Evaluating density forecasts from models of stock market returns
AbstractDensity 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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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal The European Journal of Finance.
Volume (Year): 11 (2005)
Issue (Month): 2 ()
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