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Historical Data in the Context of Risk Prediction

Author

Listed:
  • Grzegorz Mentel

    (Department of Quantitative Methods, Rzeszow University of Technology, Rzeszow, Poland)

  • Jacek Brożyna

    (Department of Quantitative Methods, Rzeszow University of Technology, Rzeszow, Poland)

Abstract

An important element of a successful prediction of the future behavior of financial instruments is a thorough analysis of possible determinants that effect the final estimates of the prognostic models. In the case of VaR models, we may include here specified values of significance levels or assumed smoothing constant. Also, an important element is the number of historical observations that should be taken into account in order to estimate the scale of the risk. In the article, therefore, a study of the effectiveness of certain value-at-risk models in the context of historical data had been carried out. Thus, an attempt to assess the impact of the amount of historical data on the effectiveness of the VaR indications had been made.

Suggested Citation

  • Grzegorz Mentel & Jacek Brożyna, 2014. "Historical Data in the Context of Risk Prediction," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(1), pages 48-60, January.
    • Handle: RePEc:mir:mirbus:v:4:y:2014:i:1:p:48-60
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    References listed on IDEAS

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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