 ramseshk
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3073415d33
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feat: funding arb strategy, queue-aware paper fills, WQI live integration
- strategies/funding_arb_strategy.py: full backtestable funding rate carry module
with entry/exit thresholds, position tracking, funding payment accounting,
basis stop-loss, max-hold timeout. Includes backtest_funding_arb() and
run_funding_discovery() for threshold optimization
- live/node_v2.py: replaced naive random fills with QueueAwareFillModel (sim/fills.py)
with queue-priority simulation; integrated WQI predictor and funding arb strategies;
per-coin WQI signal generation every 3 ticks; funding arb metrics in dashboard
- cli.py: added 'funding' command for funding rate distribution analysis and
threshold backtesting
- tests/test_funding_arb.py: 20 tests covering entry/exit logic, fee accounting,
signal generation, backtesting, and node integration
321 tests passing (20 new).
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2026-08-11 11:15:25 +08:00 |
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ramseshk
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e58c5951b7
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feat: Phase 5 — integration layer (analytics pipeline, production node v2, CLI) + 12 tests
live/integrator.py (AnalyticsPipeline):
Real-time pipeline: data → microstructure → signals.
Accumulates book snapshots + trades, computes OBI, VPIN, microprice,
spread, depth, trade imbalance, HFT regime, and emits composite
signal with confidence and breakdown. Per-coin isolation.
live/node_v2.py (ProductionNode):
Rebuilt production node integrating ALL Phase 1-4 modules:
- REST data fetching (order book, mark prices, funding rates)
- AnalyticsPipeline per coin for real-time microstructure signals
- Treasury for position/capital/PnL/breaker management
- ToxicityFilter integration via HlMakerPool makers
- HlMakerPool for per-coin A-S quoting
- CrossVenueMonitor, FundingBasisMonitor, LiquidationRiskOverlay
- Paper trading with probabilistic fill simulation
- Dashboard metrics JSON output (equity, treasury, analytics, maker)
- Periodic status logging
cli.py (unified CLI):
Subcommands integrating all modules:
collect — Run Hyperliquid data collector to Parquet
analyze — Run microstructure analytics on stored data
simulate — Run market-making simulator on stored data
run — Start production trading node (paper or live)
backtest — Run VectorBT backtest
12 integration tests (all pass):
- AnalyticsPipeline: empty, book, trade, VPIN, emit, regime, isolation
- ProductionNode: creation, tick cycle (3 ticks), metrics JSON output
- CLI: import verification
Total test suite: 184 tests, all passing.
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2026-08-07 14:54:47 +08:00 |
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