Algorithmic Trading Strategies for Optimizing Trade Execution

Robert Kissell provides an overview of how MATLAB can be used by industry professional to improve trade quality and portfolio returns throughout all phases of the investment cycle. He provides practical examples and a case study using MATLAB’s recently released Transaction Cost Analysis (TCA) functions to help Portfolio Managers, Traders, and Analysts to develop strategies to reduce trading costs and better manage trading risk. His presentation will show how MATLAB is currently being used to calculate:

• Market Impact (by Trade Time, POV Rate, and Trade Schedule)
• Timing Risk for a trade schedule
• Stock Analysis (Size, Volatility, Time, Optimization)
• Construct Stock Cost Curves
• Liquidation Cost Analysis
• What-If and Sensitivity Analysis

About the Presenter

Robert is the president and founder of Kissell Research Group. He has over 20 years of professional experience specializing in economics, quantitative modeling, statistical analysis, and risk management. He advises and consults portfolio managers throughout the U.S. and Europe on appropriate risk management, trading analysis, and portfolio construction techniques. He is author of the leading industry books Optimal Trading Strategies, The Science of Algorithmic Trading & Portfolio Management, and Multi-Asset Risk Management. Robert has published numerous research papers on trading strategies, algorithmic trading, risk management, and best execution. His paper “Dynamic Pre-Trade Models: Beyond the Black Box” won the Institutional Investor Prestigious Paper of the Year award.

As of R2021a, Trading Toolbox has been merged into Datafeed Toolbox. As a part of this merge, a subset of the functionality is moving to File Exchange. Find more details in the release notes.