IDEAS home Printed from https://ideas.repec.org/a/cpn/umkdem/v11y2011p41-54.html

Bayesian Optimal Portfolio Selection in the MSF-SBEKK Model

Author

Listed:
  • Anna Pajor

    (Cracow University of Economics)

Abstract

The aim of this paper is to investigate the predictive properties of the MSF-Scalar BEKK(1,1) model in context of portfolio optimization. The MSF-SBEKK model has been proposed as a feasible tool for analyzing multidimensional financial data (large n), but this research examines forecasting abilities of this model for n = 2, since for bivariate data we can obtain and compare predictive distributions of the portfolio in many other multivariate SV specifications. Also, approximate posterior results in the MSF-SBEKK model (based on preliminary estimates of nuisance matrix parameters) are compared with the exact ones.

Suggested Citation

  • Anna Pajor, 2011. "Bayesian Optimal Portfolio Selection in the MSF-SBEKK Model," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 41-54.
    • Handle: RePEc:cpn:umkdem:v:11:y:2011:p:41-54
    as

    Download full text from publisher

    File URL: http://www.dem.umk.pl/dem/archiwa/v11/03_Pajor_A.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jacek Osiewalski & Anna Pajor, 2009. "Bayesian Analysis for Hybrid MSF-SBEKK Models of Multivariate Volatility," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(2), pages 179-202, November.
    2. Aguilar, Omar & West, Mike, 2000. "Bayesian Dynamic Factor Models and Portfolio Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 338-357, July.
    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. Vilkkumaa, Eeva & Liesiö, Juuso & Salo, Ahti, 2014. "Optimal strategies for selecting project portfolios using uncertain value estimates," European Journal of Operational Research, Elsevier, vol. 233(3), pages 772-783.
    2. Gruber, Lutz F. & West, Mike, 2017. "Bayesian online variable selection and scalable multivariate volatility forecasting in simultaneous graphical dynamic linear models," Econometrics and Statistics, Elsevier, vol. 3(C), pages 3-22.
    3. Aßmann, Christian & Boysen-Hogrefe, Jens & Pape, Markus, 2012. "The directional identification problem in Bayesian factor analysis: An ex-post approach," Kiel Working Papers 1799, Kiel Institute for the World Economy.
    4. Varga, Katalin & Szendrei, Tibor, 2025. "Non-stationary financial risk factors and macroeconomic vulnerability for the UK," International Review of Financial Analysis, Elsevier, vol. 97(C).
    5. Conti, Gabriella & Frühwirth-Schnatter, Sylvia & Heckman, James J. & Piatek, Rémi, 2014. "Bayesian exploratory factor analysis," Journal of Econometrics, Elsevier, vol. 183(1), pages 31-57.
    6. Niko Hauzenberger & Maximilian Bock & Michael Pfarrhofer & Anna Stelzer & Gregor Zens, 2018. "Implications of macroeconomic volatility in the Euro area," Papers 1801.02925, arXiv.org, revised Jun 2018.
    7. Vitoratou, Silia & Ntzoufras, Ioannis & Moustaki, Irini, 2016. "Explaining the behavior of joint and marginal Monte Carlo estimators in latent variable models with independence assumptions," LSE Research Online Documents on Economics 57685, London School of Economics and Political Science, LSE Library.
    8. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    9. Shinichiro Shirota & Yashiro Omori & Hedibert Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochasti Volatility Model," Business and Economics Working Papers 224, Unidade de Negocios e Economia, Insper.
    10. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    11. Jean-Francois Richard & Roman Liesenfeld, 2007. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Working Paper 322, Department of Economics, University of Pittsburgh, revised Jan 2004.
    12. James Sampi, 2016. "High Dimensional Factor Models: An Empirical Bayes Approach," Working Papers 75, Peruvian Economic Association.
    13. Necati Tekatli, 2007. "Generalized Factor Models: A Bayesian Approach," UFAE and IAE Working Papers 730.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
    15. Anna Pajor, 2005. "Bayesian Analysis of Stochastic Volatility Model and Portfolio Allocation," FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making, in: Władysław Milo & Piotr Wdowiński (ed.), Acta Universitatis Lodziensis. Folia Oeconomica nr 192/2005 - Issues in Modeling, Forecasting and Decision-Making in Financial Markets, edition 1, volume 127, chapter 14, pages 229-249, University of Lodz.
    16. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2009. "Multivariate Stochastic Volatility," Springer Books, in: Thomas Mikosch & Jens-Peter Kreiß & Richard A. Davis & Torben Gustav Andersen (ed.), Handbook of Financial Time Series, chapter 16, pages 365-400, Springer.
    17. Pfarrhofer, Michael & Stelzer, Anna, 2025. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Macroeconomic Dynamics, Cambridge University Press, vol. 29, pages 1-1, January.
    18. Chew Lian Chua & G. C. Lim & Penelope Smith, 2008. "A Bayesian Simulation Approach to Inference on a Multi-State Latent Factor Intensity Model," Melbourne Institute Working Paper Series wp2008n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    19. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    20. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Working Papers in Economics 2018-4, University of Salzburg.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:11:y:2011:p:41-54. 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.