High-frequency trading (HFT) is a branch of algorithmic trading that focuses on generating profit using high execution speed. It’s used in areas such as arbitrage trading, signal-based trading, and scalping. In major exchanges, the trading volume generated from these trades—typically by proprietary traders, hedge fund managers, and market makers—is significant.

Developing HFT strategies requires intraday tick data and a solid analytical tool. MATLAB^® provides both. It supports popular techniques for efficiently developing, backtesting, and implementing these strategies:

• Hypothesis testing, machine learning, and pattern recognition
• Trading cost analysis and market impact modeling
• Analysis of financial time series to generate trading signals
• Monte Carlo simulation and model validation
• High-performance parallel computing using GPUs, clusters, grids, and clouds

For more on tools for HFT, see MATLAB and Datafeed Toolbox™.