Understanding algorithmic trading.
A reference series on what algorithmic trading is, how the systems behind it work, the main strategy families, the advantages and risks, and how strategies are tested before they trade.
What is algorithmic trading?
A plain-language introduction to algorithmic trading: what it is, the difference between execution and decision algorithms, who uses it and how it relates to high-frequency trading.
ReadHow an algorithmic trading system works
The main components of an algorithmic trading system, from market data and signal generation to pre-trade risk checks, order execution, reconciliation and monitoring.
ReadCommon algorithmic trading strategies
An overview of the main families of algorithmic trading strategy: trend following, mean reversion, statistical arbitrage, market making, cross-venue arbitrage, basis trading and execution algorithms.
ReadAdvantages and risks of algorithmic trading
The practical advantages of algorithmic trading, including speed, discipline, cost control and auditability, set against model, operational, liquidity, venue and regulatory risks.
ReadBacktesting and validation
How trading strategies are tested on historical data, the biases that make backtests misleading, and the validation practices that separate real effects from noise.
ReadAlgorithmic trading in digital-asset markets
How digital-asset market structure shapes algorithmic trading: continuous 24/7 trading, fragmented venues, exchange APIs, fee tiers, on-chain settlement, custody and venue risk.
ReadGlossary of algorithmic trading terms
Definitions of common algorithmic trading and market-structure terms, from adverse selection and basis to VWAP, slippage and walk-forward testing.
ReadExchanges, venues and technology partners.
We work with trading venues, liquidity providers and infrastructure partners. For onboarding, partnership or verification enquiries, contact us directly.