Graduation Year
2021
Date of Submission
5-2021
Document Type
Open Access Senior Thesis
Award
Robert Day School Prize for Best Senior Thesis in Economics and Finance
Degree Name
Bachelor of Arts
Department
Economics
Reader 1
Benjamin Gillen
Terms of Use & License Information
Rights Information
© 2021 Coleman A Cornell
Abstract
The limited span of useful data, coupled with increasingly expansive asset universes, cripples the traditional mean-variance problem. When optimizing in these environments, the pronounced effect of estimation error yields extremely unstable portfolios when evaluated out-of-sample. As a proposed solution to the "curse of dimensionality," Gillen (2016) presents subset optimization as a technique to reduce the impact of estimation error. Instead of optimizing jointly over the entire asset universe, subset optimization na\"ively aggregates over many "subset portfolios" that each optimize over a much smaller random sample of assets. Given the inefficiencies when using naive aggregation, converged subset optimization is presented as an extension to subset optimization. Simulation and backtest experiments illustrate the potential for outperformance when implementing this method of convergence.
Recommended Citation
Cornell, Coleman, "Converged Subset Portfolios: An Extension to Subset Optimization" (2021). CMC Senior Theses. 2726.
https://scholarship.claremont.edu/cmc_theses/2726
