Thoughts on low latency trading if exchanges went full cloud
Low‑latency trading and high-frequency strategies would be fundamentally reshaped if major stock exchanges moved their matching engines into public clouds like AWS, raising hard questions about fairness, network design and technical feasibility. Commenters highlight how today’s colocation, hardware multicast and carefully equalized cabling enable “provable” low and predictable latency, something current cloud networking, virtualization and multicast offerings can’t reliably match at scale. Alongside these engineering concerns, people debate whether ultra‑fast trading benefits ordinary investors or mainly enables latency arbitrage, and float alternatives such as batched auctions, minimum order lifetimes or random delays to reduce the value of speed.
Technical barriers to “full cloud” exchanges
- Major obstacle: lack of true hardware multicast in hyperscale clouds. Existing “multicast” is software fan‑out over unicast, adding latency and jitter.
- Ultra‑low‑latency (ULL) setups depend on purpose‑built networks where 10–40Gbps+ multicast can saturate links with predictable behavior and minimal queuing.
- Cloud SDNs hide L2, ARP, and multicast by design, limiting the ability to build these specialized fabrics.
- Cloud FPGAs exist but typically as compute accelerators without direct network access; trading FPGAs need line‑rate NIC control and protocol “abuse.”
- Concerns about cloud reliability vs exchange uptime; cloud outages and noisy neighbors are seen as unacceptable for matching engines.
Fairness, latency, and colocation
- Exchanges use equal‑length fiber and carefully engineered networks to approximate “provable fairness” within a colo; colocation remains the dominant model.
- Moving matching engines into EC2‑style environments would make it harder to prove identical latency, and would invite games around instance placement, ping‑mapping, and potential DDoS on competitors’ hosts.
- Some argue clouds could create special regions or Outposts racks with symmetric connectivity, effectively recreating colo “inside” the cloud.
Role and impact of HFT / ULL trading
- Explanations for newcomers: speed lets firms react first to news, arbitrage across venues, and gain time priority in price‑time order books; profits are tiny per trade but huge in volume.
- Supporters say HFT competition tightens spreads, improves retail execution, and replaces the older, wider‑spread floor‑trader regime.
- Critics see HFT, especially latency arbitrage, as rent‑seeking that extracts value from slower participants and drives an arms race in hardware and proximity.
- Empirical studies (cited in-thread) claim latency arbitrage is frequent and costly, though definitions and interpretations are disputed.
Batch auctions and artificial latency
- Several propose discrete batch auctions (from milliseconds to seconds) or random/jittered delays to blunt latency advantages and front‑running.
- Others note many markets already use opening/closing auctions and volatility halt auctions; experiments with frequent auctions showed mixed impact.
- Concerns: batch systems can be gamed (e.g., outsized orders, pro‑rata matching), may increase spreads, complicate multi‑asset strategies, and shift from speed games to size/strategy games.
Economics and incentives of moving to cloud
- Exchanges earn substantial revenue from colocation, cross‑connects, and proprietary feeds; moving to cloud would hand margin to cloud providers and reduce control.
- Some see little operational or cost upside for mature exchanges that already have specialized staff and hardware.