The Correlation Structure of Anomaly Strategies

55 Pages Posted: 19 Jul 2017 Last revised: 10 Aug 2018

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: August 9, 2018

Abstract

We construct 1,185 trading strategies based on previously documented anomalies, 19% of which yield mean returns with t-statistics above three. These significant anomalies can be grouped into 43 clusters based on their time-series correlations. The three largest clusters are momentum, profitability and issuance. Often a single cluster contains similar anomalies separately documented by many different prior studies. Anomaly clusters exhibit stability over time and across different market regimes. Benchmark asset pricing models leave the overall cluster structure largely intact but reduce correlations. Around two-thirds of cluster portfolios survive the stringent HXZ4 q-factor benchmark model with alpha t-statistics above three.

Keywords: return predictability; anomalies; correlation; asset pricing; benchmark models; cluster analysis; machine learning

JEL Classification: G12, G14, C38

Suggested Citation

Geertsema, Paul G. and Lu, Helen, The Correlation Structure of Anomaly Strategies (August 9, 2018). 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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