Quant Investing in Cluster Portfolios

Journal of Investment Strategies (Risk.net) https://www.risk.net/journal-of-investment-strategies, 2020

Posted: 23 Feb 2021

See all articles by Ali Akansu

Ali Akansu

New Jersey Institute of Technology

Marco Avellaneda

New York University (NYU) - Courant Institute of Mathematical Sciences; Finance Concepts LLC

Anqi Xiong

New Jersey Institute of Technology

Date Written: June 30, 2020

Abstract

This paper discusses portfolio construction for investing in N given assets, e.g. constituents of the Dow Jones Industrial Average (DJIA) or large cap stocks, which is based on partitioning the investment universe into clusters. The clusters are determined from the trailing correlation matrix via an information theoretic algorithm that uses thresholding of high-correlation pairs. We calculate the Principal Eigenvector of each cluster from its correlation matrix and the corresponding eigenportfolio. The cluster portfolios are combined into a single N-asset portfolio based on a weighting scheme for the clusters. Various tests conducted on components of DIA and a thirty-stock basket of large-cap stocks indicate that the new portfolios are superior to the DIA and other Mean-Variance portfolios in terms of risk-adjusted returns from 2009 to 2019. We also tested the cluster portfolios for the larger basket of 373 S&P500 components from 2001 to 2019. The test results give convincing evidence that cluster-based portfolio can outperform passive investing.

KEY MESSAGES
1) A correlation-based set partitioning algorithm that divides the investment universe dynamically into clusters of assets proposed.

2) The principal eigenvector of each cluster from its correlation matrix is calculated and the corresponding eigenportfolio. The cluster portfolios of varying sizes combined into a single N-asset portfolio based on a weighting scheme for the clusters.

3) The proposed portfolio outperforms hierarchical risk parity (HRP) portfolio, eigenportfolio (EP), and a few other portfolio constructions and relevant ETFs based on several tests performed with market data.

4) The performance comparisons give convincing evidence that cluster-based long-only investment portfolio can outperform passive investing.

Keywords: Set partitioning, eigenportfolio, super eigenportfolio, long-only portfolio

JEL Classification: G11

Suggested Citation

Akansu, Ali and Avellaneda, Marco and Xiong, Anqi, Quant Investing in Cluster Portfolios (June 30, 2020). Journal of Investment Strategies (Risk.net) https://www.risk.net/journal-of-investment-strategies, 2020, Available at SSRN: https://ssrn.com/abstract=3756567

Ali Akansu (Contact Author)

New Jersey Institute of Technology ( email )

University Heights
Newark, NJ 07102
United States

Marco Avellaneda

New York University (NYU) - Courant Institute of Mathematical Sciences ( email )

251 Mercer Street
New York, NY 10012
United States
212-998-3129 (Phone)
212-995-4121 (Fax)

Finance Concepts LLC ( email )

590 Madison Avenue
21st Floor
New York, NY 10022
United States

HOME PAGE: http://www.finance-concepts.com

Anqi Xiong

New Jersey Institute of Technology ( email )

University Heights
Newark, NJ 07102
United States

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