Build, test, and implement statistical arbitrage trading strategies with MATLAB
Statistical arbitrage, also referred to as stat arb, is a computationally intensive approach to algorithmically trading financial market assets such as equities and commodities. It involves the simultaneous buying and selling of security portfolios according to predefined or adaptive statistical models.
Statistical arbitrage techniques are modern variations of the classic cointegration-based pairs trading strategy. This strategy is based on short-term mean reversion principles coupled with hedging strategies that take care of overall market risk.
Hedge funds, mutual funds, and proprietary trading firms build, test, and implement trading strategies based on statistical arbitrage. An effective workflow entails:
Examples and How To
- Machine Learning for Algorithmic Trading (32:55) - Video
- Algorithmic Trading with MATLAB for Financial Applications (1:04:42) - Video
- A Real-Time Trading System in MATLAB (31:41) - Video
- Statistical Analysis of ETF Flows (29:16) - Video
- Algorithmic Trading: Winning Strategies and Their Rationale - Book
- News Sentiment Analysis Using MATLAB and RavenPack (12:01) - Video