A Validation Test Naive Bayesian Classification Algorithm and Probit Regression as Prediction Models for Managerial Overconfidence in Iran's Capital Market
Publish Year: 1398
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJFMA-4-13_003
تاریخ نمایه سازی: 13 آذر 1400
Abstract:
Corporate directors are influenced by overconfidence, which is one of the personality traits of individuals; it may take irrational decisions that will have a significant impact on the company's performance in the long run. The purpose of this paper is to validate and compare the Naive Bayesian Classification algorithm and probit regression in the prediction of Management's overconfident at present and in the future. Financial during the years are ۲۰۱۲ to ۲۰۱۷. To support the theoretical results, the samples were the companies admitted to the Tehran Stock Exchange, (financial data of ۱۲۹۲ companies/year in total). Data collection in the theoretical part of the study benefitted from the library method, and for calculating data, Excel software was used, and in order to test the research hypotheses Matlab ۲۰۱۷ and Eviews۱۰.۰ were used. The empirical findings demonstrate that, Gained nonlinear prediction model of the Naive Bayes Classification algorithm, has high ability to predict, and the Probit regression model, has limited ability to predict the over-confidence of management. Finally, the artificial intelligence prediction model (naive Bayesian classification algorithm) has better result compared with statistical binary regression prediction model (probit regression).
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Authors
Shokoufeh Etebar
PhD student of accounting, Department of Economics and Accounting, Islamic Azad University, South Tehran Branch, Tehran, Iran
Roya Darabi
Faculty Member, Department of Economics and Accounting, Islamic Azad University, South Tehran Branch, Tehran, Iran. (Corresponding Author)
Mohsen Hamidian
Faculty Member, Department of Economics and Accounting, Islamic Azad University, South Tehran Branch, Tehran, Iran
Seiyedeh Mahbobeh Jafari
Faculty Member, Department of Economics and Accounting, Islamic Azad University, South Tehran Branch, Tehran, Iran,
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