IDEAS home Printed from https://ideas.repec.org/a/vrs/ecothe/v52y2014i2p166-183n4.html
   My bibliography  Save this article

Testing The Performance Of The Investment Portfolio Using Block Bootstrap Method

Author

Listed:
  • Radovanov Boris

    (University of Novi Sad, Faculty of Economics in Subotica, Serbia)

  • Marcikić Aleksandra

    (University of Novi Sad, Faculty of Economics in Subotica, Serbia)

Abstract

The aim of this paper is to create a stable model of investment portfolio optimization through a high degree of diversification and reduction of sudden changes in the allocation with monitoring of the dynamics of the impact factor. In this sense, there is bootstrap application procedure, which, without an excessive number of constraints involved in the optimization process provides solutions based on uncertain information. Thus defined, the optimization method has been patented by Michaud (1999) entitled re-sampled efficiency. Accordingly, this paper offers a comparison of the performance block bootstrap optimization models and traditional Markowitz's model inside and outside of the sample by applying the most frequently traded stocks on the BSE. The results show a better performance out of the sample and the presence of a larger number of shares forming the portfolio through bootstrap methodology. However, only through the traditional optimization process could be attained optimum according to the required limits. Such effects can be observed by comparing the limits of efficiency obtained through these optimization models. However, optimization-based methods bootstrap finds its place in reducing errors of assessment resulting from the limited sample size.

Suggested Citation

  • Radovanov Boris & Marcikić Aleksandra, 2014. "Testing The Performance Of The Investment Portfolio Using Block Bootstrap Method," Economic Themes, Sciendo, vol. 52(2), pages 166-183, June.
  • Handle: RePEc:vrs:ecothe:v:52:y:2014:i:2:p:166-183:n:4
    DOI: 10.1515/ethemes-2014-0012
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/ethemes-2014-0012
    Download Restriction: no

    File URL: https://libkey.io/10.1515/ethemes-2014-0012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Michaud, Richard O. & Michaud, Robert O., 2008. "Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation," OUP Catalogue, Oxford University Press, edition 2, number 9780195331912.
    2. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    3. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    4. Francois Delcourt & Mikael Petitjean, 2011. "To what extent is resampling useful in portfolio management?," Applied Economics Letters, Taylor & Francis Journals, vol. 18(3), pages 239-244.
    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. Silva, A. Christian & Prange, Richard E., 2007. "Virtual volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 507-516.
    2. John Y. Campbell & Yeung Lewis Chanb & M. Viceira, 2013. "A multivariate model of strategic asset allocation," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part II, chapter 39, pages 809-848, World Scientific Publishing Co. Pte. Ltd..
    3. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    4. Gerlich, Nikolas & Rostek, Stefan, 2015. "Estimating serial correlation and self-similarity in financial time series—A diversification approach with applications to high frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 84-98.
    5. 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).
    6. Firoozye, Nikan & Tan, Vincent & Zohren, Stefan, 2023. "Canonical portfolios: Optimal asset and signal combination," Journal of Banking & Finance, Elsevier, vol. 154(C).
    7. Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2020. "Does sophistication of the weighting scheme enhance the performance of long-short commodity portfolios?," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 164-180.
    8. Leo Schubert, 2006. "Long-Short Portfolio," Economic Analysis Working Papers (2002-2010). Atlantic Review of Economics (2011-2016), Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, vol. 5, pages 1-11, December.
    9. Hasler, Michael & Khapko, Mariana & Marfè, Roberto, 2019. "Should investors learn about the timing of equity risk?," Journal of Financial Economics, Elsevier, vol. 132(3), pages 182-204.
    10. Hubáček, Ondřej & Šír, Gustav, 2023. "Beating the market with a bad predictive model," International Journal of Forecasting, Elsevier, vol. 39(2), pages 691-719.
    11. Wu, Bo & Li, Lingfei, 2024. "Reinforcement learning for continuous-time mean-variance portfolio selection in a regime-switching market," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    12. Platanakis, Emmanouil & Sutcliffe, Charles & Ye, Xiaoxia, 2021. "Horses for courses: Mean-variance for asset allocation and 1/N for stock selection," European Journal of Operational Research, Elsevier, vol. 288(1), pages 302-317.
    13. Goddard, John & Onali, Enrico, 2012. "Self-affinity in financial asset returns," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 1-11.
    14. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    15. Ma, Guiyuan & Siu, Chi Chung & Zhu, Song-Ping, 2019. "Dynamic portfolio choice with return predictability and transaction costs," European Journal of Operational Research, Elsevier, vol. 278(3), pages 976-988.
    16. Fletcher, Jonathan, 2021. "International equity U.S. mutual funds and diversification benefits," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 246-257.
    17. Newton, David & Platanakis, Emmanouil & Stafylas, Dimitrios & Sutcliffe, Charles & Ye, Xiaoxia, 2021. "Hedge fund strategies, performance &diversification: A portfolio theory & stochastic discount factor approach," The British Accounting Review, Elsevier, vol. 53(5).
    18. Zhang, Zhichao & Chau, Frankie & Xie, Li, 2012. "Strategic Asset Allocation for Central Bank’s Management of Foreign Reserves: A new approach," MPRA Paper 43654, University Library of Munich, Germany.
    19. Huffman, Stephen P. & Moll, Cliff R., 2013. "An examination of the relation between asymmetric risk measures, prior returns and expected daily stock returns," Review of Financial Economics, Elsevier, vol. 22(1), pages 8-19.
    20. Chavez-Bedoya, Luis & Rosales, Francisco, 2021. "Reduction of estimation risk in optimal portfolio choice using redundant constraints," International Review of Financial Analysis, Elsevier, vol. 78(C).

    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:vrs:ecothe:v:52:y:2014:i:2:p:166-183:n:4. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.