مدل سازی نوسانات بازده بورس اوراق بهادار تهران مدل MRS-FI-TGARCH و FI-TGARCH

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری،گروه اقتصاد، واحد شیراز، دانشگاه آزاداسلامی، شیراز، ایران

2 استادیار و عضو هیات علمی گروه اقتصاد، واحد شیراز، دانشگاه آزاداسلامی، شیراز، ایران (نویسنده مسئول)

3 استادیار و عضو هیات علمی گروه اقتصاد، واحد شیراز، دانشگاه آزاداسلامی، شیراز، ایران.

چکیده

هدف این مقاله افزایش انعطاف پذیری مدل سازی نوسانات بازار سرمایه می باشد. این امربا معرفی مدل MRS-FI-TGARCH برای اولین بار در دنیا انجام می گیرد. به این منظور از شاخص هفتگی قیمت بورس اوراق بهادار تهران طی سالهای ۲۰۰۹ تا ۲۰۱۷ استفاده می شود .پارامترها قابلیت تغییر با رژیم را دارند. نتایج نشان داد دو رژیم رونق، با بازده انتظاری بالا و نوسان بالا و رژیم رکود، با بازده انتظاری پایین و نوسان پایینوجود دارند. افزودن قابلیت پیش بینی اثرات نامتقارن وحافظه بلند مدت نوآوری مدل جدید است. معناداری ضریب منفی اثرات نامتقارن دررژیم رونق نشان می دهد اثر اخبار بد بر نوسانات، کمتر از اخبار خوب است . معنادارنبودن آن در رژیم رکود ، بیانگرمتقارن بودن اثرات اخبار خوب و بد است. دررژیم رونق، حافظه نامحدود وجود دارد اما دررژیم رکود اثر نوسانات با نرخ هیپربولیک کاهش می یابد.

کلیدواژه‌ها


عنوان مقاله [English]

Modelling of capital market returns fluctuations for Tehran Price Index Return: MRS-FI-TGARCH and FI-TGARCH models

نویسندگان [English]

  • Hajar Moradian 1
  • Ali Haghighat 2
  • Hashem Zare 3
  • Mehrzad Ebrahimi 3
1 PhD Student, Department of Economics and Management- Islamic Azad University Shiraz Branch,
2 Assistant professor and member of Scientific Board- Islamic Azad University Shiraz Branch, (corresponding author)
3 Assistant professor and member of Scientific Board- Islamic Azad University Shiraz Branch
چکیده [English]

The aim of this paper is to expand flexibility of modeling in capital market fluctuations. We achieve the goal by introducing MRS-FITGARCH model for the first time in the world. We use weekly TEPIX changes from 2009 to 2017. The parameters could change through the regimes. Results show that there are two regimes; regime one with high return mean and high return variance and regime two with low return mean and low return variance. Adding asymmetric effects and long memory potential prediction, are the novation of our new model. Valued Negative asymmetric effects coefficient results that bad news effects on the fluctuations were less than good news. It was not to be valued in regime tow and it means, good news and bad news has the symmetric effects in this regime. In regime one, there is unlimited long memory coefficient but in regime two fluctuations effects decreases in hyperbolic rate.
 

کلیدواژه‌ها [English]

  • Modeling
  • Stock Return
  • markove
  • long memory
  • symmetric
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