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Markov Switching Autoregressive Model for WTI Crude Oil Price

Year 2018, Volume: 14 Issue: 28, 45 - 56, 31.07.2018

Abstract

In this study, we aimed to test the nonlinear structure of crude oil prices with Markov Regime Switching Autoregressive

Models. In the study of weekly prices covering the period from May 06, 1990 to April 11, 2018, a two-regime Markov

switching model was applied. In the case of two regimes, we proved the that the probability the process will be in regime

1 or 2 is given by steady-state probabilities. As a result, it can be seen that the predictions made by the Markov switching

autoregressive model were succesful.

References

  • Ahdikari, R. & Agrawal, R. K. (2013). An introductory study on time series modeling and forecasting. Lambert Academic Publishing. Retrieved from: https://arxiv.org/ftp/arxiv/ papers/1302/1302.6613.pdf
  • Ailliot, P. & Monbet, V. (2012). Markov-switching autoregressive models for wind time series. Environmental Modelling and Software, 30, 92‒101. https://doi.org/10.1016/j. envsoft.2011.10.011
  • Barunik J. & Malinska, B. (2015). Forecasting the term structure of crude oil futures price with neural networks. Elsevier, 2‒26. Retrieved from: https://arxiv.org/pdf/1504.04819.pdf
  • Bayat, T., Kayhan, S. ve Koçyiğit, A. (2013). Türkiye’de işsizliğin asimetrik davranışının Rejim Değişim Modeliyle incelenmesi. Business and Economics Research Journal, 4(2), 79‒90. http://docplayer.biz.tr/5976565-Turkiye-de-issizligin-asimetrik-davranisinin-rejim-degisimmodeliyle-incelenmesi.html adresinden edinilmiştir.
  • Chen, S. S. (2014). Forecasting crude oil price movements with oil - sensitive stocks. Economic Inquiry, 52(2), 830‒844. https://doi.org/10.1111/ecin.12053
  • Çinko, M. (2006). İstanbul Menkul Kıymetler Borsası 100 Endeksinin doğrusallık testi. Ekonometri ve İstatistik e-Dergisi, 3, 23‒31. http://eidergisi.istanbul.edu.tr/sayi3/iueis3m2.pdf adresinden edinilmiştir.
  • Engel, C. & Rogers, J. H. (2006). The U.S. current account deficit and the expected share of world output. Journal of Monetary Economics, 53(5), 1063‒1093. Retrieved from: https://www.ssc.wisc.edu/~cengel/PublishedPapers/CarnegieRochesterCAcct.pdf
  • Fattouh, B. (2005). Capital mobility and sustainability evidence from U.S. current account data. Empirical Economics, 30(1), 245‒253. https://doi.org/10.1007/s00181-004-0232-6
  • Hamilton, J. D. (1983). Oil and the macro economy since World War II. The Journal of Political Economy, 91(2), 228–248. http://www.jstor.org/stable/1832055
  • Hamilton, J. D. (1989). A new approach to the economic analysis of non-stationary time series and the business cycle. Econometrica, 57(2), 357‒384. https://doi.org/10.2307/1912559
  • Hamilton, J. D. (2005). Regime Switching Models. Retrieved from: http://econweb.ucsd.edu/~jhamilton/palgrav1.pdf
  • Hamilton, J. D. (2009). Causes and consequences of the oil shock of 2007–08. The National Bureau of Economic Research, 40(1), 215‒283. https://doi.org/10.3386/w15002 http://lipas.uwasa.fi/~bepa/Markov.pdf
  • Huang, S., An, H., Wen, S. & An, F. (2017). Revisiting driving factors of oil price shocks across time scales. Energy, 139(C), 617–629. https://dx.doi.org/10.1016/j.energy.2017.07.158
  • Karahan H. (2014). Petrol piyasalarında neler oluyor? SETA Perspektif, 79. https://paperzz.com/doc/5060375/petrol-piyasalar%C4%B1nda-neler-oluyor%3F
  • King K., Deng A. & Metz D. (2012). An econometric analysis of oil price movements: the role of political events and economic news, financial trading, and market fundamentals. Bates White Economic Consulting. Retrieved from: https://www.bateswhite.com/assets/htmldocuments/media.768.pdf
  • Kuan, C. M. (2002). Lecture on the Markov Switching Model. Retrieved from: http://homepage.ntu.edu.tw/~ckuan/pdf/Lec-Markov_note.pdf
  • Middendorf, T. & Schmidt, T. (2004). Characterizing movements of the U.S. current accountdeficit. RWI Discussion Paper, 24. http://dx.doi.org/10.2139/ssrn.628461
  • Mir, A. M., Osborn, D. R. & Lombardi, M. J. (2005). The effects of seasonal adjustment on the properties of business cycle regimes. Journal of Applied Econometrics, 23(2), 257‒278. https://doi.org/10.1002/jae.980
  • Pape, B. (2005). Regime switching models. Lecture Notes, 31‒43. Retrieved from: http://lipas.uwasa.fi/~bepa/Markov.pdf
  • Psaradakis, Z. & Spagnolo, N. (2003). On the determination of the number of regimes in Markov-Switching Autoregressive Models. Journal of Time Series Analysis, 24(2), 237‒252. https://doi.org/10.1111/1467-9892.00305
  • Skalin, J. & Trasvirta, T. (2000). Modelling asymmetries and moving equilibria in unemployment rates. Macroeconomics Dynamics, 6(2), 202‒241. https://doi.org/10.1017/S1365100502031024
  • Solak, A. O. (2012). Petrol fiyatlarını belirleyici faktörler. International Journal of Alanya Faculty of Business, 4(2), 117‒124. http://dergipark.gov.tr/download/article-file/201632
  • Sümer, K. ve Hepsağ, A. (2007). Finansal varlık modelleri çerçevesinde piyasa risklerinin hesaplanması: parametrik olmayan yaklaşım, Bankacılar Dergisi, 62, 3‒24. https://www.tbb.org.tr/Dosyalar/Arastirma_ve_Raporlar/finansalvarlik.pdf adresinden edinilmiştir.
  • Ural, M. (2016). The impact of the global financial crisis on crude oil price volatility. Yönetim ve Ekonomi Araştırmaları Dergisi, 14(2), 64‒76. http://dx.doi.org/10.11611/JMER810
  • Wong, V. S. & El Massah, S. (2017). Recent evidence on the oil price shocks on gulf corporation council stock markets. International Journal of the Economics of Business, 1–16, https://doi.org/10.1080/13571516.2017.1379216
  • Yin, X., Peng, J. & Tang, T. (2018). Improving the forecasting accuracy of crude oil prices. Sustainability, 10(2), 454. https://doi.org/10.3390/su10020454

WTI (West Texas Intermediate) Ham Petrol Fiyatları için Markov Rejim Değişim Otoregresif Modeli

Year 2018, Volume: 14 Issue: 28, 45 - 56, 31.07.2018

Abstract

Bu araştırma ile ham petrol fiyatının doğrusal olmayan yapısını Markov
Rejim Değişim Otoregresif Modelleriyle test etmek amaçlanmıştır. 06 Mayıs
1990'dan 11 Nisan 2018'e kadar olan dönemi kapsayan, haftalık fiyatların
kullanıldığı çalışmada, iki rejimli Markov Switching Modeli uygulanmıştır. İki
rejim durumunda sürecin rejim 1 veya rejim 2'de olacağı kararlı yapı
olasılıkları ile kanıtlanmıştır. Sonuç olarak ise, Markov Rejim Değişim Modeli
ile yapılan öngörünün başarılı sonuçlar verdiği görülmüştür.

References

  • Ahdikari, R. & Agrawal, R. K. (2013). An introductory study on time series modeling and forecasting. Lambert Academic Publishing. Retrieved from: https://arxiv.org/ftp/arxiv/ papers/1302/1302.6613.pdf
  • Ailliot, P. & Monbet, V. (2012). Markov-switching autoregressive models for wind time series. Environmental Modelling and Software, 30, 92‒101. https://doi.org/10.1016/j. envsoft.2011.10.011
  • Barunik J. & Malinska, B. (2015). Forecasting the term structure of crude oil futures price with neural networks. Elsevier, 2‒26. Retrieved from: https://arxiv.org/pdf/1504.04819.pdf
  • Bayat, T., Kayhan, S. ve Koçyiğit, A. (2013). Türkiye’de işsizliğin asimetrik davranışının Rejim Değişim Modeliyle incelenmesi. Business and Economics Research Journal, 4(2), 79‒90. http://docplayer.biz.tr/5976565-Turkiye-de-issizligin-asimetrik-davranisinin-rejim-degisimmodeliyle-incelenmesi.html adresinden edinilmiştir.
  • Chen, S. S. (2014). Forecasting crude oil price movements with oil - sensitive stocks. Economic Inquiry, 52(2), 830‒844. https://doi.org/10.1111/ecin.12053
  • Çinko, M. (2006). İstanbul Menkul Kıymetler Borsası 100 Endeksinin doğrusallık testi. Ekonometri ve İstatistik e-Dergisi, 3, 23‒31. http://eidergisi.istanbul.edu.tr/sayi3/iueis3m2.pdf adresinden edinilmiştir.
  • Engel, C. & Rogers, J. H. (2006). The U.S. current account deficit and the expected share of world output. Journal of Monetary Economics, 53(5), 1063‒1093. Retrieved from: https://www.ssc.wisc.edu/~cengel/PublishedPapers/CarnegieRochesterCAcct.pdf
  • Fattouh, B. (2005). Capital mobility and sustainability evidence from U.S. current account data. Empirical Economics, 30(1), 245‒253. https://doi.org/10.1007/s00181-004-0232-6
  • Hamilton, J. D. (1983). Oil and the macro economy since World War II. The Journal of Political Economy, 91(2), 228–248. http://www.jstor.org/stable/1832055
  • Hamilton, J. D. (1989). A new approach to the economic analysis of non-stationary time series and the business cycle. Econometrica, 57(2), 357‒384. https://doi.org/10.2307/1912559
  • Hamilton, J. D. (2005). Regime Switching Models. Retrieved from: http://econweb.ucsd.edu/~jhamilton/palgrav1.pdf
  • Hamilton, J. D. (2009). Causes and consequences of the oil shock of 2007–08. The National Bureau of Economic Research, 40(1), 215‒283. https://doi.org/10.3386/w15002 http://lipas.uwasa.fi/~bepa/Markov.pdf
  • Huang, S., An, H., Wen, S. & An, F. (2017). Revisiting driving factors of oil price shocks across time scales. Energy, 139(C), 617–629. https://dx.doi.org/10.1016/j.energy.2017.07.158
  • Karahan H. (2014). Petrol piyasalarında neler oluyor? SETA Perspektif, 79. https://paperzz.com/doc/5060375/petrol-piyasalar%C4%B1nda-neler-oluyor%3F
  • King K., Deng A. & Metz D. (2012). An econometric analysis of oil price movements: the role of political events and economic news, financial trading, and market fundamentals. Bates White Economic Consulting. Retrieved from: https://www.bateswhite.com/assets/htmldocuments/media.768.pdf
  • Kuan, C. M. (2002). Lecture on the Markov Switching Model. Retrieved from: http://homepage.ntu.edu.tw/~ckuan/pdf/Lec-Markov_note.pdf
  • Middendorf, T. & Schmidt, T. (2004). Characterizing movements of the U.S. current accountdeficit. RWI Discussion Paper, 24. http://dx.doi.org/10.2139/ssrn.628461
  • Mir, A. M., Osborn, D. R. & Lombardi, M. J. (2005). The effects of seasonal adjustment on the properties of business cycle regimes. Journal of Applied Econometrics, 23(2), 257‒278. https://doi.org/10.1002/jae.980
  • Pape, B. (2005). Regime switching models. Lecture Notes, 31‒43. Retrieved from: http://lipas.uwasa.fi/~bepa/Markov.pdf
  • Psaradakis, Z. & Spagnolo, N. (2003). On the determination of the number of regimes in Markov-Switching Autoregressive Models. Journal of Time Series Analysis, 24(2), 237‒252. https://doi.org/10.1111/1467-9892.00305
  • Skalin, J. & Trasvirta, T. (2000). Modelling asymmetries and moving equilibria in unemployment rates. Macroeconomics Dynamics, 6(2), 202‒241. https://doi.org/10.1017/S1365100502031024
  • Solak, A. O. (2012). Petrol fiyatlarını belirleyici faktörler. International Journal of Alanya Faculty of Business, 4(2), 117‒124. http://dergipark.gov.tr/download/article-file/201632
  • Sümer, K. ve Hepsağ, A. (2007). Finansal varlık modelleri çerçevesinde piyasa risklerinin hesaplanması: parametrik olmayan yaklaşım, Bankacılar Dergisi, 62, 3‒24. https://www.tbb.org.tr/Dosyalar/Arastirma_ve_Raporlar/finansalvarlik.pdf adresinden edinilmiştir.
  • Ural, M. (2016). The impact of the global financial crisis on crude oil price volatility. Yönetim ve Ekonomi Araştırmaları Dergisi, 14(2), 64‒76. http://dx.doi.org/10.11611/JMER810
  • Wong, V. S. & El Massah, S. (2017). Recent evidence on the oil price shocks on gulf corporation council stock markets. International Journal of the Economics of Business, 1–16, https://doi.org/10.1080/13571516.2017.1379216
  • Yin, X., Peng, J. & Tang, T. (2018). Improving the forecasting accuracy of crude oil prices. Sustainability, 10(2), 454. https://doi.org/10.3390/su10020454
There are 26 citations in total.

Details

Primary Language English
Journal Section Makaleler
Authors

Çiğdem Yılmaz

Nilgün Çil

Publication Date July 31, 2018
Published in Issue Year 2018 Volume: 14 Issue: 28

Cite

APA Yılmaz, Ç., & Çil, N. (2018). Markov Switching Autoregressive Model for WTI Crude Oil Price. Istanbul University Econometrics and Statistics E-Journal, 14(28), 45-56.
AMA Yılmaz Ç, Çil N. Markov Switching Autoregressive Model for WTI Crude Oil Price. Istanbul University Econometrics and Statistics e-Journal. July 2018;14(28):45-56.
Chicago Yılmaz, Çiğdem, and Nilgün Çil. “Markov Switching Autoregressive Model for WTI Crude Oil Price”. Istanbul University Econometrics and Statistics E-Journal 14, no. 28 (July 2018): 45-56.
EndNote Yılmaz Ç, Çil N (July 1, 2018) Markov Switching Autoregressive Model for WTI Crude Oil Price. Istanbul University Econometrics and Statistics e-Journal 14 28 45–56.
IEEE Ç. Yılmaz and N. Çil, “Markov Switching Autoregressive Model for WTI Crude Oil Price”, Istanbul University Econometrics and Statistics e-Journal, vol. 14, no. 28, pp. 45–56, 2018.
ISNAD Yılmaz, Çiğdem - Çil, Nilgün. “Markov Switching Autoregressive Model for WTI Crude Oil Price”. Istanbul University Econometrics and Statistics e-Journal 14/28 (July 2018), 45-56.
JAMA Yılmaz Ç, Çil N. Markov Switching Autoregressive Model for WTI Crude Oil Price. Istanbul University Econometrics and Statistics e-Journal. 2018;14:45–56.
MLA Yılmaz, Çiğdem and Nilgün Çil. “Markov Switching Autoregressive Model for WTI Crude Oil Price”. Istanbul University Econometrics and Statistics E-Journal, vol. 14, no. 28, 2018, pp. 45-56.
Vancouver Yılmaz Ç, Çil N. Markov Switching Autoregressive Model for WTI Crude Oil Price. Istanbul University Econometrics and Statistics e-Journal. 2018;14(28):45-56.