# Markowitz Portfolio Construction at Seventy

**Authors:** Stephen Boyd, Kasper Johansson, Ronald Kahn, Philipp Schiele, Thomas Schmelzer  
**arXiv:** [2401.05080](https://arxiv.org/abs/2401.05080)  
**Date:** 2024-01-10  
**Summary page:** https://www.summarizepaper.com/en/paper/2401.05080v1/

## Key points

- Evolution of portfolio construction since Harry Markowitz's work over seventy years ago
- Markowitz introduced optimizing portfolios by balancing expected return with risk through standard deviation
- Method enhanced over time to incorporate practical constraints like transaction costs and leverage limits
- Despite criticism for sensitivity to inaccurate return forecasts, Markowitz's approach remains predominant in real-world applications
- Authors propose an extension of Markowitz's method to address criticisms and uncertainties in return statistics forecasting
- Extended approach considers broader range of practical effects and effectively manages uncertainty
- Extended method framed as a convex optimization problem for efficient and reliable solutions with high speed

## Summary

In their article "Markowitz Portfolio Construction at Seventy," authors Stephen Boyd, Kasper Johansson, Ronald Kahn, Philipp Schiele, and Thomas Schmelzer explore the evolution of portfolio construction since Harry Markowitz's groundbreaking work over seventy years ago. Markowitz introduced the concept of optimizing portfolios by balancing expected return with risk through the measurement of standard deviation. This method has been enhanced over time to incorporate practical constraints such as transaction costs and leverage limits. Despite criticism for its sensitivity to inaccurate return forecasts, Markowitz's approach remains the predominant quantitative method for constructing portfolios in real-world applications. To address these criticisms and uncertainties inherent in return statistics forecasting, the authors propose an extension of Markowitz's method. This extended approach considers a broader range of practical effects and effectively manages uncertainty. Like Markowitz's original formulation, this extended method is framed as a convex optimization problem. This characteristic ensures efficient and reliable solutions with high speed. By offering a more comprehensive framework for portfolio construction that takes into account practical considerations and uncertainty, the authors' extension builds upon Markowitz's foundational work and provides a valuable contribution to modern portfolio theory.