P/E Modeling and Prediction of Firms Listed on the Tehran Stock Exchange; a New Approach to Harmony Search Algorithm and Neural Network Hybridization
Publish place: Iranian Journal of Management Studies، Vol: 11، Issue: 4
Publish Year: 1397
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JIJMS-11-4_006
تاریخ نمایه سازی: 6 شهریور 1402
Abstract:
Investors and other contributors to stock exchange need a variety of tools, measures, and information in order to make decisions. One of the most common tools and criteria of decision makers is price-to earnings per share ratio. As a result, investors are in pursuit of ways to have a better assessment and forecast of price and dividends and get the highest returns on their investment. Previous research shows that neural networks have better predictability than statistical models. Thus, Harmony Search algorithm and neural network have been used in this work, since achieving the best forecast is more likely. For this purpose, a sample consisting of ۸۷ companies has been selected from those listed at the Tehran Stock Exchange over a ۱۰-year period (۲۰۰۶-۲۰۱۵). The results show the high accuracy of the designed model that predicts the price-to-earnings ratio at the stock exchange by hybridizing the balanced search algorithm with neural network.
Keywords:
Harmony Search , Price to earnings ratio , Fundamental Analysis , Panel data econometrics , RBF neural network
Authors
مژگان صفا
Department of Accounting, Islamic Azad University, Kashan Branch, Kashan, Iran
حسین پناهیان
Department of Accounting, Islamic Azad University, Kashan Branch, Kashan, Iran
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