Equity trading is the purchase and sale of shares in companies that are publicly listed on stock exchanges. The direction and volume of equity trading are influenced by factors such as the overall state of the economy, capital flows across asset classes, idiosyncratic news concerning specific companies, and changes in market expectations among investors and speculators.

Financial institutions such as banks, mutual funds, or hedge funds implement equity trading strategies to optimize their asset portfolios, take advantage of short-term mispricing and arbitrage opportunities, or gain exposure to multiple risk factors such as momentum, growth vs. value, or small cap vs. large cap.

You can build and test equity trading strategies with data gathered from data feeds and databases. This approach enables you to model behaviors systematically with a process that lets you:

• Optimize custom trading strategies
• Analyze news and sentiment data to generate alpha
• Apply machine learning techniques to enhance strategies
• Create dynamic portfolio management and asset allocation techniques
• Manage an automated equity trading order workflow

For more information, see MATLAB^®, Financial Toolbox™, Statistics and Machine Learning Toolbox™, and Econometrics Toolbox™.