Bookmap Addon Collection

A curated collection of high-frequency market microstructure addons for Bookmap, implementing real-time Hawkes process estimation, Monte Carlo simulation, machine learning pipelines, and adaptive indicators.

Projects

Project	Description	Key Innovation
hawkes-toolkit	Multivariate Hawkes with learned decays + Numba MLE	Grid search decay learning, O(N) analytical gradient MLE
marked-hawkes	Marked Hawkes with non-linear interaction signal + ML regression	Conditional law kernel estimation, exponent-based signal fusion
microstructure	11-metric dashboard with hydrodynamic pressure model	ODE-based pressure accumulation, VPIN, sweep-to-fill
breach	Order book breach probability via Hawkes + Monte Carlo	MLE estimation + Ogata thinning simulation, branching process
ml-forecaster	Two-layer ML pipeline for price efficiency prediction	Ridge → PCA → RandomForest architecture
decay-state	Learned linear state transitions at configurable horizons	DecayStateModel replaces fitted Hawkes with supervised regression
flow-prediction	Intensity-based pressure + imbalance prediction	Volume-weighted ticks, intensity integration, conditional intensity
orderflow-ma	Adaptive EMA driven by order flow pressure	Dynamic alpha from volume percentile, centroid-based target

Architecture

All addons follow the Bookmap Python API pattern:

Bookmap → handle_subscribe_instrument → event handlers (depth/trades) → on_interval loop → indicators

Each project is a single-file Bookmap addon that processes real-time limit order book and trade data, fits statistical models, and plots derived indicators on Bookmap charts.

Dependencies

• bookmap — Bookmap Python API
• numpy, scipy, pandas — numerical computing
• scikit-learn — Ridge regression, RandomForest, PCA (ml-forecaster, decay-state, hawkes-toolkit)
• numba — JIT compilation (hawkes-toolkit)
• tick — Hawkes process library (marked-hawkes, flow-prediction)
• multiprocessing — parallel simulation (some projects)

Usage

1. Open Bookmap and enable the Python API
2. Load any .py file as an addon
3. Configure parameters in the GLOBAL SETTINGS section of each file
4. Subscribe to an instrument

License

MIT