IDEAS home Printed from https://ideas.repec.org/a/ris/ecoint/0822.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.iei1946.it/upload/rivista_articoli/allegati/212_bonganleyaricfinal.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    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.
    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. 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.

    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. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    2. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    3. 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.
    4. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    5. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2008. "Co-movements between US and UK stock prices: the roles of macroeconomic information and time-varying conditional correlations," Centre for Growth and Business Cycle Research Discussion Paper Series 96, Economics, The University of Manchester.
    6. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    7. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    8. Annastiina Silvennoinen & Timo Teräsvirta, 2009. "Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 373-411, Fall.
    9. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    10. Aslanidis, Nektarios & Osborn, Denise R. & Sensier, Marianne, 2008. "Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations," Working Papers 2072/8950, Universitat Rovira i Virgili, Department of Economics.
    11. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    12. repec:hum:wpaper:sfb649dp2012-034 is not listed on IDEAS
    13. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    14. Vasiliki D. Skintzi & Spyros Xanthopoulos-Sisinis, 2007. "Evaluation of correlation forecasting models for risk management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 497-526.
    15. Kaijian He & Kin Keung Lai & Guocheng Xiang, 2012. "Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach," Energies, MDPI, vol. 5(4), pages 1-26, April.
    16. Fengler, Matthias R. & Okhrin, Ostap, 2012. "Realized copula," SFB 649 Discussion Papers 2012-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. Billio, Monica & Caporin, Massimiliano, 2009. "A generalized Dynamic Conditional Correlation model for portfolio risk evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2566-2578.
    18. Xiangdong Long & Liangjun Su & Aman Ullah, 2009. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model Variables with Econometric Applications," Working Papers 200908, University of California at Riverside, Department of Economics, revised Jul 2009.
    19. M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management," CESifo Working Paper Series 1358, CESifo.
    20. Nakatani, Tomoaki & Teräsvirta, Timo, 2008. "Positivity constraints on the conditional variances in the family of conditional correlation GARCH models," Finance Research Letters, Elsevier, vol. 5(2), pages 88-95, June.
    21. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.

    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

    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:ris:ecoint:0822. 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: Angela Procopio (email available below). General contact details of provider: https://edirc.repec.org/data/cacogit.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.