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02351nam a22002417a 4500 |
| 001 |
2205715 |
| 041 |
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|a eng
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| 044 |
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|b مصر
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| 100 |
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|9 774072
|a El Guoshy, Omayma Rizk
|e Author
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| 245 |
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|a Predicting Auditor Opinion and Stock Price Using Machine Learning Techniques:
|b Evidence from Egypt
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| 260 |
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|b جامعة مدينة السادات - كلية التجارة
|c 2024
|g مارس
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| 300 |
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|a 480 - 519
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| 336 |
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|a بحوث ومقالات
|b Article
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| 520 |
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|b The research aims to predicting auditor opinion and stock price using Machine Learning. Techniques the Decision Tree (DT), Neural Network (NN), Bayesian Network (BN), Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Rough Sets (RS), and Random Forest (RF) are the most widely used machine learning approaches that deal with financial variables. Additionally, this study use Probit Regression. The data of this study consists of 758 firm-years of Egyptian companies listed on Egyptian Stock Market from 2012 to 2022. The results revealed that positive relationship between auditor opinion and stock prices, audit opinion significantly different between the actual value and the predicted using machine learning techniques and stock price significantly different between the actual value and the predicted using machine learning techniques. The research recommends measuring the impact machine learning algorithms and continuous auditing, audit quality, and internal auditing in the Egyptian environment.
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| 653 |
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|a المدقق المالي
|a أسعار الأسهم
|a التعلم الآلي
|a مصر
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| 692 |
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|b Auditor Opinion
|b Stock Price
|b Machine Learning
|b Decision Tree "DT"
|b Neural Network "NN"
|b Bayesian Network "BN"
|b Support Vector Machine "SVM"
|b K-Nearest Neighbors "K-NN"
|b Rough Sets "RS"
|b Random Forest
|b Probit Regression
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| 700 |
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|a Elbrashy, Ahmed Mahmoud Ahmed
|e Co-Author
|9 595629
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| 700 |
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|9 656908
|a El-Sharawy, Bassant Badr El-Din
|e Co-Author
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| 773 |
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|4 الاقتصاد
|4 الإدارة
|6 Economics
|6 Management
|c 015
|f Al-Mağallah Al-ʿilmiyyaẗ Lil Dirāsāt wa Al-Buḥṯ Al-Māliyyaẗ wa Al-’idāriyyaẗ
|l 001
|m مج16, ع1
|o 2225
|s المجلة العلمیة للدراسات والبحوث المالیة والإداریة
|v 016
|x 2682-2113
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| 856 |
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|u 2225-016-001-015.pdf
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| 930 |
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|d y
|p y
|q n
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| 995 |
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|a EcoLink
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| 999 |
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|c 1460662
|d 1460662
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