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Assessing Portfolio Market Risk in the BRICS Economies: Use of Multivariate GARCH Models

Author

Listed:
  • BONGA-BONGA, Lumengo

    (University of Johannesburg, Johannesburg,South Africa)

  • NLEYA, Lebogang

    (University of Johannesburg, Johannesburg,South Africa)

Abstract
This paper compares the performance of the different models used to estimate portfolio value-at-risk (VaR) that combines assets in the currency and equity markets in the BRICS economies. Portfolio VaR is estimated with three different multivariate risk models, namely the constant conditional correlation (CCC), the dynamic conditional correlation (DCC) and asymmetric DCC (ADCC) GARCH models. Risk performance measures such as the average deviations, quadratic probability function score and the root mean square error are used to back-test the performance of the models at 99%. The results indicate that portfolios with more weight to currency and less to equities prove to be the best way of minimizing possible losses when investing in BRICS. La valutazione del rischio di mercato nei BRICS tramite l’utilizzo di modelli GARCH multivariati Questo studio confronta la performance di diversi modelli nella stima del Value at Risk negli investimenti in valuta e nei mercati azionari dei BRICS. Il Value at Risk è calcolato tramite tre diversi modelli a rischio multivariato, precisamente il modello CCC (Constant Conditional Correlation), il DCC (Dynamic Conditional Correlation) e il DCC(ADCC) GARCH. Le misure di performance come la deviazione media, il valore della funzione quadratica delle probabilità e l’errore quadratico minimo sono i parametri usati per testare la robustezza dei modelli al 99%. I risultati indicano che gli investimenti che danno maggior peso alla valuta e meno alle azioni sono quelli che riducono al minimo le possibili perdite in caso di investimenti nei BRICS.

Suggested Citation

  • BONGA-BONGA, Lumengo & NLEYA, Lebogang, 2018. "Assessing Portfolio Market Risk in the BRICS Economies: Use of Multivariate GARCH Models," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 87-128.
    • Handle: RePEc:ris:ecoint:0822
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    References listed on IDEAS

    as
    1. Jeroen Rombouts & Marno Verbeek, 2009. "Evaluating portfolio Value-at-Risk using semi-parametric GARCH models," Quantitative Finance, Taylor & Francis Journals, vol. 9(6), pages 737-745.
    2. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value‐at‐Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, June.
    3. Luc, BAUWENS & Walid, BEN OMRANE & Erick, Rengifo, 2006. "Intra-Daily FX Optimal Portfolio Allocation," Discussion Papers (ECON - Département des Sciences Economiques) 2006005, Université catholique de Louvain, Département des Sciences Economiques.
    4. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    5. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    6. Yuan-Hung Hsu Ku & Jai Jen Wang, 2008. "Estimating portfolio value-at-risk via dynamic conditional correlation MGARCH model - an empirical study on foreign exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 15(7), pages 533-538.
    7. Lumengo Bonga-Bonga & Jamela Hoveni, 2013. "Volatility Spillovers between the Equity Market and Foreign Exchange Market in South Africa in the 1995-2010 Period," South African Journal of Economics, Economic Society of South Africa, vol. 81(2), pages 260-274, June.
    8. André A. P. Santos & Francisco J. Nogales & Esther Ruiz, 2013. "Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 400-441, March.
    9. 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.
    10. Saurabh Ghosh & Mridul Saggar, 2017. "Volatility spillovers to the emerging financial markets during taper talk and actual tapering," Applied Economics Letters, Taylor & Francis Journals, vol. 24(2), pages 122-127, January.
    11. Darryll Hendricks, 1996. "Evaluation of value-at-risk models using historical data," Economic Policy Review, Federal Reserve Bank of New York, vol. 2(Apr), pages 39-69.
    12. Lumengo Bonga-Bonga, 2017. "Assessing the readiness of the BRICS grouping for mutually beneficial financial integration," Review of Development Economics, Wiley Blackwell, vol. 21(4), pages 204-219, November.
    13. Annastiina Silvennoinen & Timo Teräsvirta, 2005. "Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations," Research Paper Series 168, Quantitative Finance Research Centre, University of Technology, Sydney.
    14. Mensi, Walid & Hammoudeh, Shawkat & Kang, Sang Hoon, 2017. "Dynamic linkages between developed and BRICS stock markets: Portfolio risk analysis," Finance Research Letters, Elsevier, vol. 21(C), pages 26-33.
    15. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    16. Boubaker, Heni & Raza, Syed Ali, 2017. "A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets," Energy Economics, Elsevier, vol. 64(C), pages 105-117.
    17. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-362, July.
    18. Yuan-Hung Hsu Ku, 2008. "Student-t distribution based VAR-MGARCH: an application of the DCC model on international portfolio risk management," Applied Economics, Taylor & Francis Journals, vol. 40(13), pages 1685-1697.
    19. Berger, T. & Missong, M., 2014. "Financial crisis, Value-at-Risk forecasts and the puzzle of dependency modeling," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 33-38.
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    Cited by:

    1. Morema, Kgotso & Bonga-Bonga, Lumengo, 2020. "The impact of oil and gold price fluctuations on the South African equity market: Volatility spillovers and financial policy implications," Resources Policy, Elsevier, vol. 68(C).
    2. repec:agr:journl:v:4(621):y:2019:i:4(621):p:201-218 is not listed on IDEAS
    3. Ben Salem, Ameni & Safer, Imene & Khefacha, Islem, 2022. "Value-at-Risk (VAR) Estimation Methods: Empirical Analysis based on BRICS Markets," MPRA Paper 113350, University Library of Munich, Germany, revised May 2022.
    4. Lebotsa Daniel Metsileng & Ntebogang Dinah Moroke & Johannes Tshepiso Tsoku, 2020. "The Application of the Multivariate GARCH Models on the BRICS Exchange Rates," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 9, July.
    5. Siva Kiran GUPTHA. K & Prabhakar RAO. R, 2019. "GARCH based VaR estimation: An empirical evidence from BRICS stock markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(621), W), pages 201-218, Winter.
    6. Ameni Ben Salem & Imene Safer & Islem Khefacha, 2021. "Value at Risk Estimation For the BRICS Countries : A Comparative Study," Post-Print hal-03502428, HAL.

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    More about this item

    Keywords

    Portfolio Value-at-Risk; Multivariate GARCH; Risk Performance Measures; BRICS;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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