Citation

Arsad, R. and Isa, Z. and Ismail, N. and Ab Razak, Ruzanna (2020) Evaluating Technical Efficiency of Stock Performance using Copula-Based Stochastic Frontier Analysis Approach. Journal of Physics: Conference Series, 1496. pp. 1-14. ISSN 1742-6588

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Abstract

This study estimates the technical efficiency for 14 selected Malaysian trading and services companies for 2017 and 2018using the Cobb-Douglas with the Stochastic Frontier production model. In standard stochastic frontier analysis (SSFA), the two-sided error, statistical noise, and one-sided error, inefficiency term are assumed to be independent. The assumption for statistical noise is normally distributed and the inefficiency term is half-normal distributed. In this paper, the copula model is applied to capture the joint distribution of these two error components. The copula model is an alternative method that is able to account for the joint multivariate distribution. Copula functions can be used to capture rank correlation and tail dependence between two error components, thus making the SFA more flexible. Seven copula models from the Archimedean copula family are considered in this study including the copulas with the trigonometric and hyperbolic generator. This study further compares the technical efficiency yielded by copulas with standard SFA, DEA-CCR and DEA-BCC models. The results raise the question of the reliability of SFA based on the standard model. Since the dependence error between statistical noise and inefficiency error cannot be ignored, the copula-based in SFA models can be considered as an alternative suitable tool for measuring efficiency performance.

Item Type:	Article
Uncontrolled Keywords:	Copulas (Mathematical statistics), Distribution (Probability theory)
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions:	Faculty of Management (FOM)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	13 Dec 2020 12:50
Last Modified:	13 Dec 2020 12:50
URII:	http://shdl.mmu.edu.my/id/eprint/7828

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