Most trading systems fail long before strategy becomes the problem. Execution architecture, market microstructure, data quality, latency and infrastructure are often treated as afterthoughts. Durable trading systems emerge from robust infrastructure and research-driven design.
I built ToCan Analytics as a founder-led quant engineering practice focused on systematic trading infrastructure across crypto, equities, options, futures and prediction markets.
My work spans Python trading systems, market-data architecture, execution systems and research infrastructure.
Exploring the intersection of quantitative research, market structure and engineering systems to build resilient trading infrastructure for evolving markets.
Selective collaborations and long-term engagements focused on research quality, infrastructure robustness and production reliability.