نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مدیریت صنعتی گرایش مالی، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

2 استاد،گروه مدیریت مالی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران.

3 استاد،گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی تهران، تهران، ایران.

4 دانشیار،گروه مدیریت مالی، دانشکده مدیریت، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.

چکیده

چکیده
افزایش میزان تقلب در گزارشگری مالی در سال‌های اخیر باعث عدم اعتماد سرمایه‌گذاران به بازار‌های سرمایه شده است. به همین علت پیش‌بینی دقیق مدیریت سود یکی از نیازهای اساسی برای تصمیم‌گیری استفاده‌کنندگان صورت‌های مالی است. این پژوهش با ارائه یک مدل توسعه‌یافته بر مبنای مدل بنیش با تأکید بر متغیر‌های نظام راهبری شرکتی مشتمل بر ساختار کمیته حسابرسی، بازرس قانونی و حسابرس مستقل، ساختار هیئت‌مدیره و ساختار مالکیت شرکتی سعی درافزایش دقت پیش‌بینی مدیریت سود دارد. داده‌های 81 شرکت پذیرفته‌شده در بورس اوراق بهادار تهران طی سال‌های 1397-1391 با روش ترکیبی شبکه عصبی پرسپترون چندلایه و الگوریتم‌های کیهان‌شناسی سیاه­‌چاله، مه­‌بانگ – مه‌رمب و ازدحام ذرات کهکشانی مورد تحلیل قرارگرفته است. دقت پیش‌بینی مدل با روش ترکیبی شبکه عصبی مصنوعی و الگوریتم‌­های کیهان‌­شناسی ازدحام ذرات کهکشانی، مه­‌بانگ – مه­‌رمب و سیاه­‌چاله به ترتیب از 59/08 ، 63/49 و 57/5 درصد به 87/3، 79/72 و 74/25 درصد افزایش پیداکرده است که حاکی از بهبود قدرت پیش­‌بینی مدل در کشف شرکت‌­های دستکاری کننده سود است. در مدل پیشنهادی سطح زیر منحنی مربوط به دو الگوریتم سیاه‌­چاله ومه­‌بانگ-مه‌رمب، توسط الگوریتم ازدحام ذرات کهکشانی احاطه‌شده است ونشان دهنده این است که خطای شبکه عصبی پرسپترون چند­لایه ترکیبی با الگوریتم ازدحام ذرات کهکشانی به 12/7 درصد کاهش‌یافته است.

کلیدواژه‌ها

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