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Realized volatility transmission: The role of jumps and leverage effects

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  • Souček, Michael
  • Todorova, Neda

Abstract

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.

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  • Souček, Michael & Todorova, Neda, 2014. "Realized volatility transmission: The role of jumps and leverage effects," Economics Letters, Elsevier, vol. 122(2), pages 111-115.
    • Handle: RePEc:eee:ecolet:v:122:y:2014:i:2:p:111-115
    DOI: 10.1016/j.econlet.2013.11.007
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    Cited by:

    1. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
    2. Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    3. de Truchis, Gilles & Keddad, Benjamin, 2016. "On the risk comovements between the crude oil market and U.S. dollar exchange rates," Economic Modelling, Elsevier, vol. 52(PA), pages 206-215.
    4. Rim Ammar Lamouchi & Ruba Khalid Shira, 2023. "Heterogeneous Behavior and Volatility Transmission in the Forex Market using High-Frequency Data," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 13(3), pages 1-3.
    5. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
    6. Degiannakis, Stavros & Filis, George, 2016. "Forecasting oil price realized volatility: A new approach," MPRA Paper 69105, University Library of Munich, Germany.
    7. Ji‐Eun Choi & Dong Wan Shin, 2018. "Forecasts for leverage heterogeneous autoregressive models with jumps and other covariates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 691-704, September.
    8. Vortelinos, Dimitrios I., 2016. "Incremental information of stock indicators," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 79-97.
    9. Lahaye, Jerome & Shaw, Philip, 2014. "Can we reject linearity in an HAR-RV model for the S&P 500? Insights from a nonparametric HAR-RV," Economics Letters, Elsevier, vol. 125(1), pages 43-46.
    10. Jérôme Lahaye & Christopher Neely, 2020. "The Role of Jumps in Volatility Spillovers in Foreign Exchange Markets: Meteor Shower and Heat Waves Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 410-427, April.
    11. Christophe Boucher & Gilles de Truchis & Elena Ivona Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," Working Papers hal-04141651, HAL.
    12. Maki, Daiki & Ota, Yasushi, 2021. "Impacts of asymmetry on forecasting realized volatility in Japanese stock markets," Economic Modelling, Elsevier, vol. 101(C).
    13. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil prices," MPRA Paper 77531, University Library of Munich, Germany.
    14. Aganin, Artem, 2017. "Forecast comparison of volatility models on Russian stock market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 48, pages 63-84.
    15. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & de Gracia, Fernando Perez, 2023. "Dynamic connectedness among the implied volatilities of oil prices and financial assets: New evidence of the COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 114-123.
    16. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2016. "Evolving Fuzzy-GARCH Approach for Financial Volatility Modeling and Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 379-398, October.
    17. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
    18. Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
    19. Daiki Maki & Yasushi Ota, 2020. "The impacts of asymmetry on modeling and forecasting realized volatility in Japanese stock markets," Papers 2006.00158, arXiv.org.
    20. Libo Yin & Jing Nie & Liyan Han, 2021. "Intermediary capital risk and commodity futures volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 577-640, May.
    21. Yaxian Lu & Longguang Yang & Lihong Liu, 2019. "Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    22. Liu, Min & Lee, Chien-Chiang, 2022. "Is gold a long-run hedge, diversifier, or safe haven for oil? Empirical evidence based on DCC-MIDAS," Resources Policy, Elsevier, vol. 76(C).

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    More about this item

    Keywords

    Volatility transmission; Jumps; Leverage effects; Realized volatility;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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