IDEAS home Printed from https://ideas.repec.org/a/cpn/umkdem/v13y2013p145-162.html

Empirical Verification of World’s Regions Profitability in Dynamic International Investment Strategy

Author

Listed:
  • Anna Czapkiewicz

    (AGH University)

  • Artur Machno

    (AGH University)

Abstract

The main goal of the work is to present the empirical verification of the investment attractiveness in a given world financial region. The attractiveness of a region is represented by the share of assets from this region in the optimal portfolio. The multivariate GARCH model has been used to describe international dependencies. Optimal portfolios based on Value at Risk and Expected Shortfall minimization have been compared to the Markowitz portfolio. Indications, which should be taken into account by investors willing to invest in different world regions, have been presented as the result.

Suggested Citation

  • Anna Czapkiewicz & Artur Machno, 2013. "Empirical Verification of World’s Regions Profitability in Dynamic International Investment Strategy," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 13, pages 145-162.
    • Handle: RePEc:cpn:umkdem:v:13:y:2013:p:145-162
    as

    Download full text from publisher

    File URL: https://apcz.umk.pl/DEM/article/view/DEM.2013.008/2917
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Giulio Palomba, 2008. "Multivariate GARCH models and the Black-Litterman approach for tracking error constrained portfolios: an empirical analysis," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 10(4), pages 379-413.
    4. 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.
    5. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    6. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    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. 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.
    2. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    3. 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.
    4. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    5. Aslanidis, Nektarios & Martinez, Oscar, 2021. "Correlation regimes in international equity and bond returns," Economic Modelling, Elsevier, vol. 97(C), pages 397-410.
    6. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
    7. 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.
    8. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2008. "Comovements between US and UK stock prices: the roles of macroeconomic information and timevarying conditional correlations," Economics Discussion Paper Series 0805, Economics, The University of Manchester.
    9. Roumpis, Efthymios & Syriopoulos, Theodore, 2014. "Dynamics and risk factors in hedge funds returns: Implications for portfolio construction and performance evaluation," The Journal of Economic Asymmetries, Elsevier, vol. 11(C), pages 58-77.
    10. repec:wyi:journl:002141 is not listed on IDEAS
    11. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    12. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    13. Riccardo Lucchetti & Luca Pedini, 2025. "Correction to: The Spherical Parametrisation for Correlation Matrices and its Computational Advantages," Computational Economics, Springer;Society for Computational Economics, vol. 65(4), pages 2449-2450, April.
    14. 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.
    15. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
    16. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    17. 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.
    18. 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.
    19. Annastiina Silvennoinen & Timo Teräsvirta, 2009. "Multivariate GARCH Models," Springer Books, in: Thomas Mikosch & Jens-Peter Kreiß & Richard A. Davis & Torben Gustav Andersen (ed.), Handbook of Financial Time Series, chapter 9, pages 201-229, Springer.
    20. Massimiliano Caporin & Riccardo (Jack) Lucchetti & Giulio Palomba, 2020. "Analytical Gradients of Dynamic Conditional Correlation Models," JRFM, MDPI, vol. 13(3), pages 1-21, March.
    21. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    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:cpn:umkdem:v:13:y:2013:p:145-162. 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: Miroslawa Buczynska (email available below). General contact details of provider: http://www.wydawnictwoumk.pl .

    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.