برآورد بیزی رابطه میان تلاطم بازدهی و حجم معاملات شاخص کل بورس اوراق بهادار تهران
محورهای موضوعی : مهندسی مالیابراهیم حاج خان میرزای صراف 1 , تیمور محمدی 2 , محمد رضا صالحی راد 3 , رضا طالبلو 4
1 - گروه اقتصادمالی، دانشکده اقتصاد، دانشگاه علامه طباطبائی، تهران، ایران
2 - گروه اقتصاد، دانشکده اقتصاد دانشگاه علامه طباطبائی، تهران، ایران
3 - گروه آمار، دانشکده علوم ریاضی و رایانه دانشگاه علامه طباطبائی، تهران، ایران.
4 - گروه اقتصاد، دانشکده اقتصاد دانشگاه علامه طباطبائی، تهران، ایران
کلید واژه: حجم معاملات, تلاطم بازدهی سهام, رهیافت بیزی,
چکیده مقاله :
پژوهش حاضر با هدف توسعه مدلسازی بیزی تلاطم بازدهی و حجم معاملات بورس اوراق بهادار تهران انجام پذیرفته است. بر این اساس، تلاطم بازدهی شاخص کل بورس اوراق بهادار تهران و حجم معاملات آن، در بازه زمانی1 اردیبهشت 1394 تا 8 اسفند 1397 با تواترهای روزانه، هفتگی و ماهانه مورد بررسی قرار گرفته است. یافته‌های پژوهش نشان می‌دهد فرض همبستگی شرطی ثابت مدل CCC میان متغیرها نقض شده و مشاهده می-گردد رابطه موجود از نوع همبستگی شرطی پویا مدل DCC و منفی است که دلالت بر این واقعیت دارد با افزایش بازده، سرمایه‌گذاران به دلیل خوش بینی تمایلی چندانی به فروش سهام خود ندارند و با عدم فروش آن، موجب کاهش حجم معاملات در بازار می-گردند و برعکس. از سوی دیگر یافته‌های پژوهش نشان می‌دهد در نظر گرفتن توزیع tاستیودنت چوله برای پسماندها با دمی پهن‌تر از توزیع نرمال و اعمال چولگی، از عملکرد بهتری نسبت به سایر توزیع‌ها برخوردار است.
The purpose of this study was to develop Bayesian modeling of returns volatility and turnover volumes. On this basis, the volatility of the Tehran Stock Exchange index returns and its trading volume have been studied with daily, weekly and monthly frequencies during the period of 21 April 2015 to 27 February 2019. The research findings show that the CCC model assumption of constant conditional correlation between the variables is violated and it is observed that the existing relationship is a dynamic conditional correlation type of DCC model and a negative one which implies that with increasing returns, investors due to optimism is less reluctant to sell their stock and by failing to sell it reduces the volume of transactions in the market and vice versa. On the other hand, the research findings show that considering the skew student t distribution for errors with a wider tail than the normal distribution and skewness application, it has a better performance than the other distributions.
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