Algorithmic Trading

Algorithmic trading (algo trading) uses computer programs to execute trading strategies based on predefined rules. The algorithm monitors market data, evaluates conditions against its rules, and places or manages trades without human intervention. It removes emotional bias, ensures consistent execution, and can monitor many instruments simultaneously.

How Algorithmic Trading Works

A typical algo trading system consists of three components: a data feed (market data API), a strategy engine (your trading logic), and an execution layer (broker API). The data feed provides real-time indicator values, the strategy engine evaluates entry and exit conditions, and the execution layer places orders.

Before deploying live, every algorithm should be backtested against historical data to validate its edge. Key metrics include win rate, profit factor, maximum drawdown, and Sharpe Ratio. A strategy that performs well in backtesting still needs forward testing (paper trading) before risking real capital.

Modern algo trading increasingly incorporates AI. Language models can interpret the natural language output from the /v1/summary endpoint, adding qualitative analysis to quantitative indicator signals. This hybrid approach combines systematic execution with adaptive market interpretation.

Access via API

The /v1/screener scans all symbols for indicator conditions in one call, perfect for algo signal generation.