Publications
Peer-reviewed work, surveys, and preprints from Tokalpha Labs on autonomous trading systems and AI infrastructure.
Featured Paper
The 10× Research Gap: A Comprehensive Survey of AI Trading Systems and Deployment Infrastructure
Our comprehensive analysis of 110+ papers reveals a critical imbalance in AI trading research: while alpha generation receives extensive attention, the infrastructure required for real-world deployment is largely neglected. We identify the 7-stage autonomous trading pipeline and demonstrate that zero existing systems address the complete workflow—creating a fundamental disconnect between academic research and production systems.
Key Findings
- 110+ papers analyzed (2018-2024)
- 0 systems addressing complete pipeline
- 10× more research on alpha vs. infrastructure
- Critical gaps in data, XAI, and execution
Working Papers & Preprints
Multi-Modal Alpha Generation: Combining Time Series, News, and Social Media for Superhuman Trading Signals
Exploring attention mechanisms and cross-modal fusion for extracting trading signals from diverse data sources at scale.
Explainable AI for Autonomous Trading: Building Trustworthy Decision Systems
Developing interpretability frameworks that make complex trading decisions transparent, auditable, and regulatory-compliant.
Time-Travel Safe Data Infrastructure: Eliminating Look-Ahead Bias in Financial Research
A comprehensive approach to data versioning and temporal consistency in backtesting and live trading systems.
Future Research Directions
We're actively developing research in several frontier areas of autonomous trading. If you're working on related topics, we'd love to collaborate.
Adaptive Market Regimes
Planned StudySelf-adjusting models that detect and adapt to changing market conditions
Execution Optimization
Planned StudyOptimizing portfolio execution to overcome traditional limitations using order book data
Causal Inference for Trading
Planned StudyMoving beyond correlation to understand causal market relationships
Robustness & Adversarial Testing
ConceptStress-testing trading systems against extreme scenarios and adversarial conditions
Collaborate on Research
Interested in collaborating, citing our work, or discussing research directions? We'd love to hear from you.
For partnerships & joint projects
For academic collaborations & co-authorship