Journals / Maliye ve Finans Yazıları / 2017 / Sayı: 107

Regime Dynamics of International Precious Metal Markets

Uluslararası Kıymetli Metal Piyasalarının Rejim Dinamikleri

Pages
26–40
Publication Date
2017-04-18
DOI
—
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AI Summary & Key Takeaways

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

Research results have evidence that the international precious metal market have a structure with three regimes as depression, moderate growth and expansion.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study is to analyze whether the precious metals have a nonlinear pattern by using Multivariate Markov Switching Vector Autoregressive Models (MMS-VAR).
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Key Findings & Data:The observation period is between 02 January 2002 and 28 March 2016 and includes daily closed prices of gold, silver, palladium and platinum.
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Conclusion & Impact:Research results have evidence that the international precious metal market have a structure with three regimes as depression, moderate growth and expansion.
🔬Design:Modeling & Simulation
📍Scope:2002 Verileri
⚙️Variables:Kıymetli Metal Piyasaları · Doğrusal Olmama · Markov Rejim Değişim Vektör Otoregresif Modeli

Abstract

The aim of this study is to analyze whether the precious metals have a nonlinear pattern by using Multivariate Markov Switching Vector Autoregressive Models (MMS-VAR). The observation period is between 02 January 2002 and 28 March 2016 and includes daily closed prices of gold, silver, palladium and platinum. Research results have evidence that the international precious metal market have a structure with three regimes as depression, moderate growth and expansion.

Özet

Bu çalışmanın amacı, kıymetli metal piyasalarının doğrusal olmayan yapılarını Çok Değişkenli Markov Rejim Değişim Modelleriyle (MMS-VAR) analiz etmektir. Çalışmanın gözlem aralığı 02 Ocak 2002 – 28 Mart 2016 olup, spot altın, gümüş, paladyum ve platine ait günlük kapanış fiyatlarını içermektedir. Araştırma sonuçları, uluslararası kıymetli metal piyasasının daralma, ılımlı büyüme ve genişleme rejimlerinden oluşan bir yapıya sahip olduğuna dair kanıtlar sunmaktadır.

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Cite This Article

KOY, A., ÇETİN, G., ERSAN, İ. (2017). Regime Dynamics of International Precious Metal Markets. Maliye ve Finans Yazıları, Sayı: 107, 26–40. https://ajindex.com/articles/228858

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References (15)

  1. Ang, A., Timmermann A. G. 2011. Regime Changes and Financial Markets. Netspar Discussion Papers, DP 06/2011-068.
  2. Arouri, M. vd. 2013. On the short- and long-run efficiency of energy and precious metal markets. Energy Economics. 40, 832–844
  3. Arouri, M. H., D. N. Nguyen. 2010. Oil prices, stock markets and portfolio investment: evidence from sector analysis in Europe over the last decade. Energy Policy. 38, 4528–4539.
  4. Balcılar, M. vd. 2015. A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates. International Review of Economics and Finance. 40, 72-89.
  5. Bildirici, M. vd. 2010. İktisatta Kullanılan Doğrusal Olmayan Zaman Serisi Yöntemleri. İstanbul:
  6. Türkmen Kitabevi.
  7. Brockwell, P. 2011. Discussion of Threshold models in time series analysis-30 years on. Statistics and Its Interface. 4, 129-130.
  8. Caporin, M., A. Ranaldo and G. G. Velo. 2015. Precious metals under the microscope: a high-frequency analysis. Quantitative Finance. 15( 5), 743–759.
  9. Charlot, P. and V. Marimoutou. 2014. On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree, Energy Economics. 44, 456-467.
  10. Cheng, H., L. Shao, and Y. Guo. 2013. State Transition Behaviors of SHFE Copper Prices Based on Markovswitching Model, Journal of Convergence Information Technology. 8(6). Conover, C. M., G. R. Jensen, R. R. Johnson, J. M. Mercer. 2010. Is now the time to add commodities to your portfolio? Journal of Invest. 19, 10–19.
  11. Daskalaki, C., G. S. Skiadopoulos. 2011. Should investors include commodities in their portfolios after all? New evidence. Journal of Banking and Finance. 35, 2606–2626. Franses P.H. and D. van. Dijk. 2000. Nonlinear Time Series Models in Empirical Finance. Cambridge Universtiy Press.
  12. Guidolin, M. Modelling, Estimating and Forecasting Financial Data under Regime (Markov) Switching. Lecture 7. Department of Finance. Bocconi University. http://didattica.unibocconi.it/mypage/dwload.php?nomefile=Lecture_7_-_Markov_Switching_Models20130520235704.pdf, 30.03.2016.
  13. Hamilton, J. D. 1989. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica. 57(2), 357-384.
  14. Hammoudeh, S. P. Araújo-Santos, A. Al-Hassan, 2013. Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks. The North American Journal of Economics and Finance. 25, 318–334.
  15. Neftçi, S. N. 1984. Are Eco