AccelerateAI Researchin Finance
Datasets, analysis, open tools, and curated literature
for quantitative ML researchers.
Everything you need to research faster
From raw tick data to published benchmarks — the full research pipeline in one place.
Model metrics
Track accuracy, Sharpe ratio, and F1 scores across every benchmark run. Compare MLP, LSTM, DeepLOB, and more side by side.
Historical data
Tick-level NASDAQ ITCH, S&P 500, and macro time-series datasets spanning multiple market regimes — ready to load in one line.
Live monitoring
Real-time regime detection, order flow signals, and market microstructure alerts streamed directly to your research environment.
Analysis & pipeline notebooks
Pre-built Jupyter-compatible notebooks for LOB benchmarking, regime detection, and factor analysis. Load any dataset, run any model, export your results — all without leaving the platform.
Browse notebooksEverything you need.
Nothing you don't.
Benchmark accuracyComing soon
Evaluate every model against standardized LOB and tick datasets with reproducible metrics.
Production-ready data
Clean, versioned datasets with train/test splits and multi-regime labels ready to use.
Regime detection
Multi-regime NASDAQ ITCH data covering bull, bear, and high-volatility market conditions.
Open-source tools
MIT-licensed utilities for data loading, feature engineering, and model evaluation.
Research notebooks
Jupyter-compatible notebooks with pre-built pipelines for every major LOB architecture.
Curated literature
140+ frontier papers on limit order books, deep learning for finance, and market microstructure.
Pretrained modelsComing soon
DeepLOB, CTABL, BIN-CTABL, and AxialLOB pretrained on multi-regime tick data.
Guided analysis
Step-by-step analysis sessions from data loading to model training, with structured notebooks and reproducible pipelines.
A growing platform for finance AI research
Researchers from leading universities and quantitative finance teams use FinanceLab to accelerate their work.