 ramseshk
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fcfc136384
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feat: Phase 2 — microstructure analytics + 81 tests
New microstructure/ module with pure-function analytics:
microstructure/book.py:
microprice() — depth-weighted mid price
mid_price() — simple bid/ask midpoint
order_book_imbalance() — ranged [-1, 1] volume skew
depth_imbalance() — imbalance at fixed price distance
spread_stats() — spread, spread_bps, mid, bid, ask
depth_resiliency() — bid/ask volume within impact radius
queue_depletion_prob() — Poisson fill probability at level
batch_book_stats() — aggregate stats across snapshots
microstructure/trades.py:
classify_lee_ready() — Lee-Ready aggressor classification
classify_bulk_lee_ready() — batch classification with mids/bids/asks
compute_markouts() — forward mid-price change at configurable horizons
markout_summary() — mean/std/t-stat per side per horizon
trade_volume_profile() — size bucket distribution
trade_arrival_rate() — rolling trades/sec with burst detection
microstructure/toxicity.py:
compute_vpin() — volume-synchronized informed trading probability
compute_vpin_time_series() — rolling VPIN with alarm threshold
fill_toxicity() — adverse price movement post-trade
adverse_selection_ratio() — per-side adverse selection
liquidation_clustering() — cluster detection in liquidation events
microstructure/funding.py:
funding_regime() — classify regime (neutral/positive/negative/high)
funding_predictability() — AR(1) autocorrelation analysis
funding_carry_pnl() — cumulative carry PnL estimation
basis_spread() — perp premium over spot (bps)
basis_convergence_speed() — mean-reversion half-life via AR(1)
microstructure/signals.py:
composite_signal() — weighted OBI + trade + VPIN + funding signal
SignalPipeline — stateful pipeline accumulating book/trade updates
detect_hft_regime() — regime classifier for HFT strategy selection
Bug fixes in Phase 1:
- data/latency.py: proper linear-interpolation percentiles
- data/normalizer.py: UTC timezone for naive datetimes
- data/normalizer.py: detect_sequence_gap returns gap-1 (missing count)
- microstructure/toxicity.py: consistent vpin_value key in compute_vpin
81 tests across 4 test files (store, normalizer, latency, microstructure)
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2026-08-07 14:34:18 +08:00 |
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ramseshk
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a7f811eb81
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feat: Phase 1 — real-time & historical data system
New data/ module with:
- data/store.py: Parquet-based raw message storage with background writer
thread. Messages partitioned by channel/coin/date. Thread-safe queue.
Supports pyarrow Parquet with zstd compression. Includes read_range()
helper for replay.
- data/collectors/hyperliquid.py: HL WebSocket + REST collector
- WebSocket: l2Book (full book reconstruction), trades, allMids (mark prices)
- REST pollers: funding rates, predicted funding, open interest, liquidations
- Per-coin OrderBook class with snapshot/update reconstruction
- Sequence gap detection with per-coin re-snapshot on gap
- Latency tracking (exchange transport, signal, order, roundtrip)
- Periodic stats reporter (book stats + latency summary every 60s)
- CLI entrypoint: python -m data.collectors.hyperliquid --coins BTC ETH
- data/normalizer.py: Timestamp normalization (ms, s, ISO strings from
HL/Binance/Bybit/OKX/Coinbase/Deribit) + SequenceTracker with gap detection
- data/latency.py: Rolling-window latency metrics (p50/p90/p95/p99) for
transport, signal computation, order submission, and roundtrip
- Added pyarrow + aiohttp to requirements.txt
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2026-08-07 14:28:21 +08:00 |
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