Develop a high-frequency trading platform with MATLAB
High-frequency trading 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 high-frequency trading 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 high-frequency trading, see MATLAB, Datafeed Toolbox™, and Trading Toolbox™.
Examples and How To
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Best Execution Strategy with Optimal Percentage of Volume (4:14) - Video
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Cointegration and Pairs Trading with Econometrics Toolbox (1:01:27) - Webinar
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Alpha Generation Using Thomson Reuters News Sentiment and MATLAB (59:53) - Webinar
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Algorithmic Trading - Solution
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High-Frequency Trading Tools and Resources - MATLAB Central
Software Reference
- Technical Indicators - Financial Toolbox Functions
- Downloading Intraday Tick Data from Bloomberg - Datafeed Toolbox Functions
- Cointegration Testing - Econometrics Toolbox Functions
- Neural Network Time Series Tool - Neural Network Toolbox Documentation
See also: algorithmic trading, statistical arbitrage, momentum trading, concentration risk, transaction cost analysis
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