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Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market

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  • Pesaran, M.H.

Abstract

Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investi- gate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.

Suggested Citation

  • Pesaran, M.H., 2010. "Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market," Cambridge Working Papers in Economics 1025, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1025
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    Citations

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    Cited by:

    1. Sunil S. Poshakwale & Anandadeep Mandal, 2017. "Sources of time varying return comovements during different economic regimes: evidence from the emerging Indian equity market," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 859-892, May.
    2. Pesaran, M. Hashem, 2010. "Predictability of Asset Returns and the Efficient Market Hypothesis," IZA Discussion Papers 5037, Institute of Labor Economics (IZA).
    3. Bailey, Natalia & Pesaran, M. Hashem & Smith, L. Vanessa, 2019. "A multiple testing approach to the regularisation of large sample correlation matrices," Journal of Econometrics, Elsevier, vol. 208(2), pages 507-534.
    4. Narayan, S. & Sriananthakumar, S. & Islam, S.Z., 2014. "Stock market integration of emerging Asian economies: Patterns and causes," Economic Modelling, Elsevier, vol. 39(C), pages 19-31.
    5. Maghyereh, Aktham I. & Awartani, Basel & Hilu, Khalil Al, 2015. "Dynamic transmissions between the U.S. and equity markets in the MENA countries: New evidence from pre- and post-global financial crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 123-138.
    6. Thomas Dimpfl & Robert C. Jung, 2012. "Financial market spillovers around the globe," Applied Financial Economics, Taylor & Francis Journals, vol. 22(1), pages 45-57, January.
    7. Beg, A.B.M. Rabiul Alam & Anwar, Sajid, 2012. "Sources of volatility persistence: A case study of the U.K. pound/U.S. dollar exchange rate returns," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 165-184.
    8. Mohammad A. H. PRADHAN & Gias Uddin KHAN, 2015. "Role of Remittance for Improving Quality of Life: Evidence from Bangladesh," Turkish Economic Review, KSP Journals, vol. 2(3), pages 160-168, September.
    9. Katherine Uylangco & Siqiwen Li, 2016. "An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 699-718, November.
    10. Andrew S. Duncan & Alain Kabundi, 2014. "Global Financial Crises and Time-Varying Volatility Comovement in World Equity Markets," South African Journal of Economics, Economic Society of South Africa, vol. 82(4), pages 531-550, December.
    11. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
    12. Naseri, Marjan & Masih, Mansur, 2014. "Integration and Comovement of Developed and Emerging Islamic Stock Markets: A Case Study of Malaysia," MPRA Paper 58799, University Library of Munich, Germany.
    13. Rainer Jobst & Daniel Rösch & Harald Scheule & Martin Schmelzle, 2015. "A Simple Econometric Approach for Modeling Stress Event Intensities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 300-320, April.
    14. Gatfaoui, Hayette, 2013. "Translating financial integration into correlation risk: A weekly reporting's viewpoint for the volatility behavior of stock markets," Economic Modelling, Elsevier, vol. 30(C), pages 776-791.
    15. Neha Seth & Monica Sighania, 2017. "Financial market contagion: selective review of reviews," Qualitative Research in Financial Markets, Emerald Group Publishing, vol. 9(4), pages 391-408, November.

    More about this item

    Keywords

    Volatilities and Correlations; Weekly Returns; Multivariate t; Financial Interdependence; VaR diagnostics; 2008 Stock Market Crash;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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