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Evaluating density forecasts from models of stock market returns

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  • Gabriela De Raaij
  • Burkhard Raunig
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    Abstract

    Density forecasts have become important in finance and play a key role in modern risk management. Using a flexible density forecast evaluation framework that extends the Berkowitz likelihood ratio test this paper evaluates in- and out-of-sample density forecasts of daily returns on the DAX, ATX and S&P 500 stock market indices from models of financial returns that are currently widely used in the financial industry. The results indicate that GARCH-t models produce good in-sample forecasts. No model considered in this study delivers fully acceptable out-of-sample forecasts. The empirical findings emphasize that proper distributional assumptions combined with an adequate specification of relevant conditional higher moments are necessary to obtain good density forecasts.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/1351847042000255652
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

    Volume (Year): 11 (2005)
    Issue (Month): 2 ()
    Pages: 151-166

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    Handle: RePEc:taf:eurjfi:v:11:y:2005:i:2:p:151-166

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    Web page: http://www.tandfonline.com/REJF20

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    Related research

    Keywords: Density forecasting; forecast evaluation; risk management; GARCH models;

    References

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