ملخص المقالة :
هدف: در غالب پژوهش‌های پیشین در ایران و سایر کشورهای دیگر توانمندی سیستم‌های هوشمند در پیش‌بینی متغیرهای اقتصادی و مالی به‌ویژه قیمت سهام تأیید شده است، اما در ارزش‌گذاری معاملات بلوکی برای اولین‌بار محاسبه می‌گردد. هدف پژوهش حاضر بررسی نتایج رویدادها و اطلاعات از گزارش‌‌های مالی شرکت‌های پذیرفته شده در بورس اوراق بهادار تهران در قالب 15 شاخص مالی و یافتن میزان تأثیرگذاری این شاخص‌ها بر ارزش‌گذاری معاملات بلوکی با استفاده از آزمون Rmse بر روی داده‌های Test موردمطالعه قرار گرفته است.روش‌شناسی پژوهش: بدین منظور از اطلاعات مالی 64 شرکت ازمجموعه شرکت‌های پذیرفته شده درسازمان بورس اوراق بهادارتهران برای دوره زمانی 1390 تا1400 استفاده شده است. فرضیه‌ی تحقیق با بهره‌گیری از شبکه عصبی یادگیری عمیق مدل LSTM آزمون شده‌است.یافته‌ها: شبکة عصبی LSTM به جهت توانمندی بالا در آموزش داده‌ها و وزن‌های مناسب به این داده‌ها و خلق مسیری که با سرعت و دقت نتایج قابل‌قبولی جهت پیش‌بینی ارزش‌گذاری معاملات بلوکی دارد.اصالت / ارزش‌افزوده علمی: در مدل ارائه شده با اندازه‌گیری ارزش‌گذاری معاملات بلوکی، قیمت این معاملات، اثرات اطلاعات و نقدینگی معاملات با اندازه‌بزرگ را واپایش خواهیم نمود.
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