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Multi-period investment decision problem based on time consistent generalized convex risk measure and extremum scenarios

Li Yang (Department of Computing Science, School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China and School of Economics & Management, Guangxi Normal University, Guilin, China)
Zhiping Chen (Department of Computing Science, School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China)
Qianhui Hu (Department of Computing Science, School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China)

China Finance Review International

ISSN: 2044-1398

Article publication date: 11 November 2014

Abstract

Purpose

To help investors find an investment policy with strong competitiveness, the purpose of this paper is to construct a multi-period investment decision model with practicality and superior performance.

Design/methodology/approach

The paper uses a suitable multi-period risk measure to construct a multi-period portfolio selection model, where target returns at intermediate periods and market frictions are taken into account simultaneously. An efficient scenario tree generation approach is proposed in order to transform the complex multi-period portfolio selection problem into a tractable one.

Findings

Numerical results show the new scenario tree generation algorithms are stable and can further reduce the tree size. With the scenario tree generated by the new scenario tree generation approach, the optimal investment strategy obtained under the multi-period investment decision model has more superior performance and robustness than the corresponding optimal investment strategy obtained under the single period investment model or the multi-period investment model only paying attention to the terminal cash flow.

Research limitations/implications

The new risk measure and multi-period investment decision models can stimulate readers to find even better models and to efficiently solve realistic multi-period portfolio selection problems.

Practical implications

The empirical results show the superior performance and robustness of optimal investment strategy obtained with the new models. What's more important, the empirical analyses tell readers how different market frictions affect the performance of optimal portfolios, which can guide them to efficiently solve real multi-period investment decision problems in practice.

Originality/value

The paper first derives the concrete structure of the time consistent generalized convex multi-period risk measure, then constructs a multi-period portfolio selection model based on the new multi-period risk measure, and proposes a new extremum scenario tree generation algorithm. The authors construct a realistic multi-period investment decision model. Furthermore, using the proposed scenario tree generation algorithm, the authors transform the established stochastic investment decision model into a deterministic optimization problem, which can provide optimal investment decisions with robustness and superior performance.

Keywords

Acknowledgements

The authors are grateful to two anonymous referees and the managing editor for their valuable comments that have been of great help in improving the quality of the paper. The authors acknowledge financial supports from the National Natural Science Foundation of China (Grant Nos. 70971109, 71201121, 71371152 and 11326204); Research Project of the Humanities and Social Sciences of Guangxi Education Department (Grant No. LX2014046); the Scientific Research Foundation of Guangxi Normal University for Doctor; the Fundamental Research Funds for the Central Universities (Grant No. 08143032).

Citation

Yang, L., Chen, Z. and Hu, Q. (2014), "Multi-period investment decision problem based on time consistent generalized convex risk measure and extremum scenarios", China Finance Review International, Vol. 4 No. 4, pp. 360-384. https://doi.org/10.1108/CFRI-12-2013-0136

Publisher

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Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited