تدوین مدل کشف تقلب صورتهای مالی با استفاده از روش های شبکه عصبی مصنوعی و ماشین بردار پشتیبانی در شرکت‌های پذیرفته شده در بورس اوراق بهادر تهران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری حسابداری،واحد قشم ،دانشگاه آزاد اسلامی،قشم،ایران.

2 گروه حسابداری،دانشکده حسابداری و مدیریت،دانشگاه هرمزگان، بندرعباس، ایران

چکیده

امروزه با توجه به گسترش روزافزون بازارهای مالی و نیاز به جلب سرمایه‌گذاران داخلی و خارجی یکی از مهم‌ترین دغدغه‌های هر شرکت در راستای تأمین منابع مالی افشای صحیح اطلاعات مالی است.هدف از این پژوهش تدوین مدل کشف تقلب صورتهای مالی با استفاده از روش های شبکه عصبی مصنوعی و ماشین بردار پشتیبانی در شرکت‌های پذیرفته شده در بورس اوراق بهادر تهران بود. پژوهش حاضر از نوع پژوهش‌های کاربردی و تجربی- همبستگی است. جامعه آماری شامل شرکت‌های پذیرفته شده در بورس اوراق بهادر تهران در دوره زمانی 1397-1392است. تحقیقات اخیر مشخص کرده است که سرمایه‌گذاران در فرایند تصمیم‌گیری، شرکت‌هایی را انتخاب می‌کنند که سود آن‌ها از پایداری بالاتر و درواقع از کیفیت بالاتری برخوردار باشد. نتایج نشان داد که در بخش آموزش قدرت پیش بینی الگوریتم ماشین بردار پشتیبان حدود 86 درصد و در آزمون حدود 82 درصد بوده است. همچنین قدرت پیش بینی الگوریتم شبکه عصبی در بخش آموزش 81 درصد و در آزمون 78 درصد بوده است.

کلیدواژه‌ها

عنوان مقاله [English]

Formulation of Financial Statement Fraud Detection Model Using Artificial Neural Network and Support Vector Machine Approaches in Companies Listed in Tehran Bahador Stock Exchange

نویسندگان [English]

  • ... .. 1
  • .. .. 2
1 .
2 Department of Accounting, Faculty of Accounting and Management, Hormozgan University, Bandar-e-Abbas, Iran
چکیده [English]

Formulation of Financial Statement Fraud Detection Model Using Artificial Neural Network and Support Vector Machine Approaches in Companies Listed in Tehran Bahador Stock Exchange
Abstract:
Nowadays, due to the increasing expansion of financial markets and the need to attract domestic and foreign investors, one of the most important concerns of any company is to finance the correct disclosure of financial information. Artificial and support vector machines were listed at companies listed on the Tehran Stock Exchange. The present study is a kind of applied and empirical-correlation research. The statistical population includes the companies listed in the Tehran Stock Exchange during the period 1972-1999. Recent research has shown that investors in the decision-making process select companies whose profitability is higher and in fact higher quality. The results showed that in the training section the predictive power of the support vector algorithm was about 86% and in the test about 82%. Also, the prediction power of neural network algorithm was 81% in training and 78% in test.

کلیدواژه‌ها [English]

  • fraud
  • financial statements
  • artificial neural network
  • support vector machine

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