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Detection of Bubbles in Tehran Stock Exchange Using Log-Periodic Power-Low Singularity Model

عنوان مقاله: Detection of Bubbles in Tehran Stock Exchange Using Log-Periodic Power-Low Singularity Model
شناسه ملی مقاله: JR_IJFIFSA-5-4_003
منتشر شده در در سال 1400
مشخصات نویسندگان مقاله:

Ali Namaki - Assistant Prof., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.
Mehrdad Haghgoo - MSc., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.

خلاصه مقاله:
One of the essential factors that lead to severe disruptions in financial markets is price bubbles and subsequent crashes. Numerous models for detecting bubbles have been developed, one of which (LPPLS) has lately attracted considerable interest. This study aims to utilize this model to detect price bubbles in Tehran Stock Exchange's index (TEDPIX). Confidence multi-scale indicators for this model are presented by fitting the LPPLS model to the data of the TSE index from ۲۰۰۹ through ۲۰۲۰. The bubble is detected when the number of fits that are in our filter conditions increases which means the growth of the indicator's value. By applying this method on TSE data two significant crashes in ۲۰۱۳ and ۲۰۲۰ are detected. The proposed technique can be useful for market participants to detect financial crashes and bubbles.

کلمات کلیدی:
Price Bubbles, LPPLS, Confidence multi-scale indicators model, Financial Crash

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1428424/