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Ryzyko kwantylowe wybranych otwartych akcyjnych funduszy inwestycyjnych

Author

Listed:
  • Anna Rutkowska-Ziarko

    (Uniwersytet Warmińsko-Mazurski w Olsztynie)

  • Kamila Sobieska

    (Uniwersytet Warmińsko-Mazurski w Olsztynie)

Abstract

The subject of the article is the risk related to stock investment funds. In the research, the quantile measures of risk were used, in particular value at risk and conditional value at risk. The aim was to determine and compare the risk of selected stock investment funds. An additional objective was the evaluation of the influence of length of the investment period on the risk of analysed funds. The investment funds of small and medium-sized companies were deemed the riskiest ones. The quintile risk in all analysed investment funds grew with the length of the investment period.

Suggested Citation

  • Anna Rutkowska-Ziarko & Kamila Sobieska, 2016. "Ryzyko kwantylowe wybranych otwartych akcyjnych funduszy inwestycyjnych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 40, pages 491-502.
    • Handle: RePEc:sgh:annals:i:40:y:2016:p:491-502
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    References listed on IDEAS

    as
    1. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
    2. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    3. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
    4. Timotheos Angelidis & Alexandros Benos, 2008. "Value-at-Risk for Greek Stocks," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 67-104, March-Jun.
    Full references (including those not matched with items on IDEAS)

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