Portfolio selection based on predictive joint return distribution

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.

KEYWORDS:

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

Acknowledgements

The authors gratefully acknowledge financial support from the National Natural Science Foundation of China (Grant numbers 71671056, 71490725), the National Social Science Foundation of China (Grant number 15BJY008) and the Humanity and Social Science Foundation of Ministry of Education of China (Grant number 14YJA790015).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors gratefully acknowledge financial support from the National Natural Science Foundation of China (Grant numbers 71671056, 71490725), the National Social Science Foundation of China (Grant number 15BJY008) and the Humanity and Social Science Foundation of Ministry of Education of China (Grant number 14YJA790015).