روشی جهت پیش‌بینی قیمت سهام بازار بورس تهران مبتنی بر یادگیری عمیق

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، دانشگاه پیام نور، تهران، ایران

2 استادیار، دانشگاه پیام نور، تهران، ایران

چکیده

در سال‌های اخیر با توجه به سوددهی بازار بورس اوراق بهادار در ایران سرمایه‌های خرد و کلان جذب این بازار شدند ، اما متأسفانه به دلیل دانش کم این افراد از بورس و پیش‌بینی قیمت‌ها تعداد فراوانی از مردم ایران ضرر و زیان زیادی را متحمل شدند . در این تحقیق بر آن شدیم تا با استناد به تحقیق قبلی خود که از شبکه عصبی با دولایه LSTM استفاده می‌کرد .کار خود را قوت بخشیده و شبکه عصبی ترکیبی کانولوشن وlstm را جهت پیش‌بینی قیمت سهام بر روی مجموعه دیتاست وب ملت از بازار بورس اوراق بهادار تهران و سه دیتاست موجود در آن شامل آث پ ،خودرو و وساخت به کار ببریم. در انتها جهت ارزیابی روش پیشنهادی و دو روش دیگر ازنظر سه تابع خطا ،تابع میانگین مربع خطا (MSE)، تابع میانگین خطای مطلق (MAE) و تابع میانگین مربع ریشه (RMSE) بررسی شد . نتایج حاصله نشان داد در دیتاست های بزرگ با تعداد داده‌های سهام بالا بسیار بهتر عمل کرده و خطای کمتری به دنبال دارد.

کلیدواژه‌ها


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دوره 10، شماره 4 - شماره پیاپی 40
شماره پیاپی 40، فصلنامه زمستان
بهمن 1401
صفحه 91-100
  • تاریخ دریافت: 15 اردیبهشت 1401
  • تاریخ بازنگری: 08 خرداد 1401
  • تاریخ پذیرش: 18 مرداد 1401
  • تاریخ انتشار: 01 بهمن 1401