Portfolio selection based on predictive joint return distribution

Cuixia Jiang; Xiaoyi Ding; Qifa Xu; Xi Liu; Yezheng Liu

doi:10.1080/00036846.2018.1494812

Portfolio selection based on predictive joint return distribution

Cuixia Jiang, Xiaoyi Ding, Qifa Xu, Xi Liu, Yezheng Liu

Management Sciences

Research output: Contribution to journal › Article › peer-review

Abstract

A predictive joint return distribution can provide more useful information than moment-based risk measures in portfolio selection. This article develops a D-vine copula-CAViaR method to estimate and predict the joint probability distribution of multiple financial returns. Furthermore, we construct a portfolio model via the generalized Omega ratio inferred from the predicted joint return distribution. The superiority of our method is illustrated through an empirical application on five international stock market indices.

Original language	English
Pages (from-to)	196-206
Journal	Applied Economics
Volume	51
Issue number	2
Early online date	16 Jul 2018
DOIs	https://doi.org/10.1080/00036846.2018.1494812
Publication status	E-pub ahead of print - 16 Jul 2018

Keywords

Portfolio selection
CAViaR
vine copula
D-vine copula-CAViaR
generalized omega ratio

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10.1080/00036846.2018.1494812

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abstract = "A predictive joint return distribution can provide more useful information than moment-based risk measures in portfolio selection. This article develops a D-vine copula-CAViaR method to estimate and predict the joint probability distribution of multiple financial returns. Furthermore, we construct a portfolio model via the generalized Omega ratio inferred from the predicted joint return distribution. The superiority of our method is illustrated through an empirical application on five international stock market indices.",

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AU - Liu, Xi

AU - Liu, Yezheng

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Y1 - 2018/7/16

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AB - A predictive joint return distribution can provide more useful information than moment-based risk measures in portfolio selection. This article develops a D-vine copula-CAViaR method to estimate and predict the joint probability distribution of multiple financial returns. Furthermore, we construct a portfolio model via the generalized Omega ratio inferred from the predicted joint return distribution. The superiority of our method is illustrated through an empirical application on five international stock market indices.

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KW - vine copula

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KW - generalized omega ratio

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DO - 10.1080/00036846.2018.1494812

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JO - Applied Economics

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Portfolio selection based on predictive joint return distribution

Abstract

Keywords

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