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Journals / Central Bank Review / 2007 / Cilt: 7 - Sayı: 2

Long Memory in the Turkish Stock Market Return and Volatility

ADNAN KASMAN
Erdost TORUN
Pages
13–27
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results indicate that long memory dynamics in the returns and volatility might be modeled by using the ARFIMA-FIGARCH model.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper examines the dual long memory property of the Turkish stock market.
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Key Findings & Data:The data set consists of daily returns, and long memory tests are carried out both for the returns and volatility.
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Conclusion & Impact:The results indicate that long memory dynamics in the returns and volatility might be modeled by using the ARFIMA-FIGARCH model.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

This paper examines the dual long memory property of the Turkish stock market. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatility. The results indicate that long memory dynamics in the returns and volatility might be modeled by using the ARFIMA-FIGARCH model. The results of the ARFIMAFIGARCH model show strong evidence of long memory in both returns and volatility. The long memory in returns implies that stock prices follow a predictable behavior, which is inconsistent with the efficient market hypothesis. The evidence of long memory in volatility, however, shows that uncertainty or risk is an important determinant of the behavior of daily stock data in the Turkish stock market.

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Cite This Article

KASMAN, A., TORUN, E. (2007). Long Memory in the Turkish Stock Market Return and Volatility. Central Bank Review, Cilt: 7 - Sayı: 2, 13–27. https://ajindex.com/articles/151729

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