Portfolio Optimization under Regulation T: A Comparative Study of the Markowitz Model and the Index Model

Abstract

The traditional risk management system of Modern portfolio theory faces operational barriers because investment regulations restrict both borrowing and selling short. The existing regulatory boundaries which limit leverage and short-selling operations create difficulties for standard optimization methods while making alternative portfolio models less stable and harder to implement. The research investigates how Regulation T gross-exposure limits affect the performance of Markowitz Model and Single-Index Model portfolios. The study evaluates operational performance and model stability between these two models by using U.S. equity data and market index returns and risk-free proxy to create efficient frontiers and global minimum variance portfolios and tangency portfolios. The Index Model produces efficient frontiers that remain stable while delivering higher risk-adjusted returns at reduced risk levels than the Markowitz Model. The Markowitz Model generates frontiers with increased noise and needs more computational resources which makes it more vulnerable to estimation errors. The Markowitz approach provides superior theoretical completeness but its practical use becomes less effective when leverage restrictions exist while the Index Model shows better compliance with regulatory needs. The research proves that spreadsheet optimization tools encounter operational barriers which need sophisticated computational systems to deliver enhanced performance and accuracy. The research proves that portfolio models need to fulfill both theoretical requirements and current regulatory standards to achieve their best performance. Investors and researchers obtain superior outcomes by using methods which merge mathematical accuracy with operational ease to link theoretical frameworks with actual portfolio construction.