Adv. Math. Fin. App., 2022, 7(1), P. 245-260 Advances in Mathematical Finance & Applications www.amfa.iau-arak.ac.ir Print ISSN: 2538-5569 Online ISSN: 2645-4610 Doi: 10.22034/AMFA.2019.579662.1145 * Corresponding author. Tel.: +98 9123194494 E-mail address: : royadarabi110@yahoo.com © 2022. All rights reserved. Hosting by IA University of Arak Press Applied-Research Paper Evaluation of Intelligent and Statistical Prediction Models for Overconfidence of Managers in the Iranian Capital Market Com- panies Shokoufeh Etebar a , Roya Darabi b, *, Mohsen Hamidian b , Seiyedeh Mahbobeh Jafari b a College of Skills and Entrepreneurship, Karaj Branch, Islamic Azad University, Karaj, Iran b Department of Economics and Accounting, Islamic Azad University, South Tehran Branch, Tehran, Iran ARTICLE INFO Article history: Received 2018-11-21 Accepted 2019-08-04 Keywords: managerial overconfidence machine learning Adaboost Algorithm Probit Regression ABSTRACT Behavioural characteristic managerial overconfidence of managers ef- fects on the investment and financing decisions and company perfor- mance in the long run. the purpose of the present study was to validate the Adaboost machine learning and probit regression in the prediction of Management's overconfidence at present and in the future. It also compares the predicted models obtained during the years 2012 to 2017. The samples of the research were the companies admitted to the Tehran Stock Exchange, Data collection in the theoretical section of this study uses content analysis of international scientific articles in the library method and calculating the data used by Excel software using Matlab 2017 and Eviews10.0 to test the research hypothesis. The empirical find- ings demonstrate that The Adaboost's algorithm nonlinear prediction model represents the highest power in learning and prediction (perfor- mance of this model) the managerial over-confidence for this year and the next year, proved to be better than the probit regression prediction model. 1 Introduction One of the Managers goals is to utilize scarce resources for better rendering services and providing competitive benefits in the manufacturing companies by improved in the (technology, employee effi- ciency, industry practices, macroeconomic status, and investment) in enterprise projects [8]. In psychol- ogy science and financial management, characteristic behavior manager's is one of the known possible factors of overconfidence of management. Managerial overconfidence is one of the insights judgments and affected in decision making. The accounting information system, as a sub-system of management information, is one of the critical tools for making information relevant for decision-making. The work of this system, on the one hand, depends on the quality of the information provided, and on the other hand, on the functioning of management [12]. More importantly, this is a well-documented measurable