[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/ibn/ibrjnl/v11y2018i12p18-25.html
   My bibliography  Save this article

An Investigation of the Predictive Speed of the UK VIX for the Downside Risk in European Equity Markets

Author

Listed:
  • Chikashi Tsuji
Abstract
Using the time-series data of UK volatility index (VIX) and other four European equity indices of France, Italy, Spain, and Portugal, and applying quantile regressions, this study investigates the predictive power and predictive speed of the UK VIX for the future sharp price drops in other four European equity markets. As a result, our empirical examinations derive the following findings. (1) First, we clarify that the increases of the UK VIX have statistically significant predictive power for the downside risk in other four European equity markets. (2) Second, our empirical results reveal that the two to four days before, the changes in the UK VIX can forecast the downside risk in other four European equity markets.

Suggested Citation

  • Chikashi Tsuji, 2018. "An Investigation of the Predictive Speed of the UK VIX for the Downside Risk in European Equity Markets," International Business Research, Canadian Center of Science and Education, vol. 11(12), pages 18-25, December.
    • Handle: RePEc:ibn:ibrjnl:v:11:y:2018:i:12:p:18-25
    as

    Download full text from publisher

    File URL: http://www.ccsenet.org/journal/index.php/ibr/article/download/0/0/37312/37561
    Download Restriction: no
    File URL: http://www.ccsenet.org/journal/index.php/ibr/article/view/0/37312
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chikashi Tsuji, 2016. "Does the fear gauge predict downside risk more accurately than econometric models? Evidence from the US stock market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1220711-122, December.
    2. Chuliá, Helena & Fernández, Julián & Uribe, Jorge M., 2018. "Currency downside risk, liquidity, and financial stability," Journal of International Money and Finance, Elsevier, vol. 89(C), pages 83-102.
    3. Chikashi Tsuji, 2017. "Does the CBOE Volatility Index Predict Downside Risk at the Tokyo Stock Exchange?," International Business Research, Canadian Center of Science and Education, vol. 10(3), pages 1-7, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mikhail Stolbov & Maria Shchepeleva, 2022. "In Search of Global Determinants of National Credit-to-GDP Gaps," Risks, MDPI, vol. 10(12), pages 1-22, December.
    2. Wang, Mengjiao & Liu, Jianxu & Yang, Bing, 2024. "Does the strength of the US dollar affect the interdependence among currency exchange rates of RCEP and CPTPP countries?," Finance Research Letters, Elsevier, vol. 62(PA).
    3. Chikashi Tsuji, 2017. "Does the CBOE Volatility Index Predict Downside Risk at the Tokyo Stock Exchange?," International Business Research, Canadian Center of Science and Education, vol. 10(3), pages 1-7, March.
    4. Tsuji, Chikashi, 2018. "New DCC analyses of return transmission, volatility spillovers, and optimal hedging among oil futures and oil equities in oil-producing countries," Applied Energy, Elsevier, vol. 229(C), pages 1202-1217.
    5. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    6. Yang, Cai & Wang, Xinyi & Gao, Wang, 2022. "Is Bitcoin a better hedging and safe-haven investment than traditional assets against currencies? Evidence from the time-frequency domain approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Jose E. Gomez-Gonzalez & Jorge M. Uribe & Oscar M. Valencia, 2023. "Risk spillovers between global corporations and Latin American sovereigns: global factors matter," Applied Economics, Taylor & Francis Journals, vol. 55(13), pages 1477-1496, March.
    8. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
    9. Agudze, Komla & Ibhagui, Oyakhilome, 2020. "Oil Price Dynamics and Currency-Hedging Behavior," MPRA Paper 100949, University Library of Munich, Germany.
    10. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    11. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    12. Tissaoui, Kais & Zaghdoudi, Taha, 2021. "Dynamic connectedness between the U.S. financial market and Euro-Asian financial markets: Testing transmission of uncertainty through spatial regressions models," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 481-492.
    13. Tissaoui, Kais, 2019. "Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 232-249.
    14. Tsuji, Chikashi, 2018. "Return transmission and asymmetric volatility spillovers between oil futures and oil equities: New DCC-MEGARCH analyses," Economic Modelling, Elsevier, vol. 74(C), pages 167-185.

    More about this item

    Keywords

    European equity markets; downside risk; quantile regression; VIX;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ibrjnl:v:11:y:2018:i:12:p:18-25. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.