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Analyzing volatility transmission using group transfer entropy

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  • Dimpfl, Thomas
  • Peter, Franziska J.

Abstract

We analyze the transmission of volatility between the oil, stock, gold, and currency markets using transfer entropy. Our approach, which we denote by group transfer entropy, measures the overall sensitivity of a process to lagged realizations of a group of other processes. We supplement our measure by a suitable block bootstrap approach which allows to conduct inference. Our empirical analysis uses daily data of OVX, VIX, GVZ, and EVZ from 2008 to 2017. The results show that oil and stock market volatility are the most affected by past volatility changes in the other markets, which highlights the importance for investors to hedge against this predictable risk transmission. Furthermore, we show that group transfer entropy can unveil nonlinear dynamics beyond the standard vector autoregressive methodology and provides a useful basis for forecast averaging.

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  • Dimpfl, Thomas & Peter, Franziska J., 2018. "Analyzing volatility transmission using group transfer entropy," Energy Economics, Elsevier, vol. 75(C), pages 368-376.
    • Handle: RePEc:eee:eneeco:v:75:y:2018:i:c:p:368-376
    DOI: 10.1016/j.eneco.2018.08.008
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    as
    1. Adrian Fernandez-Perez & Bart Frijns & Alireza Tourani-Rad, 2017. "Precious metals, oil and the exchange rate: contemporaneous spillovers," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3863-3879, August.
    2. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael & Thompson, Mark A., 2010. "Precious metals-exchange rate volatility transmissions and hedging strategies," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 633-647, October.
    3. repec:dau:papers:123456789/14980 is not listed on IDEAS
    4. He, Jiayi & Shang, Pengjian, 2017. "Comparison of transfer entropy methods for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 772-785.
    5. Creti, Anna & Joëts, Marc & Mignon, Valérie, 2013. "On the links between stock and commodity markets' volatility," Energy Economics, Elsevier, vol. 37(C), pages 16-28.
    6. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
    7. Junsoo Lee & Mark C. Strazicich, 2003. "Minimum Lagrange Multiplier Unit Root Test with Two Structural Breaks," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1082-1089, November.
    8. Okyu Kwon & Jae-Suk Yang, 2008. "Information flow between stock indices," Papers 0802.1747, arXiv.org.
    9. Clemon, Robert T & Winkler, Robert L, 1986. "Combining Economic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 39-46, January.
    10. Chunxia, Yang & Xueshuai, Zhu & Luoluo, Jiang & Sen, Hu & He, Li, 2016. "Study on the contagion among American industries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 601-612.
    11. Malik, Farooq & Ewing, Bradley T., 2009. "Volatility transmission between oil prices and equity sector returns," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 95-100, June.
    12. Bašta, Milan & Molnár, Peter, 2018. "Oil market volatility and stock market volatility," Finance Research Letters, Elsevier, vol. 26(C), pages 204-214.
    13. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
    14. David E. Rapach & Jack K. Strauss, 2008. "Forecasting US employment growth using forecast combining methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 75-93.
    15. Kwon, Okyu & Yang, Jae-Suk, 2008. "Information flow between composite stock index and individual stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2851-2856.
    16. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    17. Brian J. Henderson & Neil D. Pearson & Li Wang, 2015. "Editor's Choice New Evidence on the Financialization of Commodity Markets," Review of Financial Studies, Society for Financial Studies, vol. 28(5), pages 1285-1311.
    18. Arouri, Mohamed El Hedi & Lahiani, Amine & Nguyen, Duc Khuong, 2011. "Return and volatility transmission between world oil prices and stock markets of the GCC countries," Economic Modelling, Elsevier, vol. 28(4), pages 1815-1825, July.
    19. Ihsan Ullah Badshah & Bart Frijns & Alireza Tourani‐Rad, 2013. "Contemporaneous Spill‐Over Among Equity, Gold, and Exchange Rate Implied Volatility Indices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(6), pages 555-572, June.
    20. Sari, Ramazan & Soytas, Ugur & Hacihasanoglu, Erk, 2011. "Do global risk perceptions influence world oil prices?," Energy Economics, Elsevier, vol. 33(3), pages 515-524, May.
    21. Dimpfl, Thomas & Peter, Franziska J., 2014. "The impact of the financial crisis on transatlantic information flows: An intraday analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 1-13.
    22. Chanont Banternghansa & Michael W. McCracken, 2011. "Real-time forecast averaging with ALFRED," Review, Federal Reserve Bank of St. Louis, vol. 93(Jan), pages 49-66.
    23. Teng, Yue & Shang, Pengjian, 2017. "Transfer entropy coefficient: Quantifying level of information flow between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 60-70.
    24. Liu, Ming-Lei & Ji, Qiang & Fan, Ying, 2013. "How does oil market uncertainty interact with other markets? An empirical analysis of implied volatility index," Energy, Elsevier, vol. 55(C), pages 860-868.
    25. Leonidas Sandoval Junior & Asher Mullokandov & Dror Y. Kenett, 2015. "Dependency Relations among International Stock Market Indices," JRFM, MDPI, vol. 8(2), pages 1-39, May.
    26. Jeremy Smith & Kenneth F. Wallis, 2009. "A Simple Explanation of the Forecast Combination Puzzle," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 331-355, June.
    27. Maghyereh, Aktham I. & Awartani, Basel & Tziogkidis, Panagiotis, 2017. "Volatility spillovers and cross-hedging between gold, oil and equities: Evidence from the Gulf Cooperation Council countries," Energy Economics, Elsevier, vol. 68(C), pages 440-453.
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    More about this item

    Keywords

    Transfer entropy; Volatility transmission; Oil market; Forecast averaging;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • G19 - Financial Economics - - General Financial Markets - - - Other

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