Skip to main content

Latency

signal decay and execution latency - my hidden edge killer
2:15am on a monday. been staring at fill data for the past six hours. march has been rough. not catastrophically down, but underperforming where my models say i should be. january was decent (+2.1%). february was a loss (-1.3%). march was supposed to recover and it’s just… flat.
redis for market data - why i ditched postgres
moved all my real-time market data from postgres to redis about 8 weeks ago. latency dropped from ~15ms to sub-millisecond. should’ve done this way earlier. the postgres problem # when i first built my algo infrastructure i stored everything in postgres because that’s what i knew. tick data, order book snapshots, greeks, everything went into timescaledb (postgres extension for time-series).
redis timeseries - cutting latency from 45ms to 8ms
just finished a redis optimization project. latency went from 45ms to 8ms. here’s how. the problem # market data pipeline was bottlenecking at redis.
chicago colocation - 67ms to 12ms latency improvement, worth the cost
moved execution server to chicago colo march 2024. 3 months data in. latency dropped 67ms → 12ms average. why chicago # CME exchange location: chicago
upgrading chicago colocation to 10gbe - latency improvements
chicago colocation server needed upgrade. 1gbe connection = bottleneck. current setup # location: chicago datacenter (equinix CH1)