Impact of corporate performance on stock price predictions in the UAE markets: Neuro-fuzzy model

被引：11

作者：

Mohamed, Elfadil A. ^{[1
]}

Ahmed, Ibrahim Elsiddig ^{[2
]}

Mehdi, Riyadh ^{[1
]}

Hussain, Hanan ^{[1
]}

机构：

[1] Ajman Univ, Coll Engn, Ajman, U Arab Emirates

[2] Ajman Univ, Coll Business Adm, POB 346, Ajman, U Arab Emirates

来源：

INTELLIGENT SYSTEMS IN ACCOUNTING FINANCE & MANAGEMENT | 2021年 / 28卷 / 01期

关键词：

neuro-fuzzy model; performance measures predictive power; stock price predictions; UAE financial markets; EXCHANGE-RATE; TIME-SERIES; SYSTEM; CLASSIFICATION; REGRESSION; ALGORITHM; FEATURES; ANFIS;

D O I：

10.1002/isaf.1484

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

Predicting stock price remains one of the challenges for investors' investment strategies. This study helps with accurate prediction and the main factors affecting variations in stock prices. It applies an adaptive neuro-fuzzy model on 58 listed firms from both the Abu Dhabi Securities Exchange and the Dubai Financial Market for the period 2014-2018 to estimate the predictive power of corporate performance measures and their significance. After examining four performance predictors-return on asset (ROA), return on equity (ROE), earning per share (EPS), and profit margin (PM)-the study finds that ROE is the most significant predictor and ROA is the least. EPS is the most influential profitability measure and PM the least.

引用

页码：52 / 71

页数：20

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