报告题目：Mutual Information for Optimal Asset Allocation
报告人： KC Chang教授 (George Mason University)
时间：2025年4月16日 下午2:30-4:30
地点：中国西部科技创新港经济金融研究院8004报告厅
报告人简介：
Dr. Chang is a dedicated researcher with expertise in data fusion, machine learning, and probabilistic inference for decision-making. He earned his M.S. and Ph.D. degrees in Electrical Engineering from the University of Connecticut. Since 1992, Dr. Chang has been a professor in the Systems Engineering and Operations Research department at George Mason University, where he also directs the Sensor Fusion Lab. Dr. Chang has published nearly 300 papers on topics such as multitarget tracking, sensor fusion, Bayesian network modeling, machine learning, and financial engineering. He has held editorial roles, including Editor on Tracking/Navigation Systems and Large-Scale Systems for the IEEE Transactions on Aerospace and Electronic Systems, as well as an editor for the IEEE Transactions on Systems, Man, and Cybernetics. Dr. Chang also chaired the Technical Program for Fusion 2009. His recognition as an IEEE Life Fellow reflects his significant contributions to the field of sensor data fusion and Bayesian inference.
摘要：
This presentation introduces an innovative dynamic portfolio allocation strategy grounded in mutual information principles derived from communication theory. The strategy leverages Kelly's formula, based on the channel capacity of a binary symmetric channel, to determine the optimal equity allocation in repeated trading scenarios. By focusing on equity index futures and options, the approach offers a robust framework for financial investment and risk management.
An analytical operating curve is presented, providing predictive insights into trading performance and facilitating a balanced evaluation of the risk-return trade-off. Simulated results validate the strategy's efficacy in optimizing equity growth while effectively managing risk, making it a promising tool for derivatives trading and portfolio management. This approach seamlessly integrates theoretical communication models with practical financial applications, presenting a unique perspective on advanced investment strategies.
经济与金融学院
2025年4月14日
