The Correlation Structure of Anomaly Strategies

90 Pages Posted: 19 Jul 2017 Last revised: 12 May 2020

See all articles by Paul Geertsema

Paul Geertsema

University of Auckland - Department of Accounting and Finance

Helen Lu

University of Auckland - Department of Accounting and Finance

Date Written: May 12, 2020

Abstract

We use cluster analysis to consolidate a large number of mean-significant anomalies into cluster portfolios. More than a third of cluster portfolios remain significant under the Hou, Mo, Xue and Zhang (2020) five-factor model – the best performing among six benchmark models considered. A best-first search yields nine factors that subsume all cluster portfolios as well as all significant anomalies, demonstrating the feasibility of a parsimonious description of average realised returns. The search-generated model produces a maximum squared Sharpe ratio of 0.51, a considerable increase in pricing ability relative to current benchmark models.

Keywords: anomalies; correlation; cluster analysis; machine learning; asset pricing

JEL Classification: G12; C38

Suggested Citation

Geertsema, Paul G. and Lu, Helen, The Correlation Structure of Anomaly Strategies (May 12, 2020). Available at SSRN: https://ssrn.com/abstract=3002797 or http://dx.doi.org/10.2139/ssrn.3002797

Paul G. Geertsema (Contact Author)

University of Auckland - Department of Accounting and Finance ( email )

12 Grafton Rd
Private Bag 92019
Auckland, 1010
New Zealand

Helen Lu

University of Auckland - Department of Accounting and Finance ( email )

Private Bag 92019
Auckland 1001
New Zealand

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