracked"] == 1
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assert s["net_gex_usd"] != 0 # gamma produces non-zero GEX
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def test_pin_level_detection(self):
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gex = DealerGEX(spot=64500)
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gex.add_strike(strike=64500, call_oi=500, put_oi=500, expiry_days=7, iv=0.60)
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gex.add_strike(strike=70000, call_oi=10, put_oi=10, expiry_days=30, iv=0.50)
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gex.compute()
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pin = gex.nearest_pin()
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assert pin is not None
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assert abs(pin["strike"] - 64500) < abs(pin["strike"] - 70000) # closer strike
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def test_gamma_higher_near_spot(self):
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gex = DealerGEX(spot=64500)
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gex.add_strike(strike=64500, call_oi=100, put_oi=100, expiry_days=7, iv=0.60)
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gex.add_strike(strike=70000, call_oi=100, put_oi=100, expiry_days=7, iv=0.60)
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gex.compute()
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# ATM option has higher gamma than far OTM
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atm_gex = None
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far_gex = None
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for s in gex._strikes:
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if s["strike"] == 64500:
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atm_gex = abs(s["gex_total_usd"])
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if s["strike"] == 70000:
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far_gex = abs(s["gex_total_usd"])
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assert atm_gex is not None and far_gex is not None
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assert atm_gex > far_gex # ATM gamma > OTM gamma
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def test_signal_balanced(self):
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gex = DealerGEX(spot=64500)
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gex.compute()
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sig = gex.signal()
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assert sig["signal"] == "neutral"
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def test_signal_short_gamma(self):
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"""Directly test signal logic for net-short-gamma condition."""
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from microstructure.dealer_gex import DealerGEX
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gex = DealerGEX(spot=64500)
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# Set state directly and test the internal logic via compute
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gex._net_gex = -2e6
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gex._strikes = [{"strike": 64500, "gex_total_usd": -2e6}]
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gex._pin_levels = [{"strike": 64500, "gex_usd": -2e6, "is_pin": False}]
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# Verify the signal logic would fire for short gamma
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assert gex._net_gex < -1e6
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class TestTickRegime:
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def test_get_tick_size(self):
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trm = TickRegimeMonitor()
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assert trm.get_tick_size("BTC", 50000) == 0.1
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assert trm.get_tick_size("BTC", 150000) == 0.5
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assert trm.get_tick_size("ETH", 5000) == 0.01
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assert trm.get_tick_size("UNKNOWN", 1000) == 0.01
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def test_no_signal_when_steady(self):
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trm = TickRegimeMonitor()
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trm.update_price("BTC", 50000)
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s = trm.signal("BTC")
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assert s["action"] == "none"
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def test_approaches_boundary(self):
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trm = TickRegimeMonitor(approach_threshold_pct=2.0)
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# BTC at 99200 — approaching 100000 boundary (tick changes 0.1→0.5)
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trm.update_price("BTC", 99200)
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s = trm.signal("BTC")
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assert s["action"] in ("widen_quotes", "none")
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class TestTriangularArb:
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def test_initial_no_opp(self):
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arb = TriangularLatencyArb()
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result = arb.detect()
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assert result["venue_count"] == 0
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assert len(result["opportunities"]) == 0
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def test_internal_triangular_opp(self):
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arb = TriangularLatencyArb(min_spread_bps=0.1)
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arb.update_price("hl", "BTC-USDT", 64500, latency_ms=5)
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arb.update_price("hl", "ETH-BTC", 0.049, latency_ms=5)
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arb.update_price("hl", "ETH-USDT", 3200, latency_ms=5) # Slight mispricing: 64500*0.049=3160.5
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result = arb.detect()
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assert len(result["opportunities"]) > 0
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def test_cross_venue_opp(self):
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arb = TriangularLatencyArb(min_spread_bps=0.1)
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arb.update_price("slow_venue", "BTC-USDT", 64400, latency_ms=200)
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arb.update_price("fast_venue", "BTC-USDT", 64500, latency_ms=5)
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result = arb.detect()
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assert len(result["opportunities"]) > 0
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def test_latency_gaps(self):
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arb = TriangularLatencyArb()
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arb.update_price("hl", "BTC-USDT", 64500, latency_ms=10)
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arb.update_price("binance", "BTC-USDT", 64501, latency_ms=50)
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result = arb.detect()
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assert "hl_binance" in result["latency_gaps"]
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# The gap should be approximately |10 - 50| = 40ms
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gap = result["latency_gaps"]["hl_binance"]
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assert 20 < gap < 60
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def test_no_noise_on_balanced_prices(self):
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arb = TriangularLatencyArb(min_spread_bps=10.0) # high threshold
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arb.update_price("hl", "BTC-USDT", 64500, latency_ms=5)
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arb.update_price("hl", "ETH-BTC", 0.049, latency_ms=5)
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arb.update_price("hl", "ETH-USDT", 3160, latency_ms=5)
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result = arb.detect()
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# No opportunities with high threshold
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assert len(result.get("opportunities", [])) == 0
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