Journals / Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi / 2018 / Cilt: 15 - Sayı: 41

REGIME RELATED VOLATILITY IN OIL FUTURES PRICES

VADELİ PETROL FİYATLARINDA REJİMLE DEĞİŞEN VOLATİLİTE

Pages
175–184
Publication Date
2018-04-29
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 volatility of the oil futures contract is switching between two regimes with low volatility and high volatility depending on a markov process.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Oil futures prices, which have undergone major changes, maintain an important research topic for academics.
📊
Key Findings & Data:Oil prices, which tended to decline for political and economic reasons in the 1990s, fell to as low as 12 US dollars after the Asian Crisis, rising again in 2002.
💡
Conclusion & Impact:The volatility of the oil futures contract is switching between two regimes with low volatility and high volatility depending on a markov process.
🔬Design:Modeling & Simulation
📍Scope:2002 Verileri
⚙️Variables:MS GARCH · oil futures · volatility

Abstract

Oil futures prices, which have undergone major changes, maintain an important research topic for academics. Oil prices, which tended to decline for political and economic reasons in the 1990s, fell to as low as 12 US dollars after the Asian Crisis, rising again in 2002. The oil prices, which have fallen again after the 2008 crisis, have not reached the level of 100 US dollars again. This study explains the volatility of petroleum futures contracts as low and high volatility in two regimes by the Markov Regime Switching GARCH model. In the study based on 7077 observations in a long sample period from January 1990 to October 2017, the transition probabilities and durations between two different volatility regimes of oil futures prices are explained. The volatility of the oil futures contract is switching between two regimes with low volatility and high volatility depending on a markov process.

Özet

Büyük değişimler geçiren vadeli petrol fiyatları, akademisyenler için önemli bir araştırma konusu olmaya devam etmektedir. Politik ve ekonomik nedenlerle 1990’lı yıllarda düşme eğiliminde olan petrol fiyatları, Asya Krizi sonrası 12 ABD dolarına kadar düşmüş, 2002 itibariyle tekrar yükselmiştir. 2008 krizinden sonar tekrar düşme eğilimine giren petrol fiyatları, bir daha 100 ABD doları seviyesine ulaşmamıştır. Bu çalışma, Petrol vadeli işlem sözleşmelerinin volatilitesini düşük ve yüksek volatilite olarak iki rejimli bir Markov Rejim Değişim GARCH modeli ile açıklamaktadır. yapıda açıklayan çalışmada. Ocak 1990-Ekim 2017 dönemindeki 7077 gözlemlik uzun bir örneklem dönemini ele alan çalışmada, iki farklı volatilite rejimi arasındaki geçiş olasılıkları ve durasyonları açıklanmıştır. Petrol vadeli işlem sözleşmesinin volatilitesi, düşük ve yüksek volatiliteye sahip iki rejim arasında bir markov sürecine bağlı olarak geçiş yapmaktadır.

🔖

Cite This Article

KOY, A. (2018). REGIME RELATED VOLATILITY IN OIL FUTURES PRICES. Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, Cilt: 15 - Sayı: 41, 175–184. https://ajindex.com/articles/267348

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (15)

  1. Agnolucci, P. (2009). Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models. Energy Economics, 31, 316-321.
  2. Anderson, H.M., K. Nam and Vahid, F. (1999). Asymmetric nonlinear smooth transition GARCH models. in P. Rothman (ed.), Nonlinear Time Series Analysis of Economic and Financial Data, Boston: Kluwer, 191–207.
  3. Baillie, R.T., Bollerslevi T. and Mikkelsen, H.-O. (1996). Fractionally integrated generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 74, 3–30.
  4. Baum, C. C. and Zerilli, P. (2016). Jumps and stochastic volatility in crude oil futures prices using conditional moments of integrated volatility. Energy Economics, 53, 175-181.
  5. Bildirici, M., Aykaç Alp, E.i Ersin, Ö. Ö. and Bozoklui Ü. (2010). İktisatta Kullanılan Doğrusal Olmayan Zaman Serisi Yöntemleri. İstanbul,
  6. Türkmen Kitabevi.
  7. Bodie, Z. and Rosansky V. I. (1980) Risk and Return in Commodity Futures. Financial Analysts Journal, 36(3) 27-39.
  8. Cai, J., (1994). A Markov model of switching-regime ARCH. Journal of Business & Economic Statistics, 12, 309–16.
  9. Chevallier, J. (2013). Price relationships in crude oil futures: new evidence from CFTC disaggregated data. Environmental Economics and Policy Studies, 15(2), 133–170.
  10. Dueker, M. J. (1997) Markov Switching in GARCH Processes and Mean-Reverting Stock Market Volatility. Journal of Business and Economic Studies, 15(1), 26-34.
  11. Dusak, K. (1973). Futures Trading and Investor Returns: An Investigation of Commodity Market Risk Premiums. Journal of Political Economy, 81(6), 1387-1406. Engle,R.F., Lilien, D. M. and Robins, R. P. (1987). Estimating time varying risk premia in the term structure: the ARCH-M model. Econometrica, 55, 391–407.
  12. Fong, W. M. and See, K. H. (2002). A Markov switching model of the conditional volatility of crude oil futures prices. Energy Economics, 24(1):71–95.
  13. Fornari, F. and A. Mele (1997). Sign and volatility switching ARCH models: theory and applications to international stock markets. Journal of Applied Econometrics, 12, 49–65.
  14. Franses, P. H. and Dijk D. (2000). Nonlinear Time Series Models in Empirical Finance. Cambridge Universtiy Press. Gonz´alez-Rivera, G., (1998). Smooth transition GARCH models. Studies in Nonlinear Dynamics and Econometrics, 3, 61–78
  15. Glosten, L.R., R. Jagannathan and D.E. Runkle, (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance, 48, 1779–801 G