KaydedilenlerDerginizi ekleyin

Dergiler / Iğdır Üniversitesi Sosyal Bilimler Dergisi / 2020 / Cilt: 0 - Sayı: 22

Modeling Volatility of Sector Indexes with Mul-tivariate GARCH Model

AYŞEGÜL KIRKPINAR
Sayfa
473–486
Yayın Tarihi
2022-10-18
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The findings are of great im-portance for market participants and investors to make proper-ly asset allocation and optimal portfolio management.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:The volatility spillover effect has always been an at-tractive issue for financial market participants.
📊
Temel Bulgular & Veri:Granger causali-ty and Hong’s causality tests were used to determining causal relation between them.Examining two major sector indexes from January 4, 2010, to July 24, 2018, the findings indicated that there wasvolatility spillover BIST Financial and BIST Ser-vices sector indexes.
💡
Sonuç & Katkı:The findings are of great im-portance for market participants and investors to make proper-ly asset allocation and optimal portfolio management.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2010 Verileri
⚙️Değişkenler:Alan Parametreleri

Abstract

The volatility spillover effect has always been an at-tractive issue for financial market participants. This research aimsto investigate volatility spillover between two major sector indexes, namely BIST Financial and BIST Services of Borsa Is-tanbul by using a multivariate GARCH model. Granger causali-ty and Hong’s causality tests were used to determining causal relation between them.Examining two major sector indexes from January 4, 2010, to July 24, 2018, the findings indicated that there wasvolatility spillover BIST Financial and BIST Ser-vices sector indexes. As for causality analyses, the volatility spillover between two sector indexes indicated bivariate causal relation in accordance with both the results of the Granger cau-sality and Hong’s causality tests. The findings are of great im-portance for market participants and investors to make proper-ly asset allocation and optimal portfolio management.

🔖

Bu Makaleye Atıf Yap

KIRKPINAR, A. (2022). Modeling Volatility of Sector Indexes with Mul-tivariate GARCH Model. Iğdır Üniversitesi Sosyal Bilimler Dergisi, Cilt: 0 - Sayı: 22, 473–486. https://ajindex.com/articles/538699

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (13)

  1. Arouri, M. E. H., Jouini, j., Nguyen, D. K. (2011), “Volatility spillovers between oil prices and stock sector returns: Implications for port-folio management”,Journal of International Moneyand Finance,30,1387-1405.
  2. Arouri M. E. H., Lahiani, A., Nguyen, D. K.(2013), “World gold prices and stock returns in China: insights for hedgingand diversifica-tion strategies”,https://hal.archives-ouvertes.fr/hal-00798038
  3. Çağlı, E. Ç., Taşkın, F. D., Mandacı, P. E. (2014),“The interactions be-tween oil prices and Borsa Istanbul sector indices”,International Journal of Economic Policy in Emerging Economies, 7(1),55-65.
  4. Dickey, D. A. Fuller,W. A. (1979), “Distribution of the estimators for autoregressive time serieswith a unit root”, Journal of the American Statistical Associatio,74,427-431.
  5. Elmas, B. (2013). “İstanbul Menkul Kıymetler Borsası’nda Hesaplanan Endeksler Arası İlişkiler”, Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, C:2 S:5, 21-34.
  6. Engle, R. (2002),“Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroske-dasticity Models”, American Statistical Association Journal of Busi-ness & Economic Statistics, 20 (3). Granger, C. W. J. (1969), “Investigating causal relations by econometric models and cross-spectral methods”, Econometrica, 37, 424–438. doi: 10.2307/1912791. Goeij P., Marquering, W. (2009),“Stock and bond market interactions with level and asymmetry dynamics: An out-of-sample applica-tion”,Journal of Empirical Finance,16, 318–329.
  7. Haesen, D., Houweling, P., and Van Zundert, J. (2017),“Momentum spilloverfrom stocks to corporate bonds”,Journal of Banking & Fi-nance, 79, 28-41.
  8. Hassan, S. A., Malik, F. (2007),“Multivariate GARCH modeling of sector volatility transmission”,The Quarterly Review of Economics and Finance, 47,470–480.
  9. Hong, Y. (2001),“A test for volatility spillover withapplication to exchange rates”,Journal of Econometrics, 103,183-224.
  10. Jones, P. M., Olson E. (2013), “The time-varying correlation between uncertainty, output, and inflation: Evidence from a DCC-GARCH model”, Economics Letters, 118, 33–37.
  11. Kim, S. J., Moshirian, F., WU, E. (2006),“Evolution of international stock and bond market integration: Influenceof the European Monetary Union”,Journal of Banking & Finance, 30(5), 1507-1534.
  12. Kouki I., Harrathi, N., Haque, M. (2011),“A volatility spillover among sector indexof international stock markets”,Journal of Money, In-vestment and Banking, 22,32-45.
  13. Malik, F.,