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Journals / Central Bank Review / 2009 / Cilt: 9 - Sayı: 1

Estimating value-at-risk for the Turkish stock index futures in the presence of long memory volatility

ADNAN KASMAN
Pages
1–14
DOI
—
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AI Summary & Key Takeaways

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

The results indicate strong evidence of long memory in volatility.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper examines the long memory properties for closing prices of the Turkish stock index futures market using the FIGARCH(1,d,1) model with three different distributions: Normal, Student-t, and skewed Student-t.
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Key Findings & Data:The value-at-risk (VaR) values are calculated using the estimated models.
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Conclusion & Impact:The results indicate strong evidence of long memory in volatility.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:risk · risk

Abstract

This paper examines the long memory properties for closing prices of the Turkish stock index futures market using the FIGARCH(1,d,1) model with three different distributions: Normal, Student-t, and skewed Student-t. The value-at-risk (VaR) values are calculated using the estimated models. The results indicate strong evidence of long memory in volatility. The evidence of long memory in volatility shows that uncertainty or risk is an important determinant of the behavior of daily futures prices in the Turkish futures market. The empirical results further indicate that based on the Kupiec LR failure rate test the FIGARCH(1,d,1) models with skewed Student-t distribution perform better than those of generated by normal distribution.

Keywords
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Cite This Article

KASMAN, A. (2009). Estimating value-at-risk for the Turkish stock index futures in the presence of long memory volatility. Central Bank Review, Cilt: 9 - Sayı: 1, 1–14. https://ajindex.com/articles/151031

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