Market-Making on Prediction Markets
Trading infrastructure on two exchanges, running unattended in normal operation: liquidity quoting, treasury, positions and risk, alerts and a manual stop. Custom low-latency infrastructure and a research loop, the whole stack on me.
Order submit 290-596 → 18-41 ms, March 2026. Numbers: my own measurements on my own infrastructure, 2025-2026. Methods are closed on purpose.
Execution layer
A series of trading bots: async Python orchestration with Rust on the hot path. Sub-50ms order submission, a 13x latency gain.
Market-making engine
Liquidity quoting for a rewards program, careful position reconciliation, its own treasury. Around the clock, with alerts and a manual stop.
Edge research
Market research on our own data: 3.9M trades across 6,249 wallets.
Low-latency backbone
A market WebSocket multiplexer: one upstream connection feeding every bot, reconnect without data loss.
Strategy calibration
Parameters are tuned and checked on history before rollout.














