SavedAdd your journal

Journals / Business and Management Studies: An International Journal / 2020 / Cilt: 8 - Sayı: 1

VOLATILITY INTERACTION BETWEEN BIST (BORSA ISTANBUL) TECHNOLOGY INDEX AND OTHER MAIN SECTOR INDICES

BORSA İSTANBUL (BIST) TEKNOLOJİ ENDEKSİ VE DİĞER ANA SEKTÖR ENDEKSLERİ ARASINDAKİ VOLATİLİTE ETKİLEŞİMİ

Barış KOCAARSLAN
Pages
458–475
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

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

The analysis results show a substantial one-way volatility spillover from BIST Technology index to other indices.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study is to test the causality in variance (volatility spillover) relationship between the Borsa Istanbul (BIST) Technology Index and other main industry indices (BIST Industry, BIST Services and BIST Financial indices).
📊
Key Findings & Data:To this end, a causality in variance approach developed by Hafner and Herwartz (2006) is used.
💡
Conclusion & Impact:The analysis results show a substantial one-way volatility spillover from BIST Technology index to other indices.
🔬Design:Modeling & Simulation
📍Scope:2006 Verileri
⚙️Variables:Domain Parameters

Abstract

The aim of this study is to test the causality in variance (volatility spillover) relationship between the Borsa Istanbul (BIST) Technology Index and other main industry indices (BIST Industry, BIST Services and BIST Financial indices). To this end, a causality in variance approach developed by Hafner and Herwartz (2006) is used. The results of the volatility model show that long-term volatility considerably affects all sector indices. According to the causality in variance test results, it is found that there are significant volatility spillovers between the main sector indices. The analysis results show a substantial one-way volatility spillover from BIST Technology index to other indices. In addition, the findings point to the presence of volatility transmission from BIST Industrial index to BIST Services and BIST Financial indices. Finally, a two-way volatility spillover between BIST Services and BIST Financial indices is observed. The test results contain important information for market participants in determining optimal hedging and investment strategies.

Özet

Bu çalışmanın amacı Borsa İstanbul (BIST) Teknoloji endeksi ve diğer ana sektör endeksleri (BIST Sınai, BIST Hizmetler ve BIST Mali endeksleri) arasındaki varyansta nedensellik (volatilite geçişkenliği) ilişkisini test etmektir. Bu amaçla, Hafner ve Herwartz (2006) tarafından geliştirilen varyansta nedensellik yaklaşımı kullanılmıştır. Volatilite modeli sonuçları, uzun vadeli volatilitenin sektör endekslerinin tamamını büyük ölçüde etkilediğini göstermektedir. Varyansta nedensellik testi sonuçlarına göre, ana sektör endeksleri arasında önemli derecede volatilite yayılımları olduğu bulgusuna ulaşılmıştır. Analiz sonuçları, BIST Teknoloji endeksinden diğer endekslere doğru oldukça güçlü tek yönlü volatilite geçişkenliğini göstermektedir. Ayrıca, bulgular BIST Sınai endeksinden BIST Hizmetler ve BIST Mali endekslerine doğru volatilite yayılımının varlığını işaret etmektedir. Son olarak, BIST Hizmetler ve BIST Mali endeksleri arasında iki yönlü volatilite geçişkenliği olduğu gözlemlenmiştir. Test sonuçları optimum riskten korunma ve yatırım stratejileri belirleme açısından piyasa katılımcıları için önemli bilgiler içermektedir.

🔖

Cite This Article

KOCAARSLAN, B. (2020). VOLATILITY INTERACTION BETWEEN BIST (BORSA ISTANBUL) TECHNOLOGY INDEX AND OTHER MAIN SECTOR INDICES. Business and Management Studies: An International Journal, Cilt: 8 - Sayı: 1, 458–475. https://ajindex.com/articles/144808

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (17)

  1. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292.
  2. Barberis, N., & Thaler, R. (2003). A survey of behavioral finance. Handbook of the Economics of Finance, 1, 1053-1128.
  3. Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307-343.
  4. Berument, H., Akdi, Y., & Atakan, C. (2005). An empirical analysis of Istanbul stock exchange sub-indexes. Studies in Nonlinear Dynamics & Econometrics, 9(3). Bloom, N. (2014). Fluctuations in uncertainty. Journal of Economic Perspectives, 28(2), 153-76.
  5. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
  6. Cheung, Y. W., & Ng, L. K. (1996). A causality-in-variance test and its application to financial market prices. Journal of Econometrics, 72(1-2), 33-48.
  7. Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under‐and overreactions. The Journal of Finance, 53(6), 1839-1885.
  8. De Bondt, W. F., & Thaler, R. (1985). Does the stock market overreact?. The Journal of Finance, 40(3), 793- 805. Dreman, D. N., & Berry, M. A. (1995). Overreaction, underreaction, and the low-P/E effect. Financial Analysts Journal, 51(4), 21-30.
  9. Duran, S., & Şahin, A. (2006).
  10. İMKB Hizmetler, Mali, Sınai ve Teknoloji Endeksleri Arasındaki İlişkinin Belirlenmesi.Sosyal Bilimler Araştırmaları Dergisi, 1, 57-70.
  11. Elliott, G., Rothenberg, T., & Stock, J. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813-836.
  12. Enders, W., & Siklos, P. L. (2001). Cointegration and threshold adjustment. Journal of Business & Economic Statistics, 19(2), 166-176.
  13. Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: Journal of the Econometric Society, 55, 251-276.
  14. Eyüboğlu, S., & Eyüboğlu, K. (2019). Borsa İstanbul sektör endekslerinin karşılıklı bağımlılıklarının test edilmesi. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, (53), 246-260.
  15. Fleming, J., Kirby, C., & Ostdiek, B. (1998). Information and volatility linkages in the stock, bond, and money markets. Journal of Financial Economics, 49(1), 111-137.
  16. Gervais, S., & Odean, T. (2001). Learning to be overconfident. The Review of Financial Studies, 14(1), 1-27.
  17. Granger, C. (1969). Investigating causal relations by econometric m