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Designing an Early Warning Model to Examine the Effect of OPEC Summit Announcements on Stock Market Bubble Formation: A Logit Regression
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Maryam Poursalehi    , Mehrzad Ebrahimi * , Hashem Zare , Jalil Khodaparast Shirazi |
| Department of Economics, Faculty of Economics and Management, Shiraz Branch, Islamic Azad University |
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Abstract: (21 Views) |
In today’s global economy, oil price fluctuations have significant implications across various dimensions. Economic growth, inflation, trade balance, and financial markets are all highly sensitive to changes in oil prices. These fluctuations can deeply impact markets worldwide, creating both challenges and opportunities for investors, financial institutions, and policymakers. In light of this importance, the main motivation and innovation of this study is to design an early warning model to examine the effect of OPEC summit announcements on the formation of stock market bubbles in Iran during the period from April 2011 to February 2023, using a logit regression approach. The findings indicate that OPEC announcements regarding production cuts are associated with a reduced probability of bubble formation, while announcements to maintain production levels are linked to an increased likelihood of bubble formation. Furthermore, the designed early warning model demonstrates a 94% accuracy rate in predicting bubble periods in Iran's stock market. Based on these results, it is recommended that policymakers develop an early warning system and periodically monitor key macroeconomic indicators such as money supply growth, inflation rate, exchange rate, and etc. to create the necessary conditions for taking appropriate actions to reduce the likelihood of stock market bubbles.
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| Keywords: Early Warning Model, OPEC, Stock Market, Logit Regression |
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Full-Text [PDF 1643 kb]
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Type of Study: Research |
Subject:
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