پیش بینی شاخص بورس اوراق بهادار تهران با استفاده از شبکه های عصبی

مدیریت بهره‌وری

مقاله 8، دوره 3، 2(9)تابستان، شهریور 1388، صفحه 191-212   

نوع مقاله: علمی پژوهشی

نویسندگان

بیتا دلنواز اصغری¹؛ میر فیض فلاح شمس^{* 2}

¹کارمند دانشگاه آزاد اسلامی واحدتبریز و دانش آموخته کارشناسی ارشد مدیریت مالی

²استادیارگروه مدیریت مالی ، واحد تهران مرکزی، ،دانشگاه آزاد اسلامی،تهران،ایران

چکیده

اندازه و روند شاخص‌های قیمت سهام یکی از مهمترین عوامل تاثیرگذار بر تصمیمات سرمایه گذاران در بازارهای مالی می‌باشد. جهت پیش‌بینی بازار از تکنیکهای مختلفی استفاده شده است که معمول‌ترین آنها روشهای رگرسیون و مدل‌های 3ARIMA هستند اما این مدل‌ها در عمل جهت پیش‌بینی بعضی از سریها ناموفق بوده‌اند. در تحقیق حاضر برای پیش‌بینی شاخص کل بورس از مدل شبکه‌های عصبی پیش خور4 با قانون یادگیری پس انتشار خطا5 در سه ساختار شبکه با الگوهای متفاوت ورودی استفاده گردید و  نتایج مدل با نتایج مدل‌های رگرسیون چند متغیره و مدل‌های ARIMA مورد مقایسه قرار گرفت.
نتایج تحقیق نشان داد که روش شبکه‌های عصبی خطای RMSE به میزان قابل توجهی کمتر از RMSE روشهای دیگر است و در بازار بورس اوراق بهادارتهران پیش‌بینی کوتاه مدت با فاصله زمانی کمتر، مناسب‌تر از پیش‌بینی بلند مدت با فاصله زمانی طولانی تر است.                                                                                                                                                                                                                                                                                                                           



3. autoregressive integrated moving average


4. Feed Forward Neural network


5. back propagation

کلیدواژه‌ها

شاخص سهام؛ پیش‌بینی؛ شبکه‌های عصبی؛ سری‌های زمانی

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