- add Databento options adapter (TS) with Python sidecar and env wiring - add to stream historical trades and resolve instrument_id -> raw_symbol via symbology - include Databento + typing_extensions in ingest-options Python requirements - expose Databento env settings in ingest-options index (dataset/schema/start/end/stype/limit/price scale/python bin) - update README with Databento replay usage and env docs - speed up UI replay polling/drain, add per-card replay time display - stop replay at end and prevent fallback to synthetic by pinning replay to initial trace source
143 lines
5.7 KiB
Markdown
143 lines
5.7 KiB
Markdown
# Real-Time Options Flow & Off-Exchange Analysis
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This repository contains a real-time market-flow analysis platform focused on **options flow**, **off-exchange equity trades**, and **inferred institutional behavior**, built for low-latency, explainable analysis rather than black-box signals.
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The system ingests real-time options trades/quotes and equity prints, clusters raw activity into higher-level flow events (sweeps, spreads, rolls, ladders), applies rule-first classifiers, and visualizes the results through a high-performance, TradingView-smooth interface with full replay and backtesting support.
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## CURRENT STATE (Plan Progress)
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Plan progress (rough): [####------]
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Done now (in repo):
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- Bun monorepo + infra docker compose (ClickHouse, Redis, NATS JetStream)
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- Shared event schemas + logging + config helpers
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- Synthetic options/equity prints published to NATS and persisted to ClickHouse
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- Deterministic option FlowPacket clustering (time window) + persistence
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- API: REST for prints/flow packets, WS for live options/equities/flow, replay endpoints
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- UI: live tapes for options/equities/flow + replay toggle + pause controls
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In progress / blocked:
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- Live data adapters (requires licensed data source)
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- Rolling stats and advanced clustering
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Not started:
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- Classifiers + alert scoring
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- Dark pool inference
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- Candle service and chart overlays
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- Auth / secure deployment
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## Core Principles
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- **Explainability first** — every alert and signal is backed by observable data and explicit logic.
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- **Event-sourced architecture** — all raw and derived events are persisted and replayable.
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- **Market microstructure correctness** — conservative handling of aggressor inference, OI, and off-exchange prints.
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- **Low-latency, tangible UX** — smooth real-time interaction that feels like an instrument panel, not a spreadsheet.
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## Current Capabilities
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- Synthetic options/equity prints with deterministic sequencing
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- Ingest adapter seam (env-selected; options default `alpaca`, equities default `synthetic`)
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- Raw event persistence in ClickHouse + streaming via NATS JetStream
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- Deterministic option FlowPacket clustering (time-window)
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- API gateway with REST, WS, and replay endpoints
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- UI tapes for options/equities/flow packets with live/replay toggle and pause controls
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- Alpaca options adapter (dev-only) with bounded contract selection
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- Databento historical replay adapter (options, Python sidecar)
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## Planned Capabilities (from PLAN.md)
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- Real-time licensed market data ingestors (options + equities)
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- Rule-first classifiers and alert scoring
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- Dark pool inference and evidence linking
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- Candle aggregation + chart overlays
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- Replay/backtesting metrics and calibration
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## Tech Stack
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- **Runtime & tooling:** Bun
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- **Language:** TypeScript
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- **Frontend:** Next.js + React
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- **Realtime:** WebSockets
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- **Event streaming:** NATS JetStream or Redpanda
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- **Storage:** ClickHouse, Redis
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- **Charting:** TradingView Lightweight Charts + custom canvas/WebGL overlays
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## Repository Structure
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apps/
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web/
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services/
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ingest-options/
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ingest-equities/
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compute/
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api/
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packages/
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types/
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ui/
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chart/
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## Build and Run
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Install dependencies:
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- `bun install`
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Start infra:
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- `docker compose up -d`
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Start everything (infra + services + web):
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- `bun run dev`
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Run just the web app (auto-picks a free port in 3001-3005):
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- `bun --cwd apps/web run dev`
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Run just the API:
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- `bun --cwd services/api run dev`
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IBKR adapter (options, via Python `ib_insync`):
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- Install Python deps: `python3 -m pip install -r services/ingest-options/py/requirements.txt`
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- Set `INGEST_ADAPTER=ibkr` and configure:
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- `IBKR_HOST`, `IBKR_PORT`, `IBKR_CLIENT_ID`
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- `IBKR_SYMBOL`, `IBKR_EXPIRY` (YYYYMMDD), `IBKR_STRIKE`, `IBKR_RIGHT`
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- Optional: `IBKR_EXCHANGE` (default `SMART`), `IBKR_CURRENCY` (default `USD`), `IBKR_PYTHON_BIN`
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Alpaca adapter (options, dev-only bridge):
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- Set `INGEST_ADAPTER=alpaca` and configure:
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- `ALPACA_KEY_ID`, `ALPACA_SECRET_KEY`
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- `ALPACA_UNDERLYINGS` (comma-separated, default `SPY`)
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- Optional: `ALPACA_FEED` (`indicative` default, `opra` with subscription)
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- Optional: `ALPACA_MAX_QUOTES` (default `200`), `ALPACA_REST_URL`, `ALPACA_WS_BASE_URL`
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- Optional selection tuning: `ALPACA_STRIKES_PER_SIDE` (default `8`), `ALPACA_MAX_DTE_DAYS` (default `30`),
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`ALPACA_MONEYNESS_PCT` (default `0.06`), `ALPACA_MONEYNESS_FALLBACK_PCT` (default `0.10`)
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Alpaca selection policy (dev-only, deterministic):
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- Pick nearest weekly and nearest monthly expiries within 30 DTE (fallback to earliest expiries if missing)
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- For each expiry, select 8 strikes per side closest to ATM within ±6% (fallback to ±10% if needed)
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- Subscriptions are built once at startup to keep the stream bounded and repeatable
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Databento historical replay adapter (options, via Python `databento`):
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- Install Python deps: `python3 -m pip install -r services/ingest-options/py/requirements.txt`
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- Set `INGEST_ADAPTER=databento` and configure:
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- `DATABENTO_API_KEY`, `DATABENTO_START` (ISO date/time)
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- Optional: `DATABENTO_END`, `DATABENTO_DATASET` (default `OPRA.PILLAR`), `DATABENTO_SCHEMA` (default `trades`)
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- Optional: `DATABENTO_SYMBOLS` (`ALL` or comma list), `DATABENTO_STYPE_IN`/`DATABENTO_STYPE_OUT` (default `raw_symbol`)
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- Optional: `DATABENTO_LIMIT` (record cap), `DATABENTO_PRICE_SCALE` (divide raw price), `DATABENTO_PYTHON_BIN`
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- This adapter replays historical data only; live capture will be added later.
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Run tests:
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- `bun test`
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## Status
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Active build for personal, non-delayed analytical use. Multi-user access and redistribution are intentionally out of scope.
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## Non-Goals
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- No black-box AI predictions
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- No profit guarantees
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- No real-time data redistribution
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- No guessing at intent without evidence
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## License / Usage
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For research and personal analytical use.
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Market data usage is subject to the terms of the data providers.
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