IDEAS home Printed from https://ideas.repec.org/a/wut/journl/v2y2006p5-30.html
   My bibliography  Save this article

The impact of institutional investors on risk and stock return autocorrelations in the context of the Polish pension reform

Author

Listed:
  • Henryk Gurgul
  • Paweł Majdosz

Abstract

The main aim of this paper is to examine the relationship between the increasing share of institutional investors resulting from the pension reform in Poland and stock return autocorrelation as well as risk level on the Warsaw Stock Exchange. The problem under consideration is investigated by applying the M–GARCH model for the individual stocks included in the investment portfolios of the pension funds operating in Poland.

Suggested Citation

  • Henryk Gurgul & Paweł Majdosz, 2006. "The impact of institutional investors on risk and stock return autocorrelations in the context of the Polish pension reform," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(2), pages 5-30.
  • Handle: RePEc:wut:journl:v:2:y:2006:p:5-30
    as

    Download full text from publisher

    File URL: https://ord.pwr.edu.pl/assets/papers_archive/53%20-%20published.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sentana, Enrique & Wadhwani, Sushil B, 1992. "Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data," Economic Journal, Royal Economic Society, vol. 102(411), pages 415-425, March.
    2. Axel Börsch‐Supan & Florian Heiss & Alexander Ludwig & Joachim Winter, 2003. "Pension Reform, Capital Markets and the Rate of Return," German Economic Review, Verein für Socialpolitik, vol. 4(2), pages 151-181, May.
    3. Holger Bonin & Joan Gil & Concepció Patxot, 2001. "Beyond the Toledo agreement: the intergenerational impact of the Spanish Pension Reform," Spanish Economic Review, Springer;Spanish Economic Association, vol. 3(2), pages 111-130.
    4. Eduardo Walker & Fernando Lefort, 2002. "Pension Reform And Capital Markets: Are There Any (Hard) Links?," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 5(2), pages 77-149.
    5. Robert D. Brooks & Robert W. Faff & Michael D. McKenzie, 1998. "Time†Varying Beta Risk of Australian Industry Portfolios: A Comparison of Modelling Techniques," Australian Journal of Management, Australian School of Business, vol. 23(1), pages 1-22, June.
    6. Klaus Schmidt-Hebbel, 1998. "Does Pension Reform Really Spur Productivity, Saving, and Growth?," Working Papers Central Bank of Chile 33, Central Bank of Chile.
    7. Anton Dobronogov & Les Mayhew, 2000. "Pension Reform in a Highly Informalized Post-Soviet Economy," Public Economics 0004008, University Library of Munich, Germany.
    8. LeBaron, Blake, 1992. "Some Relations between Volatility and Serial Correlations in Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 65(2), pages 199-219, April.
    9. Axel Börsch‐Supan & Florian Heiss & Alexander Ludwig & Joachim Winter, 2003. "Pension Reform, Capital Markets and the Rate of Return," German Economic Review, Verein für Socialpolitik, vol. 4(2), pages 151-181, May.
    10. Queisser, Monika & Bailey, Clive & Woodall, John, 1997. "Reforming pensions in Zambia : an analysis of existing schemes and options for reform," Policy Research Working Paper Series 1716, The World Bank.
    11. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    12. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    13. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    14. Michael D. McKenzie & Robert W. Faff, 2003. "The Determinants of Conditional Autocorrelation in Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 26(2), pages 259-274, June.
    15. Gebka, Bartosz & Henke, Harald & Bohl, Martin T., 2006. "Institutional trading and stock return autocorrelation: Empirical evidence on Polish pension fund investors' behavior," Global Finance Journal, Elsevier, vol. 16(3), pages 233-244, March.
    16. Toshiaki Watanabe, 2002. "Margin requirements, positive feedback trading, and stock return autocorrelations: the case of Japan," Applied Financial Economics, Taylor & Francis Journals, vol. 12(6), pages 395-403.
    17. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    18. 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.
    19. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    20. Josef Lakonishok & Andrei Shleifer & Robert W. Vishny, 1991. "Do Institutional Investors Destabilize Stock Prices? Evidence on Herding and Feedback Trading," NBER Working Papers 3846, National Bureau of Economic Research, Inc.
    21. Barclay, Michael J. & Warner, Jerold B., 1993. "Stealth trading and volatility : Which trades move prices?," Journal of Financial Economics, Elsevier, vol. 34(3), pages 281-305, December.
    22. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    23. Brooks, Robert D. & Faff, Robert W. & McKenzie, Michael D. & Ho, Yew Kee, 2000. "U.S. Banking Sector Risk in an Era of Regulatory Change: A Bivariate GARCH Approach," Review of Quantitative Finance and Accounting, Springer, vol. 14(1), pages 17-43, January.
    24. Tsui, Albert K. & Yu, Qiao, 1999. "Constant conditional correlation in a bivariate GARCH model: evidence from the stock markets of China," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(4), pages 503-509.
    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. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    2. Marshall, Andrew & Maulana, Tubagus & Tang, Leilei, 2009. "The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 250-259, December.
    3. Giovanni Barone-Adesi & Francesco Audrino, 2006. "Average conditional correlation and tree structures for multivariate GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 579-600.
    4. Kusen, Alex & Rudolf, Markus, 2019. "Feedback trading: Strategies during day and night with global interconnectedness," Research in International Business and Finance, Elsevier, vol. 48(C), pages 438-463.
    5. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
    6. Kin-Yip Ho & Albert K Tsui, 2008. "Volatility Dynamics in Foreign Exchange Rates : Further Evidence from the Malaysian Ringgit and Singapore Dollar," Finance Working Papers 22571, East Asian Bureau of Economic Research.
    7. Fotini Economou & Konstantinos Gavriilidis & Bartosz Gebka & Vasileios Kallinterakis, 2022. "Feedback trading: a review of theory and empirical evidence," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 15(4), pages 429-476, February.
    8. Yilmaz, Tolgahan, 2010. "Improving Portfolio Optimization by DCC And DECO GARCH: Evidence from Istanbul Stock Exchange," MPRA Paper 27314, University Library of Munich, Germany.
    9. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    10. Kuper, Gerard H. & Lestano, 2007. "Dynamic conditional correlation analysis of financial market interdependence: An application to Thailand and Indonesia," Journal of Asian Economics, Elsevier, vol. 18(4), pages 670-684, August.
    11. Mark, Joy, 2011. "Gold and the US dollar: Hedge or haven?," Finance Research Letters, Elsevier, vol. 8(3), pages 120-131, September.
    12. Maximilian-Benedikt Herwarth Kohn & Pedro L. Valls Pereira, 2017. "Speculative bubbles and contagion: Analysis of volatility’s clusters during the DotCom bubble based on the dynamic conditional correlation model," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1411453-141, January.
    13. Panayiotis F. Diamandis & Anastassios A. Drakos & Georgios P. Kouretas & Leonidas P. Zarangas, 2012. "Asset allocation in the Athens stock exchange: a variance sensitivity analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 17(2), pages 167-181, April.
    14. Rahim, Adam Mohamed & Masih, Mansur, 2016. "Portfolio diversification benefits of Islamic investors with their major trading partners: Evidence from Malaysia based on MGARCH-DCC and wavelet approaches," Economic Modelling, Elsevier, vol. 54(C), pages 425-438.
    15. Marçal, Emerson Fernandes & Pereira, Pedro L. Valls, 2008. "Testing the Hypothesis of Contagion Using Multivariate Volatility Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 28(2), November.
    16. Tae-Hwy Lee & Millie Yi Mao & Aman Ullah, 2021. "Estimation of high-dimensional dynamic conditional precision matrices with an application to forecast combination," Econometric Reviews, Taylor & Francis Journals, vol. 40(10), pages 905-918, November.
    17. Alexei Kolokolov, 2011. "Futures hedging: Multivariate GARCH with dynamic conditional correlations (in Russian)," Quantile, Quantile, issue 9, pages 61-75, July.
    18. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    19. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    20. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.

    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:wut:journl:v:2:y:2006:p:5-30. 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: Adam Kasperski (email available below). General contact details of provider: https://edirc.repec.org/data/iopwrpl.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.