Who Uses Algorithmic Trading, How, and Where
Who uses it?
Investment banks and brokers now execute most of their orders via algorithms. Barclays estimates that more than 80% of US equity volume is handled by automated systems (HFT, smart routing, VWAP/TWAP).
Systematic hedge funds (Renaissance, DE Shaw, Two Sigma) manage several hundred billion dollars almost exclusively with quant strategies. Renaissance Technologies alone reportedly manages more than $50bn fully algorithmically (source: Bloomberg).
Which markets and volumes?
US equities: algorithmic trading represents over 70% of daily volume on NYSE/NASDAQ (source: NYSE), equating to tens of billions of dollars traded each day.
FX: roughly 60% of spot (on a market above $7tn/day, source: BIS 2022) goes through algos via ECNs such as EBS, Currenex, Refinitiv.
Crypto: market makers and quant desks (Jump, Wintermute) provide liquidity algorithmically. Aggregated daily spot volumes routinely exceed $30–50bn (source: CoinGecko).
How does it work in practice?
Smart order routing (SORS), basket execution (VWAP, TWAP), market making, and statistical arbitrage are dominant use cases. Algorithms encode entry/exit rules and risk controls, then operate at high cadence to minimise market impact.
Equities example: a desk executes a $50m basket using TWAP over two hours to smooth impact, connecting to multiple venues (dark/liquid) to optimise the average price (source: MSCI).
Why does it matter?
Speed, discipline, and lower transaction costs. On daily volumes of tens of billions, a few basis points saved in execution translate into millions in savings (source: Nasdaq SOR).
Human supervision remains essential: monitoring latency, impact, and errors, and triggering circuit-breakers when needed. Algorithms must comply with MiFID II/SEC/AMF requirements and log every action.
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