Journal Article

An application of a cardinality-constrained multiple benchmark tracking error model on a plant enterprise selection problem

Qiuzhuo Ma, Krishna P Paudel, Liting Gu and Xiaowei Wen

in European Review of Agricultural Economics

Volume 45, issue 5 Published in print December 2018 | ISSN: 0165-1587
Published online March 2018 | e-ISSN: 1464-3618 | DOI: https://dx.doi.org/10.1093/erae/jby004
An application of a cardinality-constrained multiple benchmark tracking error model on a plant enterprise selection problem

More Like This

Show all results sharing this subject:

  • Mathematical Methods; Programming Methods; Mathematical and Simulation Modelling

GO

Show Summary Details

Preview

Abstract

Yield and return of plants grown in a region are generally closely related. Agricultural scientists are less likely to recommend a single-plant enterprise for a region because of risk and return concerns. From a risk/return perspective, a plant enterprise selection problem can be considered as a portfolio optimisation problem. We use a multiple benchmark tracking error (MBTE) model to select an optimal plant enterprise combination under two goals. A cardinality constraint (CC) is used to efficiently balance multiple objectives and limit over-diversification in a region. We use Chinese national and province level datasets from multiple plant enterprises over 25 years to identify the best plant enterprise combination with two objectives under consideration: return maximisation and risk minimisation. A simulated case using discrete programming is applied in order to analyse a farmer’s choice of specific plant enterprise and the transaction cost during rotation. In the continuous problem, the MBTE model is found to be efficient in choosing plant enterprises with high returns and low risk. The inclusion of a CC in the MBTE model efficiently reduces the plant enterprise number and volatility while creating smaller tracking errors than the MBTE model alone in an out-of-sample test. In the discrete problem, a CC can be used to search for the optimal number of plant enterprises to obtain high returns and low risk. The study and methods used can be helpful in choosing an optimal enterprise combination with multiple objectives when there are over-diversification concerns.

Keywords: cardinality constraint; multiple benchmarks tracking error; plant enterprise selection

Journal Article.  15781 words.  Illustrated.

Subjects: Mathematical Methods; Programming Methods; Mathematical and Simulation Modelling

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content. subscribe or login to access all content.