A semiparametric graphical modelling approach for large-scale equity selection

Han Liu, John Mulvey and Tianqi Zhao

Quantitative Finance, 2016, vol. 16, issue 7, 1053-1067

Abstract: We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1080/14697688.2015.1101149

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