IDEAS home Printed from https://ideas.repec.org/a/eee/intfin/v38y2015icp25-41.html
   My bibliography  Save this article

A cross-volatility index for hedging the country risk

Author

Listed:
  • Aboura, Sofiane
  • Chevallier, Julien

Abstract

This paper proposes a new empirical methodology for computing a cross-volatility index, coined CVIX, that characterizes the country risk understood here as the financial market risk measurement. The approach, based on the Factor DCC-model, requires to encapsulate all the sources of risk stemming from the financial markets for any given country. We provide an application to the U.S. economy by constructing an aggregate volatility index composed of implied volatility indexes characterizing the equity market, the FX market, fixed income market and the commodity market. The analysis reveals that 75% of the aggregate risk comes from the commodity market, and that the volatility index average value evolves around 22%. The CVIX provides a better hedging performance than the VVIX used as a benchmark.

Suggested Citation

  • Aboura, Sofiane & Chevallier, Julien, 2015. "A cross-volatility index for hedging the country risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 25-41.
    • Handle: RePEc:eee:intfin:v:38:y:2015:i:c:p:25-41
    DOI: 10.1016/j.intfin.2015.05.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S104244311500061X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intfin.2015.05.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(6), pages 1113-1141, December.
    2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    3. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    4. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    5. Connor, Gregory & Korajczyk, Robert A, 1993. "A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-1291, September.
    6. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    7. Andrade, Sandro C., 2009. "A model of asset pricing under country risk," Journal of International Money and Finance, Elsevier, vol. 28(4), pages 671-695, June.
    8. Saini, Krishan G. & Bates, Philip S., 1984. "A survey of the quantitative approaches to country risk analysis," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 341-356, June.
    9. Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, September.
    10. Agliardi, Elettra & Agliardi, Rossella & Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2012. "A new country risk index for emerging markets: A stochastic dominance approach," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 741-761.
    11. Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
    12. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    13. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    14. Carol Alexander, 2000. "Orthogonal Methods for Generating Large Positive Semi-Definite Covariance Matrices," ICMA Centre Discussion Papers in Finance icma-dp2000-06, Henley Business School, University of Reading.
    15. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
    16. Jonathan Eaton & Mark Gersovitz & Joseph E. Stiglitz, 1991. "The Pure Theory of Country Risk," NBER Chapters, in: International Volatility and Economic Growth: The First Ten Years of The International Seminar on Macroeconomics, pages 391-435, National Bureau of Economic Research, Inc.
    17. Kun Zhang & Laiwan Chan, 2009. "Efficient factor GARCH models and factor-DCC models," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 71-91.
    18. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    19. Kabir Hassan, M. & Maroney, Neal C. & Monir El-Sady, Hassan & Telfah, Ahmad, 2003. "Country risk and stock market volatility, predictability, and diversification in the Middle East and Africa," Economic Systems, Elsevier, vol. 27(1), pages 63-82, March.
    20. Tibor F. Liska, 2007. "The Liska model," Society and Economy, Akadémiai Kiadó, Hungary, vol. 29(3), pages 363-381, December.
    21. Cosset, Jean-Claude & Siskos, Yannis & Zopounidis, Constantin, 1992. "Evaluating country risk: A decision support approach," Global Finance Journal, Elsevier, vol. 3(1), pages 79-95.
    22. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    23. Liu, Tengdong & Hammoudeh, Shawkat & Thompson, Mark A., 2013. "A momentum threshold model of stock prices and country risk ratings: Evidence from BRICS countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 99-112.
    24. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2010. "Improved penalization for determining the number of factors in approximate factor models," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1806-1813, December.
    25. Oetzel, Jennifer M. & Bettis, Richard A. & Zenner, Marc, 2001. "Country risk measures: how risky are they?," Journal of World Business, Elsevier, vol. 36(2), pages 128-145, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ching-Chun Wei, 2016. "Empirical Analysis of ¡°Volatility Surprise¡± between Dollar Exchange Rate and CRB Commodity Future Markets," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(9), pages 117-126, September.
    2. Cañón Salazar Carlos Iván & Gallón Santiago & Olivar Santiago, 2016. "Functional Systemic Risk, Complementarities and Early Warnings," Working Papers 2016-12, Banco de México.
    3. Guido Bonatti & Andrea Ciacci & Enrico Ivaldi, 2021. "Different Measures of Country Risk: An Application to European Countries," JRFM, MDPI, vol. 14(1), pages 1-16, January.
    4. Kilic, Erdem, 2017. "Contagion effects of U.S. Dollar and Chinese Yuan in forward and spot foreign exchange markets," Economic Modelling, Elsevier, vol. 62(C), pages 51-67.

    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. Aboura, Sofiane & Chevallier, Julien, 2015. "Geographical diversification with a World Volatility Index," Journal of Multinational Financial Management, Elsevier, vol. 30(C), pages 62-82.
    2. Aboura, Sofiane & Chevallier, Julien, 2015. "Cross-market volatility index with Factor-DCC," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 132-140.
    3. Aboura, Sofiane & Chevallier, Julien, 2014. "Cross-market index with Factor-DCC," Economic Modelling, Elsevier, vol. 40(C), pages 158-166.
    4. Aboura, Sofiane & Chevallier, Julien, 2017. "A new weighting-scheme for equity indexes," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 159-175.
    5. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
    6. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    7. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    8. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
    9. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
    10. Sofiane Aboura & Julien Chevallier, 2014. "The cross-market index for volatility surprise," Journal of Asset Management, Palgrave Macmillan, vol. 15(1), pages 7-23, February.
    11. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2015. "Dynamic factor models with infinite-dimensional factor spaces: One-sided representations," Journal of Econometrics, Elsevier, vol. 185(2), pages 359-371.
    12. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    13. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
    14. Mao Takongmo, Charles Olivier & Stevanovic, Dalibor, 2015. "Selection Of The Number Of Factors In Presence Of Structural Instability: A Monte Carlo Study," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 177-233, Mars-Juin.
    15. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2017. "Dynamic factor models with infinite-dimensional factor space: Asymptotic analysis," Journal of Econometrics, Elsevier, vol. 199(1), pages 74-92.
    16. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    17. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    18. Forni, Mario & Cavicchioli, Maddalena & Lippi, Marco & Zaffaroni, Paolo, 2016. "Eigenvalue Ratio Estimators for the Number of Common Factors," CEPR Discussion Papers 11440, C.E.P.R. Discussion Papers.
    19. Forni, Mario & Gambetti, Luca, 2010. "The dynamic effects of monetary policy: A structural factor model approach," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 203-216, March.
    20. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.

    More about this item

    Keywords

    Cross-volatility index; Country risk; Factor-DCC; PCA; LASSO;
    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
    • G01 - Financial Economics - - General - - - Financial Crises
    • F15 - International Economics - - Trade - - - Economic Integration

    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:eee:intfin:v:38:y:2015:i:c:p:25-41. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/intfin .

    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.