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Journals / Journal of Life Economics / 2022 / Cilt: 9 - Sayı: 3

The comparison of range-based volatility estimators and an application of TVP-VARbased connectedness

Yakup ARI
Pages
147–157
Publication Date
2022-08-07
DOI
—
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AI Summary & Key Takeaways

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

The comparison results show that Rogers-Satchell for ASELSAN, KATMERLER, and PAPIL, and Parkinson volatility estimator for OTOKAR have the smallest error, respectively.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper aims to show the application of range-based volatility in connectedness analysis.
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Key Findings & Data:We compared the forecast performance of volatility against Heteroskedastic Root Mean Square Error statistics.
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Conclusion & Impact:The comparison results show that Rogers-Satchell for ASELSAN, KATMERLER, and PAPIL, and Parkinson volatility estimator for OTOKAR have the smallest error, respectively.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Diebold-Yilmaz Connectedness · HRMSE · Range-based volatility

Abstract

This paper aims to show the application of range-based volatility in connectedness analysis. For this purpose, we compare the volatility estimators Parkinson, Yang-Zhang, Garman-Klass, Rogers-Satchell, and modified Garman- Klass by Yang and Zhang methods. As an example, we calculated the range-based stock prices’ volatility of four defense industry companies quoted in Borsa Istanbul. We compared the forecast performance of volatility against Heteroskedastic Root Mean Square Error statistics. We include the best performing volatility series in the spillover analysis. Instead of the Cholesky decomposition VAR and generalized VAR approaches used in the calculation of the Diebold-Yılmaz connectedness index, we apply the TVP-VAR-based connectedness approach. The comparison results show that Rogers-Satchell for ASELSAN, KATMERLER, and PAPIL, and Parkinson volatility estimator for OTOKAR have the smallest error, respectively. The empirical findings of TVP-VAR connectedness show that the average forecast error variance of the network is 34.35%.

Özet

This paper aims to show the application of range-based volatility in connectedness analysis. For this purpose, we compare the volatility estimators Parkinson, Yang-Zhang, Garman-Klass, Rogers-Satchell, and modified Garman- Klass by Yang and Zhang methods. As an example, we calculated the range-based stock prices’ volatility of four defense industry companies quoted in Borsa Istanbul. We compared the forecast performance of volatility against Heteroskedastic Root Mean Square Error statistics. We include the best performing volatility series in the spillover analysis. Instead of the Cholesky decomposition VAR and generalized VAR approaches used in the calculation of the Diebold-Yılmaz connectedness index, we apply the TVP-VAR-based connectedness approach. The comparison results show that Rogers-Satchell for ASELSAN, KATMERLER, and PAPIL, and Parkinson volatility estimator for OTOKAR have the smallest error, respectively. The empirical findings of TVP-VAR connectedness show that the average forecast error variance of the network is 34.35%.

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Cite This Article

ARI, Y. (2022). The comparison of range-based volatility estimators and an application of TVP-VARbased connectedness. Journal of Life Economics, Cilt: 9 - Sayı: 3, 147–157. https://ajindex.com/articles/866199

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References (9)

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