مدلسازی رفتارهای پیچیده و کامپوزیتی نوسانات آنتروپی بازار سهام با استفاده از فیزیک آماری
کلمات کلیدی:
رفتارهاي پیچیده , نوسانات آنتروپي بازار سهام , فیزیک آماري, عدم قطعیت , حرکت استاندارد برآونیچکیده
هدف: هدف پژوهش حاضر، تحلیل و مدلسازی رفتارهای پیچیده و کامپوزیتی نوسانات آنتروپی بازار سهام ایران با استفاده از مفاهیم فیزیک آماری و استخراج الگوهای پویای نوسانات از فرآیندهای براونی، پواسون، لوی و لوی-خینچین است. روششناسی: این پژوهش از نوع کمی و در چارچوب مدلسازی پیشبینی انجام شده است. دادههای پژوهش شامل شاخصهای اصلی بازار سهام ایران در بازه زمانی ۱۳۹۱ تا ۱۴۰۳ با فرکانس ماهانه است. برای تحلیل از فرآیند تماسهای تصادفی بین شاخصها، فرآیند نوسانات پرش تصادفی، و توابع ترکیبی احتمال در چارچوب فیزیک آماری استفاده شد. مدلهای براونی، پواسون و لوی-خینچین برای شبیهسازی حرکات تصادفی و پرشهای ناگهانی به کار رفتند. دادهها با نرمافزارهای R، Python و MATLAB تحلیل و از آزمونهای همبستگی، رگرسیون چندمتغیره، مدلهای AR، GARCH و مدل میانگین متحرک وزنی نمائی چندمتغیره برای بررسی پویایی روابط میان متغیرها استفاده گردید. یافتهها: نتایج نشان داد که آنتروپی بازار سهام ایران به طور معناداری تحت تأثیر نوسانات قیمت نفت، نرخ ارز، اونس جهانی طلا، صرف ریسک بازار و رمزارزها قرار دارد. نوسانات شدید قیمت نفت و رمزارزها موجب افزایش آنتروپی و پیچیدگی بازار شدهاند، در حالی که نوسانات کوچکتر تأثیر تدریجیتری دارند. مدل پرش تصادفی و فرآیند لوی-خینچین توانستند بهطور دقیق پویایی رفتارهای غیرخطی و اثرات متقابل میان متغیرهای کلان اقتصادی و مالی را تبیین کنند. بر اساس نتایج آزمون انگل–شپارد و تسای، همبستگی میان متغیرها زمانمتغیر بوده و مدل میانگین متحرک وزنی نمائی عملکرد بهتری نسبت به مدل ناهمسانواریانس شرطی داشت. نتیجهگیری: پژوهش حاضر نشان داد که مدلسازی فیزیک آماری و بهویژه فرآیند لوی-خینچین ابزاری قدرتمند برای درک پیچیدگی و پیشبینی رفتارهای غیرخطی در بازار سهام ایران است. این مدلها با توانایی شناسایی پرشهای تصادفی، امکان تحلیل دقیقتر ریسک و بیثباتی بازار را فراهم میکنند و میتوانند به بهبود تصمیمگیری سرمایهگذاران و سیاستگذاران کمک کنند.
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حق نشر 2025 Mahsa Rahavi, Gholamreza Zomorodian, Bahman Banimahd (Author)

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