EARNINGS PER SHARE FORECAST: THE COMBINATION OF ARTIFICIAL NEURAL NETWORKS AND PARTICLE SWARM OPTIMIZATION ALGORITHM

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FOROUGI DARIUSH; FOROUGHNEJAD HEIDAR; MIRZAEI MANOCHEHR

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Journal: INVESTMENT KNOWLEDGE Year:2013 | Volume:2 | Issue:6 Page(s): 63-82

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Title

EARNINGS PER SHARE FORECAST: THE COMBINATION OF ARTIFICIAL NEURAL NETWORKS AND PARTICLE SWARM OPTIMIZATION ALGORITHM

Author(s)

FOROUGI DARIUSH | FOROUGHNEJAD HEIDAR | MIRZAEI MANOCHEHR | Issue Writer Certificate

Keywords

EARNINGS PER SHAREQ2

PARTICLE SWARM OPTIMIZATION ALGORITHMQ2

FUNDAMENTAL ACCOUNTING VARIABLESQ2

ARTIFICIAL NEURAL NETWORKSQ1

Abstract

Expectations about earning have significant effects on managers and investors’ decisions. Today, one of the measures that are taken in to consideration as an indicator of companies ‘profitability is the concept of earning per share. Also earning per share has major effects on stock price of companies. Hence, fore casting earning per share is of great importance for both investors and managers. The aim of this study is to model earning per share forecast of listed companies in Tehran Stock Exchange (TSE) by using the combination of ARTIFICIAL NEURAL NETWORKS and PARTICLE SWARM OPTIMIZATION ALGORITHM based on univariate and multivariate models. To do this, the data of114 companies among the existing listed ones in Tehran Stock Exchange was usedduring1380-1389(2001-2010).The results showed that univariate model with 78.5% accuracy and multivariate models with 91.7% accuracy, forecast earning per share.

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APA: Copy

FOROUGI, DARIUSH, FOROUGHNEJAD, HEIDAR, & MIRZAEI, MANOCHEHR. (2013). EARNINGS PER SHARE FORECAST: THE COMBINATION OF ARTIFICIAL NEURAL NETWORKS AND PARTICLE SWARM OPTIMIZATION ALGORITHM. INVESTMENT KNOWLEDGE, 2(6), 63-82. SID. https://sid.ir/paper/188121/en

Vancouver: Copy

FOROUGI DARIUSH, FOROUGHNEJAD HEIDAR, MIRZAEI MANOCHEHR. EARNINGS PER SHARE FORECAST: THE COMBINATION OF ARTIFICIAL NEURAL NETWORKS AND PARTICLE SWARM OPTIMIZATION ALGORITHM. INVESTMENT KNOWLEDGE[Internet]. 2013;2(6):63-82. Available from: https://sid.ir/paper/188121/en

IEEE: Copy

DARIUSH FOROUGI, HEIDAR FOROUGHNEJAD, and MANOCHEHR MIRZAEI, “EARNINGS PER SHARE FORECAST: THE COMBINATION OF ARTIFICIAL NEURAL NETWORKS AND PARTICLE SWARM OPTIMIZATION ALGORITHM,” INVESTMENT KNOWLEDGE, vol. 2, no. 6, pp. 63–82, 2013, [Online]. Available: https://sid.ir/paper/188121/en

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