Journals / Finans Politik ve Ekonomik Yorumlar Dergisi / 2011 / Cilt: 48 - Sayı: 551

Global crisis and exchange rate volatility transmission

Küresel kriz ve döviz kurlarında oynaklık geçişi

Pages
9–17
DOI
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AI Summary & Key Takeaways

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

The empirical results show that, the exchange rate volatility has increased during the global crisis period and both the source of degree of innovation and the source of volatility transmission is USD exchange rate.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The importance of the volatility transmission across the international financial markets has become a current issue by the effects of global crisis in 2008.
📊
Key Findings & Data:The purpose of this study is to assign the effect of the global crisis among the exchange rate volatilities and which exchange rate is more effective than the others in the volatility transmission.
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Conclusion & Impact:The empirical results show that, the exchange rate volatility has increased during the global crisis period and both the source of degree of innovation and the source of volatility transmission is USD exchange rate.
🔬Design:Modeling & Simulation
📍Scope:2008 Verileri
⚙️Variables:Domain Parameters

Abstract

The importance of the volatility transmission across the international financial markets has become a current issue by the effects of global crisis in 2008. The purpose of this study is to assign the effect of the global crisis among the exchange rate volatilities and which exchange rate is more effective than the others in the volatility transmission. We analyze EUR, USD and JPY daily exchange rate series for the period December 2001-May 2010 by using a multivariate GARCH model. The empirical results show that, the exchange rate volatility has increased during the global crisis period and both the source of degree of innovation and the source of volatility transmission is USD exchange rate.

Özet

Uluslararası finansal piyasalar arasındaki oynaklık geçişlerinin önemi, 2008 yılında yaşanan küresel kriz ile tekrar gündeme gelmiştir. Bu çalışmanın amacı, küresel krizin döviz kurları oynaklığı üzerindeki etkisini ve döviz kurları arasındaki oynaklık geçişlerini belirlemektir. Çalışmada, Aralık 2001-Mayıs 2010 dönemine ait EUR, USD ve JPY günlük döviz kuru serileri analize dahil edilmiştir. Oynaklık geçişlerinin kaynağının ve büyüklüğünün belirlenmesi için çok değişkenli GARCH (multivariate GARCH) yöntemi kullanılmıştır. Elde edilen ampirik sonuçlara göre; küresel kriz sürecinde serilerin oynaklığının arttığı ve hem haber etkisinin hem de oynaklık geçişinin kaynağının USD döviz kuru olduğu belirlenmiştir.

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Cite This Article

URAL, M., ÖZTEKİN, D. (2011). Global crisis and exchange rate volatility transmission. Finans Politik ve Ekonomik Yorumlar Dergisi, Cilt: 48 - Sayı: 551, 9–17. https://ajindex.com/articles/224037

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References (16)

  1. BAUWENS, L., S. LAURENT VE J.V.K. ROMBOUTS (2006), “Multivariate GARCH Models: A Survey”, Journal of Applied Econometrics, 21(1), 79-109.
  2. BOLLERSLEV, T. (1990), “Modeling the Coherence in Short Run Nominal Exchange Rates: A Multivariate Generalized ARCH Approach”, Review of Economics and Statistics, 72, 498-505.
  3. BOLLERSLEV, T., R.F. ENGLE VE J.M. WOOLDRIDGE (1988), “A Capital Asset Pricing Model with Time-Varying Covariances”, The Journal of Political Economy, 96, 116-131.
  4. BOZKURT, H. (2009), “M-GARCH Modellerinin Karşılaştırmalı Analizi”, Kocaeli Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18(2), 126-145.
  5. BROOKS, C. (2008), Introductory Econometrics for Finance, Cambridge University Press,
  6. Second Edition.
  7. BROOKS, C., S. BURKE VE G. PERSAND (2003), “Multivariate GARCH Models: Software Choice and Estimation Issues”, ISMA Centre Discussion Papers in Finance, 2003-07.
  8. CAPORALE, G.M., N. PITTIS VE N. SPAGNOLO (2006), “Volatility Transmission and Financial Crises”, Journal of Economics and Finance, 30(3), 376-390.
  9. ÇİÇEK, M. VE F. ÖZTÜRK (2007), “Yabancı Hisse Senedi Yatırımcıları Türkiye’de Döviz Kuru Volatilitesini Şiddetlendiriyor mu?”, Ankara Üniversitesi Siyasal Bilgiler Fakültesi Dergisi, 62(4), 83-106.
  10. ENGLE, R.F. VE K. SHEPPARD (2001), “Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH”, NBER Working Paper Series, National Bureau of Economic Research, Working Paper No: 8554. ENGLE, R.F, K.F. KRONER, Y. BABA VE D.F. KRAFT (1993), “Multivariate Simultaneous Generalized ARCH”, University of California, Economics Working Paper Series, 89-57.
  11. ENGLE, R.F. VE K.F. KRONER (1995), “Multivariate Simultaneous Generalized ARCH”, Econometric Theory, 11(01), 122- 150. HAMILTON, J.D. (1994),
  12. Time Series Analysis, Princeton University Press,
  13. USA. KAROLYI, G.A. (1995), “A Multivariate GARCH Model of International Transmissions of Stock Returns and Volatility: The Case of the United States and Canada”, Journal of Business & Economic Statistics, 13(1), 11-25.
  14. KEARNEY, C. VE A.J. PATTON (2000), “Multivariate GARCH Modeling of Exchange Rate Volatility Transmission in the European Monetary System”, The Financial Review, Eastern Finance Association, 35(1), 29-48.
  15. KHALID, A.M. VE G. RAJAGURU (2005), “Financial Market Contagion: Evidence from Asia Using Fraction Co-integration and Multivariate GARCH Approach”, www.economics.smu. edu.sg/events/Paper/ahmed_khalid.pdf, (12.04.2010).
  16. LAURENT, S., J.V.K. ROMBOUTS, A. SILVENNOINEN VE F. VIO