Evolutionary Ensemble for Stock Prediction
نویسندگان
چکیده
We propose a genetic ensemble of recurrent neural networks for stock prediction model. The genetic algorithm tunes neural networks in a two-dimensional and parallel framework. The ensemble makes the decision of buying or selling more conservative. It showed notable improvement on the average over not only the buy-and-hold strategy but also other traditional ensemble approaches.
منابع مشابه
سودمندی رگرسیون‌های تجمیعی و روش‌های انتخاب متغیرهای پیش‌بین بهینه در پیش‌بینی بازده سهام
مقاله حاضر به بررسی سودمندی رگرسیون‌های تجمیعی و روش‌های انتخاب متغیرهای پیش‌بین بهینه (شامل روش مبتنی بر همبستگی و ریلیف) برای پیش‌بینی بازده سهام شرکت‌های پذیرفته شده در بورس اوراق بهادار تهران می‌پردازد. به‌منظور ارزیابی عملکرد رگرسیون تجمیعی، معیارهای ارزیابی (شامل میانگین قدرمطلق درصد خطا، مجذور مربع میانگین خطا و ضریب تعیین) مربوط به پیش‌بینی این روش، با رگرسیون خطی و شبکه‌های عصبی مصنوعی...
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