DERIBIT LOB MODEL
Real-time limit order book analysis and paper-trading system for Deribit. Streams live order-book snapshots and trades via WebSocket, runs four competing microstructure strategies side-by-side, and displays a live terminal dashboard comparing their performance.
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THE IDEA
Most alpha in liquid crypto markets lives in the microstructure — queue imbalances, order flow, and price-impact dynamics that play out over milliseconds to seconds. This project streams live Deribit order-book snapshots via WebSocket, runs three academic microstructure models in parallel, and wraps them in a composite signal with explicit confidence gating and asymmetric risk management.
The result is a live paper-trading engine that logs every decision — signal values, confidence scores, skip/entry/exit rationale — to a real-time terminal dashboard powered by Rich.
STRATEGIES — MICROSTRUCTURE
Three standalone microstructure strategies run independently, each rooted in a canonical academic model:
| Strategy | Paper | Signal |
|---|---|---|
| Cont-de Larrard | SIAM J. Financial Math, 2013 | LOB queue imbalance at best bid/ask |
| Kyle | Econometrica, 1985 | Price-impact coefficient λ from net order flow |
| OFI | J. Financial Econometrics, 2014 | Event-by-event order flow imbalance z-score |
COMPOSITE ALPHA
The fourth strategy fuses all three microstructure signals plus an Ornstein-Uhlenbeck mean-reversion anchor into a single composite score. Every entry is gated through a multi-layer confidence filter:
- Confidence check: requires 3 of 4 sub-signals to agree, a favorable vol regime, and no recent price jumps.
- Asymmetric SL/TP: stop-loss = 5× ATR, take-profit = 20× ATR — a 1:4 risk-reward ratio.
- 30s cooldown: prevents overtrading; quality over quantity.
The model logs its full reasoning to a live thought-process panel on the dashboard, making every skip and entry fully auditable in real time.
DASHBOARD LAYOUT
The terminal dashboard refreshes twice per second and organises information into five panels:
- Strategy table: signal, position, trade count, realized / unrealized / total PnL for all four strategies.
- PnL sparklines: rolling history per strategy, rendered as ASCII bar charts.
- Signal breakdown: horizontal bars for each Composite Alpha sub-signal plus a confidence meter.
- Thought process: scrolling log of Composite Alpha decisions with timestamps.
- Recent trades: last 10 fills across all strategies with side, price, size, position, and PnL delta.
ADDITIONAL MODELS
Three more models are included but inactive by default — they can be enabled in run_model.py:
- Jump Diffusion: Merton (1976) — drift plus Poisson jump estimation.
- OU Mean Reversion: Ornstein-Uhlenbeck mean-reverting process.
- Heston Vol: Heston (1993) — momentum scaled by stochastic vol regime.