Optimal Portfolio under Non-Extensive Statistical Mechanics and Value-at-Risk Constraints

• Authors: Pan Zhao , Jixia Wang , Yu Song
• Languages of publication: EN

Abstracts

EN

In this study, we consider the optimal portfolio selection problem with a value-at-risk constraint in the non-extensive statistical mechanics framework. We propose a portfolio selection model, which is suitable not only for normal return distributions, but also for non-normal return distributions. Using Chinese stock data, under the normal and q-Gaussian return distributions, we provide empirical results. The results indicate that portfolio selections under the q-Gaussian return distributions are considerably different from those under the normal return distributions. Moreover, by using the q-Gaussian distribution, the underestimated portfolio risk can be effectively avoided.

Keywords

EN

Tsallis entropy; q-Gaussian distribution; value-at-risk; optimal portfolio

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2018
• Volume: 133
• Issue: 5
• Pages: 1170-1173

Dates

published

2018-05

received

2017-06-27

Contributors

author

Pan Zhao

• College of Finance and Mathematics, West Anhui University, Lu'an, Anhui, China
• Financial Risk Intelligent Control and Prevention Institute of West Anhui University, Lu'an, Anhui, China

author

Jixia Wang

• School of Mathematics and Information Sciences, Henan Normal University, Xinxiang, Henan, China

author

Yu Song

• School of Economics and Management, Nanjing University of Science and Technology, Nanjing, Jiangsu, China

Identifiers

DOI

10.12693/APhysPolA.133.1170