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Structural changes and volatility transmission in crude oil markets

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  • Kang, Sang Hoon
  • Cheong, Chongcheul
  • Yoon, Seong-Min

Abstract

This study examines the influence of structural changes in volatility on the transmission of information in two crude oil prices. In an effort to assess the impact of these structural changes, we first identify the time points at which structural changes in volatility occurred using the ICSS algorithm, and then incorporate this information into our volatility modeling. From the estimation results using a bi-variate GARCH framework with and without structural change dummies, we find that the degree of persistence of volatility can be reduced via the incorporation of these structural changes in the volatility model. In this direction, we conclude that ignoring structural changes may distort the direction of information inflow and volatility transmission between crude oil markets.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 390 (2011)
Issue (Month): 23 ()
Pages: 4317-4324

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Handle: RePEc:eee:phsmap:v:390:y:2011:i:23:p:4317-4324

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: ICSS algorithm; Information transmission; Long memory; Persistence; Spillover effect;

References

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Citations

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Cited by:
  1. Delavari, Majid & Gandali Alikhani, Nadiya & Naderi, Esmaeil, 2013. "Does long memory matter in forecasting oil price volatility?," MPRA Paper 46356, University Library of Munich, Germany.
  2. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "How do OPEC news and structural breaks impact returns and volatility in crude oil markets? Further evidence from a long memory process," Energy Economics, Elsevier, vol. 42(C), pages 343-354.
  3. Gordon J. Ross, 2012. "Modeling Financial Volatility in the Presence of Abrupt Changes," Papers 1212.6016, arXiv.org.
  4. Ross, Gordon J., 2013. "Modelling financial volatility in the presence of abrupt changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(2), pages 350-360.
  5. Amélie Charles & Olivier Darné, 2014. "Volatility persistence in crude oil markets," Post-Print hal-00940312, HAL.
  6. Delavari, Majid & Gandali Alikhani, Nadiya, 2012. "The Effect of Crude Oil Price on the Methanol price," MPRA Paper 49727, University Library of Munich, Germany.
  7. Delavari, Majid & Gandali Alikhani, Nadiya, 2013. "The Dynamic Effects of Crude Oil and Natural Gas Prices on Iran's Methanol," MPRA Paper 49733, University Library of Munich, Germany.
  8. Komijani, Akbar & Naderi, Esmaeil & Gandali Alikhani, Nadiya, 2013. "A Hybrid Approach for Forecasting of Oil Prices Volatility," MPRA Paper 44654, University Library of Munich, Germany.
  9. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
  10. Delavari, Majid & Gandali Alikhani, Nadiya & Naderi, Esmaeil, 2012. "The analyses of Crude Oil and Natural Gas Prices on Petrochemicals Products: A Case Study of IRAN's Methanol," MPRA Paper 48788, University Library of Munich, Germany.
  11. Alethea Rea & William Rea & Marco Reale & Carl Scarrott, 2012. "A comparison of Spillover Effects before, during and after the 2008 Financial Crisis," Working Papers in Economics 12/03, University of Canterbury, Department of Economics and Finance.

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